However, as organizations seek skilled employees to assist their organizations in properly incorporating AI tools into their operating environments, the types of skills and employees needed are broader than one might think. AI is not a single monolith.

There are many tools, categories, and branches of AI which an organization can leverage to solve problems.

As a result, understanding the job to be done and the types of AI tools that exist is an essential prerequisite to help organizations identify the right skills they may need to support their goals.

In fact, a recent survey on AI in the workplace and higher education indicated that understanding the nuances and different capabilities around AI is an opportunity area.

There are several different skill areas that organizations can look into on a global basis that will help staff their teams to support the wave of advancements that companies can benefit from with the AI boom. Let’s look at those now.

1. Data science and programming

Two almost universal skill areas that organizations need to invest in if they want to leverage AI capabilities are in data science and programming, and foundationally these skill areas come from having good mathematical backgrounds.

Data science skills

Ultimately, the majority of AI models are consuming and responding to data in some way shape or form. The stimuli, data format and consumption pattern of the AI model may differ, but the output of AI decisions and responses depend on data.

Individuals skilled in data science, and the principles behind it, are essential to identifying and implementing the right kinds of methods to solve organizational problems using AI.

Programming skills

Equally important are individuals that are skilled in programming languages that support AI such as Python, Julia, and R. To build tools suited to solving the problems organizations have, there is a need for skilled programmers to build and enhance these tools to be aligned to the organization’s goals and consumer’s needs.

Although several off the shelf AI tools and programs can potentially be incorporated into an organization’s infrastructure through application programming interfaces (APIs), many organizations find having talented in-house programmers remains important to customize output and results to match organizational needs.

As organizations specify the type of AI branch or approach they want to lean on to solve their problems, this may require the organization to specify the types of specializations they want their data science and programming talent to be versed in (i.e. machine learning, neural networks, pattern recognition, etc.), but the general need for data science and programming resources will be consistent.

2. UX/UI and front-end developers

Data science and programming resources are essential in creating working AI tools and algorithms that help solve the problems an organization may have, but they are only one part of the equation of getting these tools in the hands of employees or customers to achieve their intended results.

To do this organizations need skilled employees that are well versed in UI/UX design and front-end developers that can bring these designs to life.

UX/UI design skills

Although it may be a benefit to have UX/UI designers that understand coding and programming in some organizations, this is not essential when searching for skilled UX/UI designers.

Additionally, when looking for the best UX/UI resources to support the implementation of AI into your customer or employee-facing tools it is also important to recognize the difference between UX (product effectiveness to solve the job to be done) and UI (product aesthetics to guide digital user behaviors) skills as both are needed to create the most effective synergy between AI tool and intended user outcome.

Front-end developer skills

To get the designs of UX/UI resources into the hands of users it is important to have front-end developers. In a sense, the data scientists and programmers that create the AI models and tools could be considered the back-end development team.

Front-end developers, on the other hand, are experts in using web applications or similar tools to bring the design principles and back-end AI code into a format that works for general-user consumption.

Although both of these roles and skill set areas may not get as much focus as compared to AI programming and data science roles, they will be an essential part of incorporating AI tools and products effectively into the customer experience. This could influence adoption rates and product sustainability long term.

3. Skills to support adoption and effectiveness of AI tools

Two things that stand out concerning AI are:

1. The goal of AI is to use tools to replicate human-like behavior and thoughts
2. AI represents a large change for how we will approach work and tasks in the future

With these concepts in mind, it shouldn’t be surprising that skills in these areas are also helpful to organizations that are looking to leverage AI into their infrastructure.

Given that AI tries to replicate components of the human experience, individuals that are balanced in critical thinking, verbal, linguistic, and problem-solving skills are needed. In fact, some organizations are specifically looking for individuals that have strong writing skills and experience interacting with AI tools to support their organizational efforts.

Organizations should keep a keen eye out for those who understand human behavior and can interact with AI tools effectively, as skills in these areas can assess the value and/or get the most out of AI applications.

Change and adaptability skills

The incorporation of AI into our lives and the workplace also represents a big change for many, and there is some trepidation around this. To offset these fears organizations may also seek talent that is well-versed in change management principles.

The best fusion of AI into the job environment is to use it to unlock the talent of our human capital to focus more on complex and engaging tasks for them and leveraging AI as a peer that can remove roadblocks from reaching this state by having AI run through time-consuming or staid activities.

Experts in change management can help organizational cultures pivot to an adoptive rather than adversarial stance with the implementation of AI and so resources in this area should be considered.

Skills in critical thinking, linguistic, and change management areas may not be top of mind for many employers as they seek to leverage AI into their companies; however, organizations that look at skills that go beyond the functional aspects of just building AI protocols and algorithms may find they have a competitive advantage over others.

AI-relevant skills will continue to evolve

The conversation around the impact and level of disruption that AI will cause continues to evolve, but if there is one absolute truth about AI, it is this: AI will change the way we work and how much time we spend on certain functions over others.

Because of this, the modern organization needs to prepare for these changes by looking at skill-set needs on a holistic basis that focuses on implementing AI, but also critically, on the responsible use and adoption of these tools to meet organizational goals and results to improve productivity and products.

Marc Booker, Ph.D., is Vice Provost of Strategy at the University of Phoenix. 

The post AI skills in the workplace: what hiring teams should look for now appeared first on Recruiting Resources: How to Recruit and Hire Better.

Dive in and start building the perfect blueprint tailored to your unique challenges – your future star performers will thank you.

Related: Build a high-performing sales team: your comprehensive guide

Let’s start with common sales team organization structures and org charts for each:

1. Functional sales team structure

A software company has a sales team that is divided into three main functions: lead generation, account executives, and customer success.

The lead generation team is responsible for finding and qualifying potential customers, the account executives are responsible for closing deals, and the customer success team is responsible for onboarding and retaining customers.

2. Geographic sales team structure

A multinational pharmaceutical company has divided its sales team based on geographic regions: North America, Europe, Asia, and Latin America.

Each regional team is responsible for all sales activities within its assigned region, allowing them to cater to the specific needs and regulations of their respective markets.

3. Market-based sales team structure

A financial services company has different sales teams for each of its market segments: individual investors, small businesses, and institutional clients.

Each team understands the unique needs and challenges of its specific market segment.

4. Product sales team structure

A large tech company with multiple product lines, such as laptops, smartphones, and software services, has separate sales teams for each product line.

Each team specializes in understanding and selling its specific product.

5. Hybrid sales team structure

A large consumer goods company uses a hybrid structure. It has a geographic structure for its field sales team, with different teams responsible for different regions.

It also has a product-based structure for its inside sales team, with different teams specializing in different product categories.

6. Account-based sales team structure

A B2B software company that sells high-value enterprise solutions has an account-based sales structure.

Each sales team is assigned a set of key accounts that they are responsible for managing and growing.

7. Channel sales team structure

A manufacturing company sells its products through a network of distributors and retailers.

It has a channel sales team that is responsible for managing these partner relationships, providing them with product training, and supporting their sales efforts.

8. Customer success sales team structure

A SaaS company has a sales team that focuses on acquiring new customers and a customer success team that focuses on retaining and growing existing accounts.

The sales team works on bringing in new business, while the customer success team ensures that existing customers are satisfied and identifies opportunities for upselling or cross-selling.

Different team building plans to think about

Regardless of which organizational structure you follow above, there will be different scenarios for you to consider when building your sales team. Some of these are longer-term, others are quick and nearly off-the-cuff.

Related: Build a sales team with ChatGPT – with prompt examples

Let’s start with a potential scenario, variables to consider, and what the sales team organizational structure might include for each of these. Consider bundling one or more of the following scenarios into your overall sales team structure to align your sales system with overall business strategies.

Scenario 1: you are just getting started

Variables:

• Limited resources
• Small customer base
• Need to establish market presence

Organizational structure:

• Startup sales lead: Multi-tasker who handles account management and some admin tasks
• Generalist sales reps: Team members who handle everything from lead generation to closing deals
• Customer success associate: Focuses on onboarding and retaining the initial customer base

Scenario 2: you have landed a new funding round and you’re looking to grow

Variables:

• Sudden influx of resources
• Aggressive expansion plans
• High growth targets.

Organizational structure:

• Growth manager: Specializes in scaling businesses and managing large teams
• Recruitment specialist: Fast-tracks hiring of new team members
• Sales reps by tier: Separated into junior and senior reps, each focusing on different customer segments
• Sales analyst: Uses data analytics to optimize sales strategies

Scenario 3: you’ve got a new product in place and you’re looking to push it

Variables:

• Newly launched product
• Need for market adoption
• Focus on product-specific sales

Organizational structure:

• Product sales manager: Specializes in the new product and its market positioning
• Product evangelists: Focus on storytelling and explaining the product’s USP
• Cross-selling sales reps: Leveraging existing customer base to introduce the new product
• Technical support: On-call for product-specific inquiries and demonstrations

Scenario 4: you’re facing high attrition rates

Variables:

• High turnover
• Low morale
• Dissatisfied employees

Organizational structure:

• Team lead: Responsible for morale and personal development
• Retention specialist: Focused on employee engagement
• Sales reps: Generalists with rotation across different accounts to prevent burnout

Scenario 5: you’re transitioning to remote work

Variables:

• Remote work
• Need for smoother communication
• Need for streamlined coordination

Organizational structure:

• Remote team manager: Oversees remote operations
• Communication liaison: Ensures effective communication and project tracking
• Sales reps: Allocated to regions/time zones for customer convenience

Scenario 6: you’re entering a new market

Variables:

• Unknown market dynamics and consumer behavior

Organizational structure:

• Market specialist: Expert in the new market’s nuances
• Cultural advisor: Provides cultural training and guidance
• Localized sales reps: Hired from the local market for authentic engagement

Scenario 7: you have a seasonal business

Variables:

• Fluctuating sales depending on the season or time of year

Organizational structure:

• Seasonal team lead: Oversees seasonal hires and operations
• Stock analyst: Focuses on inventory and demand prediction
• Temporary sales reps: Hired for peak season, focus on short-term goals

Scenario 8: you’re facing stiff competition

Variables:

• Increased competition affecting sales and market share
• Sudden ascent of a new presence in the marketplace

Organizational structure:

• Strategy lead: Focuses on competitive tactics and market analysis
• Product evangelist: Specializes in the USP and brand storytelling
• Sales reps: Special training in negotiation and advanced selling techniques

Time to start building

Building a sales team isn’t a one-size-fits-all endeavor. Depending on your company’s unique circumstances, goals, and challenges, your organizational structure should adapt and evolve.

Whether you’re just breaking ground, scaling rapidly with new funding, launching a product, or grappling with issues like high attrition and remote work, the right setup can be a game-changer. It aligns your resources and focuses your efforts, serving as the backbone of your sales strategy.

Remember, an effective sales team is not just about the number of people but about putting the right people in the right roles. These eight scenarios offer a versatile blueprint for assembling a sales team that’s not just built for the present, but also adaptable for the future.

The post 8 sales team structure models – plus scenarios to build them out appeared first on Recruiting Resources: How to Recruit and Hire Better.

The executive embodies the visionary, the manager, and the technical specialist – the three personalities that are needed for a business to succeed.

They’re central to the functioning and future success of your business. Executives are hired and fired based on the revenue they bring to the organization.

That’s why when a new executive joins your core leadership team – be it a CMO, a CFO, or a COO – effective executive onboarding is a must-have strategic necessity, even more so than normal onboarding.

Related: CEO vs. COO: What’s the difference? and CEO vs. CFO: What’s the difference?

Traditional onboarding methods often miss the mark when it comes to getting new executives up to speed. They’re time-consuming. They’re tedious. They lack a personal touch. They’re inefficient.

Here, ChatGPT can be a transformative tool for modernizing your executive onboarding and positioning your business for future success.

Let’s dive into how a ChatGPT-guided executive onboarding process differs from traditional methods, and offer a step-by-step guide on how you can use ChatGPT in your executive onboarding plan.

Traditional vs. ChatGPT-enabled executive onboarding

ChatGPT and AI tools have their own limitations, but their benefits far surpass those of more traditional methods of onboarding.

With ChatGPT’s help, executives can frame their decisions, explore possibilities, and think of alternatives they may have missed otherwise. A recent article by Harvard Business Review explored how ChatGPT can help executives make better decisions.

Forward-thinking executives and business leaders embrace new ways of doing things and then adapt them if they improve on the old methods.

An onboarding plan made with ChatGPT improves on more conventional onboarding methods in several ways:

1. Increased efficiency

ChatGPT can streamline your executive onboarding plan and free up valuable time for your HR team.

Traditional onboarding involves a mountain of paperwork and often grueling manual effort, a waste of your HR team’s resources.
The traditional method is also much more prone to human error and subjective bias.

2. Personalization

ChatGPT can create a personalized onboarding experience tailored to each executive’s needs and role – like a personalized concierge or onboarding assistant you only have to pay $20 a month.

In contrast, traditional onboarding fits all of your new executives in a box. It gives your bright and promising new executive talent a more generic and less engaging experience.

3. Scalability

Using ChatGPT for executive onboarding is much more scalable, and is easy to implement whether you’re onboarding one executive or 10.

Having multiple executives join the team at the same time – such as what might happen if your business is in a more advanced stage of growth – just isn’t something that traditional onboarding methods can deal with very well. It can make it hard to give all of them the individual guidance and attention they need. That’s a one-way ticket to stretching your HR team thin.

How to use ChatGPT for executive onboarding

When a new executive takes the helm, they need to get brought up to speed fast and learn everything they need to know about what’s what, who’s who, and how things get done.

This is a problem with slower and less efficient traditional onboarding methods, which can often leave gaps that make the new executives have to take shots in the dark. A 2020 workplace learning report from LinkedIn showed that 49% of learners don’t have time to learn at work.

Let’s look at some of the ways you can use ChatGPT to expedite this process and bring your new leadership into the fold.

1. Drafting an offer letter

The offer letter is usually the first official document your new executive receives from your company. It sets the tone of their entire experience working together with you, be it months, years, or decades.

This isn’t a problem with ChatGPT, which can automate the drafting process and create a customized offer letter that aligns with your company’s policies and the specific role they’ll be entering into.

Example prompt: “Please generate an offer letter for a Chief Marketing Officer with a starting salary of $200,000.”

Note that you may have to input a few specific, necessary details, like the position, salary, and benefits. Give ChatGPT that input, and let it take care of the rest.

Example prompt: “Please generate an offer letter for a Chief Marketing Officer with a starting salary of $200,000, including the following benefits: comprehensive health insurance, 401(k) with 5% company match, 20% performance bonus, stock options, 25 vacation days, $5,000 for professional development, $10,000 for relocation, and $100 monthly for wellness.”

2. Creating a mentorship program

Mentorship isn’t just for entry-level rank-and-file employees.

New executives might need a mentor who’s been with the team for longer when they’re first starting – at least while they’re finding their feet and learning the lay of the land.

Where ChatGPT can be an asset in this regard is in creating your mentorship program, in such a way that provides the new executive with guidance, resources, and support they’ll need to succeed in their new position.

Example prompt: ”Suggest a mentorship program outline for a new Chief Technology Officer.”

3. Training executives on leadership

Leadership training equips your new executives with the skills and knowledge they need to lead your team effectively and further your company’s strategic goals.

ChatGPT can create personalized leadership training programs after analyzing the executive’s role, career goals, and the company’s strategic objectives.

That way, the leadership training stays relevant but also directly aligned with your company’s business objectives.

Example prompt: “Create a 90-day leadership training plan for a new CFO, whose career goals include streamlining financial operations and leading an IPO. The company aims to achieve 20% YoY revenue growth, expand into new international markets, and reduce its carbon footprint.”

You can also give them additional resources and pathways for further learning while you’re at it.

Example prompt: “What are some leadership books and resources suitable for this new position?”

4. Create a strategic alignment plan

Your strategic alignment is the compass that your new executive uses to make sure the ship is on course and headed in the right direction.

Give ChatGPT data like the executive’s role, career goals, and the company’s strategic objectives, and it can make a comprehensive strategic alignment plan that outlines how the executive can help the company achieve those goals.

Example prompt: “Draft a strategic alignment plan for a new Vice President of Sales whose responsibilities include overseeing the sales team, setting quarterly targets, and building client relationships. The company aims to increase market share by 15%, launch two new products, and improve customer satisfaction rates.”

You can also give them some KPIs to use as benchmarks for their success. A prompt you can follow up with may be:

Example prompt: “List key performance indicators for this position.”

5. Building networks

If you want to build a million-dollar business, you need to shake 10 million hands.

In the realms of entrepreneurship in business, who you know is often more important than what you know. Networking is key for savvy executives who want to build professional connections – both in and out of your organization – that add value to the team.

Here, ChatGPT can be useful for:

Internal networking

Identifying key departments and teams that the executive can connect with.

Example prompt: “List internal teams that a new General Manager should meet in the first month at a SaaS company focused on HR solutions.”

External networking

Web-enabled ChatGPT-4 (using plugins such as VoxScript and Wolfram) can recommend industry events and conferences where the executive can meet potential partners or clients.

Example prompt: “Suggest networking events for a new Chief Human Resources Officer.”

6. Performance tracking

After a few months have gone by, at some point it’ll be time to sit down with the new executive and have a chat about how things are going.

You, the executive, and maybe one or two other members of the leadership team will sit down together at a conference table or a Zoom call to measure the executive’s success against the KPIs outlined in previous stages of the executive onboarding process.

You can use ChatGPT to simplify this process by making your generating performance review templates for the new executive’s role.

Let’s say you need a list of customized KPIs. You could have ChatGPT generate the list of KPIs for you based on the executive’s role and the company’s objectives.

Example prompt: “Generate KPIs for a Chief Financial Officer focused on cost reduction and revenue growth.”

Then, once you have those KPIs, you can use them to track the executive’s performance during their quarterly review.

Example prompt: “Create a performance review template for a new Chief Financial Officer.”

7. Compliance and legal training

Ambition, vision, and motivation are all well and good. However, they need to be kept in check by a strong integrity so that the company stays on the right side of the law, and stays committed to doing the right thing.

The consequences of violating industry violations and upholding contractual obligations can be severe – even brutal – but what kind of executive has the time to sift through piles of legal documents?

ChatGPT can create your compliance checklists and review legal documents for your executive. The executive can then use these briefs to make sure your organization is legally compliant.

In the long run, this can save the executive much of their valuable time, and minimize the likelihood of causing expensive legal errors.

Example prompt: “Create a compliance checklist for a new executive in the healthcare industry.”

ChatGPT can also give you advice on legal documents to review before the new executive starts their new role, based on their industry.

It’s important to know though that ChatGPT is not a legal expert, and only serves as a place to start. You’ll want to have any templates it creates reviewed by professional legal counsel to ensure it’s accurate and in line with your industry’s regulations.

Example prompt: “Generate a list of legal documents a new executive in a fintech startup needs to review.”

Use ChatGPT to get your best and brightest up to speed

Integrating ChatGPT into your executive onboarding process can address the limitations of traditional onboarding methods. It just doesn’t help you onboard new executives faster, it helps you do it smarter, more effectively, and more strategically.

Build ChatGPT into your onboarding plan for executives together with Workable’s onboarding tools, and create a bigger, brighter, better leadership team.

For more ways you can use ChatGPT in your HR processes, check out our series of ChatGPT tutorials.

The post ChatGPT for executive onboarding: hiring the big shots appeared first on Recruiting Resources: How to Recruit and Hire Better.

This month, we have a look at the three metrics again with this in mind, and bring some fresh insights to the table. Ready? Let’s get started!

How we’re looking at data

We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.

For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.

As always, we look at the worldwide trends for three common SMB hiring metrics:

• Time to Fill (TTF)
• Total Job Openings (JO)
• Candidates per Hire (CPH)

Let’s start analyzing!

Main highlights

The three main highlights for this month’s Hiring Pulse are:

• We’re in a “new normal” when it comes to Time to Fill and Candidates per Hire
• Technology may be a huge factor in both
• Seasonal and sectoral hiring are potentially impacting job opening trends

1. Time to Fill

For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of August are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.

Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.

Got that? Good. Let’s have a look at the monthly TTF trend through to the end of August against the average of 2019, based on jobs that have been filled:

In short: the time it’s taking employers to fill open roles is still at a historically lower point. Sure, it took a relatively dramatic jump from May’s 80.5 to June’s 84.4, but it’s coming down again.

In last month’s Hiring Pulse, we noted how the TTF trend seems to be stabilizing when compared with previous years – this is still happening. What’s interesting is that the stabilization is happening at a much lower level. Cliche alert: this may be the new normal in hiring.

In short, while the undulations of the TTF trend are normal, the actual trend itself is much lower than years past. Two thoughts happening here: first, there are far more candidates than ever before meaning it’s easier to find the ideal candidate for a job.

Second, the added bandwidth due to the deluge of candidates is easier to manage because HR professionals and hiring teams are using software to optimize their processes (yes, that’s a cheap plug for Workable!).

Now, are we seeing the same trend in job openings? Let’s have a look.

2. Total Job Openings

Total job openings represent the total number of job openings activated across the entire Workable network.

As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of August.

Last month, we pointed out a surprising drop in job postings across all companies from June’s 7.6 to July’s 7.1, which turns out to be anomalous when compared with previous Junes and Julys.

July to August this year is a little different – rising from 7.1 new job postings per company in July to 7.4 in August. In 2022, the change was just an increase of .1 of one job, and in 2021, it was a drop of .2.

But when we look at the size buckets, the differences start to stand out. Companies with 200 or more full-time employees (FTEs) posted 17.4 jobs in August on average, up from July’s 16.9. Small businesses (50 or fewer FTEs) also saw growth – from 5.4 to 5.6.

The big story this time is in the mid-sized businesses (51-200 FTEs). Averages in this size bucket went from 5.0 in July to 5.8 in August – moving it higher than the average for small businesses for the first time since May.

There are two stories here:

First, this jump in general which marks nearly a full new job per mid-sized business in August.

And second, that companies with 51-200 FTEs were hiring less than their smaller cousins for three months in a row from May to July.

Why? One theory is that it’s seasonal. June, July, and August are traditionally big-travel seasons and that puts a lot of pressure on a hospitality sector that’s already struggling to fill gaps in their teams. The triple-whammy of surging tourism numbers after COVID, the Great Resignation (which hit restaurants hard), and of course the traditional tourist season all lead to an increase in demand for short-term workers ahead of time.

Perhaps it’s not so much that medium-sized businesses slowed their hiring – it’s more that small businesses increased theirs. According to BLS, the leisure and hospitality sector has gained an average of 61,000 jobs per month over the prior 12 months ending in August 2023, making it one of the fastest-growing sectors in terms of hiring in the United States. And that sector has many small businesses.

Now, let’s look at the Candidates per Hire trend.

3. Candidates per Hire

Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.

Now that Let’s look at what’s going on here through August:

What we said above about a “new normal in hiring”? This is another example of it. The highest the CPH trend ever reached in our dataset before 2023 was in October 2020, when the index reached 140.3. That was also the only time it had reached more than 140 – in other words, 40% higher than the monthly average for 2019.

Now? It’s gone upwards of 140 for five straight months – and above 170 for the last three months. It’s got to come down to earth at some point once the job market stabilizes, but what interests us is that job openings aren’t coming down at all during the course of 2023. You’d think there would be a direct correlation between fewer job openings and more candidates per jobs – but not here.

This is likely a fallout of the Great Resignation. Many people dumped their jobs over the last couple of years to the tune of more than 4 million quits every single month from June 2021 to December 2022 – and that number is steadily falling throughout 2023 reaching 3.55 million quits for July, the lowest for a single month in the United States since before the pandemic. And in pre-COVID times, 3.5 million quits was pretty normal for a given month.

All these people who left their jobs and not moving on to new ones – some of them launched freelance careers, others started their own business, and others still just took off to a cabin in Maine to live the rest of their lives in solitude. And – we mentioned this last month as well – it’s either not working out so well for them, or they miss the old daily grind and the social life that can come with an interesting day-to-day job. So, back to the job hunt they go.

Combine this with the increase in layoffs this year (482K layoffs from January to July compared with one-third of that in the same period in 2022), and you have a situation where there are many more candidates looking for jobs. Hence, the rise in the CPH trend.

What’s going on here?

Whatever your experience may be in terms of hiring, you’ve got one thing at the top of your mind: find the absolute perfect candidate for the role. Yes, it’s nice to have a growing candidate pool because it means you have the pick of the crop – but is that necessarily the case? Just because you’re now getting 120 applications for a job compared with 80 for the same job last year doesn’t mean you now have 30 ideal candidates this year compared with 20 last year.

When you have a growing pool of candidates, you run the risk of saturation. There’s also desperation – on the side of candidates. There are those who are returning to work after an extended period of time, and there are those quickly trying to land on their feet after losing their job in an unfortunate reorg at their previous company.

We made a side reference to HR technology up there and how it’s helping hiring teams better manage the recruitment pipeline and that’s speeding up the process to a filled job.

Well, technology does cut both ways – candidates also have the benefits of HR technology and now have one-click-apply and resume parsing options when applying for jobs.

Add AI to the mix; candidates can just plug their resume *and* the job description into ChatGPT or Claude and tell it to create the perfect cover letter for that specific job. The AI will even calibrate the resume so it best fits the opportunity.

So, as it becomes easier to go through hundreds of resumes a day, it also becomes harder, because the applications are becoming more plentiful and sophisticated all the time. It reminds one of the old Stephen Wright joke about putting a humidifier and dehumidifier into a room and letting them work it out.

Back to the plot: you want to focus on finding the *right* candidates, not the *most* candidates. That distinction is very important. To attract the *right* candidates, you need to understand what would compel them to apply for a role with your organization.

There are tools to help you out here – including custom application forms and knockout questions  so candidates self-select out of the process, candidate search functionalities, and of course Workable’s AI Recruiter.

And guess what? We already asked 1,250 workers to understand their wants and needs at a high level, and the result is the Great Discontent for 2023. Have a look, and package what you’ve learned into your careers page and your job descriptions – and reap the rewards.

Thoughts, comments, disagreements? Send them to content@workable.com, with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in May!

The Hiring Pulse: Methodology

Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.

To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.

For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.

And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.

The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.

The post Your Hiring Pulse report for September 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

Now more than ever, you’re going to need the best and brightest working for you and by your side if you want a sales team that can succeed in the age of AI.

In this respect, ChatGPT can potentially be a godsend for you. ChatGPT and other generative AI tools can automate and enhance many of your existing sales processes, so you can spend more time and energy thinking of ways to close more leads, get more customers, and drive growth.

A strong sales team is the backbone of any successful business. ChatGPT can help you strategically build a better sales team that’s stronger, smarter, and more efficient than ever.

In this tutorial, we’ll offer some ways you can use ChatGPT to build a sales team – one that’s forward-thinking, adaptable, and innovative.

1. Recruiting top sales talent

Half the battle in building a sales team is finding the right people.

B2B sales is a notoriously competitive industry, and not everyone is cut out for it. Being good at sales requires a blend of strategic thinking, adaptability, resilience, and determination to meet goals and overcome challenges, and a fierce ambition coupled with the ethical integrity to keep it in check.

Finding the right mix of all those qualities is rare. Using ChatGPT in your recruitment process can not only help expedite your sales team recruitment but can make it easier for you to find the best sales reps.

Using ChatGPT for job description writing

There is a fine art to making a good job description. It’s about striking the right balance between outlining the key responsibilities of the role, attracting the right candidates, and sparking their interest in the position.

When you tell it your needs and requirements of the sales reps you’re looking for, ChatGPT can create compelling job descriptions. ChatGPT can tailor the job description to the role,

Give ChatGPT a clear outline of the responsibilities of the role, your company culture, and your expectations in the position, and ChatGPT can make a job description that helps you find the right candidates for your sales team.

You can also use it in conjunction with Workable’s AI job description generator to create something that’s more personalized and aligned with your business goals.

Example prompt: “Write a job description for a Sales Manager position focusing on B2B SaaS sales.”

Screening resumes with ChatGPT

Sales is also an oversaturated field, and sales hiring teams often have to sort through a mountain of resumes and cover letters before they arrive at a candidate who’s worth talking to.

With ChatGPT’s help, you can dig through all the filler resumes and unqualified applicants and find the star candidates who can be a true asset to your team.

ChatGPT can quickly analyze resumes, summarize key qualifications and work experiences, and help you gauge whether a candidate is a good fit for the role.

Example prompt: “Analyze the following resume and summarize the key qualifications for a Sales Executive role.”

2. Streamlining team onboarding

Finding rockstars to hire for your sales team is one thing, but you also need to onboard them and get them up to speed with how you do things before they can start making money for you.

Your sales onboarding process lays the foundation for your new hire’s success and helps them get started on the right foot.
ChatGPT is useful here as well because it can optimize and streamline your onboarding experience and get your recruits on their phones and in the field as soon as possible.

Creating onboarding guides with ChatGPT

An onboarding guide helps your new sales reps to understand your company policies, sales tools, and tech stack, and immerse themselves in your company culture. They can start on day 1 already feeling as though they’re a part of the team.

Give ChatGPT a structured outline for your onboarding, and it can create detailed content for an onboarding guide that tells the new hire everything they need to know.

Example prompt: “Create an onboarding guide for new sales team members, including company policies, sales tools, and team culture.”

Automating FAQ responses

The new hires on your sales team will naturally have a lot of questions as they get their feet wet and learn the lay of the land.
Giving them immediate and consistent answers will help things go smoothly all around – both for them and for you.

You can program ChatGPT to field common questions and offer guidance and support where it is needed. That can be explaining your key performance indicators, or outlining your company values.

Example prompt: “Generate a response to a common question from new hires for an entry-level sales rep position: ‘What are the key performance metrics for sales representatives at our company?’”

3. Enhancing sales training

Training your new team will enable them for their future success and give them the skills, knowledge, and know-how to excel on your sales team.

You can use ChatGPT to enhance your training, nurture your new talent, and help them stay prepared for modern sales challenges they’ll encounter on the job.

Developing sales scripts with ChatGPT

Persuasive sales scripts help to guide the conversation in a way that earns the lead’s trust and allows things to flow naturally.

ChatGPT can generate persuasive sales scripts and templates tailored to specific products, audiences, or real-world scenarios.

Your sales reps can use these scripts as a starting point when interacting with potential customers.

When you give ChatGPT context and objectives to follow, it can make sales scripts that align perfectly with your sales goals.

Example prompt: “Write a sales script for introducing our latest product to potential clients. The product is called ‘X’, its core benefits and features are ‘Y’, and it’s made by company ‘Z’.”

Creating role-playing scenarios for training

There is no better teacher than experience. Practice makes perfect, as the saying goes.

ChatGPT can create realistic role-playing situations emulating hypothetical scenarios that the reps and executives on your sales team might encounter in the real world.

These scenarios might include anything from negotiating deals to relationship building. Playing through these scenarios in a controlled setting can help your reps hone essential skills before trying them out on real customers. With them, your sales reps can practice handling rejection and keeping the conversation going.

Example prompt: “Design a role-playing scenario for training sales representatives in handling objections. The scenario should involve a potential client objecting to the price of our latest product, and the sales representative must use value-based selling techniques to overcome the objection.”

4. Sales prospecting and lead generation

In the world of sales, the name of the game is finding leads.

Finding potential clients and engaging with them with a personalized, conversational approach to outreach between success and failure when it comes to building a sales pipeline.

ChatGPT offers you some unique opportunities here when it comes to optimizing your sales process.

Generating personalized outreach emails with ChatGPT

Striking a balance between personalization and scalability is a common one in sales and marketing. Here, ChatGPT can be the key to making a personal outreach email that’s scalable.

If you tell it your client’s industry, needs, and interests, ChatGPT can create engaging emails that get your lead’s attention, invite a response from them, and convince them to purchase from you. Then, you can repeat this process no matter how many times you do it, be it hundreds or thousands.

Example prompt: “Compose a personalized email to a potential client in the B2B SaaS industry, expressing interest in their business needs and highlighting our product’s ability to streamline their sales process.”

Brainstorming sales strategies with ChatGPT

Innovation is what drives success in sales. Making cutting-edge strategies that speak right to the heart of your customer’s wants and needs is what separates an exceptional salesperson from a mediocre one.

For this reason, sales managers are always looking for fresh new ideas and practical strategies to reach their customers. ChatGPT can be very useful in this creative and strategizing process.

Give ChatGPT insights into your target markets, your competitors, and your business goals, and ChatGPT can brainstorm a list of creative and effective sales strategies. You can then take the strategies it comes up with and adapt them to your needs.

Example prompt: “Generate a list of 10 innovative sales strategies for targeting the healthcare industry, focusing on our product’s ability to enhance patient engagement and streamline administrative tasks.”

5. Sales performance analysis and feedback

Sales performance analysis lets you know that whatever you’re doing is working.

Having the right insights shows you what needs improvement, what’s doing well, and how individual team members are progressing.

ChatGPT has valuable tools to enhance your performance analysis and cut right to the heart of the information you need to drive your sales team’s success.

Automating sales performance reports with ChatGPT

You can use ChatGPT to create a standardized sales performance template to highlight key metrics such as revenue growth, conversion rates, customer satisfaction, sales rep achievements, and areas for improvement.

That automation can help ensure consistent reporting that allows you as the sales manager to track the progress of your reps over time.

Example prompt: “Create a monthly sales performance report template focusing on key metrics such as conversion rates, revenue growth, top-performing products, and areas for improvement.”

Providing constructive feedback through ChatGPT

Feedback provides an opportunity for growth, but it has to be delivered with care, empathy, and precision.

You can use ChatGPT to draft constructive feedback emails that are clear, supportive, and actionable. You can tell your sales rep what they’re doing well, and give them suggestions for future development.

Outline specific areas of success and improvement, and ChatGPT can help you deliver feedback that encourages growth.

Example prompt: “Write a feedback email to a sales representative who exceeded quarterly targets but struggled with customer engagement, highlighting areas of improvement and success, and providing actionable steps to enhance customer relationships.”

6. Integrating ChatGPT with existing sales tools

Your team doesn’t just include your sales reps, but the digital tools you use to be good at your jobs as well.

Sales teams rely on various tools as a part of their technology stack, like their Customer Relationship Management (CRM) systems and sales enablement platforms. Integrating ChatGPT with these existing tools can unlock whole other levels of efficiency.

ChatGPT-4 comes with a Plugin Store that lets it integrate with many popular sales and marketing tools such as Zapier, and others for specific marketing and sales use cases like personalized outreach and sales prospecting.

You can also ask for ChatGPT’s help in integrating with other sales tools in your tech stack using your API key.

Example prompt: “Describe the process of integrating ChatGPT with Salesforce for automated data entry, including the necessary API connections, data mapping, and testing procedures.”

Ethical considerations and best practices

Using ChatGPT and AI tools can be so helpful for building your sales team that you’ll wonder how you ever managed without them.

With that said, this technology is still very new and comes with several ethical considerations that should be addressed before implementing it.

Here are a few considerations to keep in mind to ensure responsible and ethical use:

Transparency and accountability

Clearly communicate with your team and customers how and why you use AI in your sales process. Implement ways to keep yourself accountable with regular audits and reviews.

Bias and fairness

Be on the lookout for any potential biases that can arise from the training data or algorithms. Make sure that the decisions the AI makes are fair and don’t discriminate against particular groups.

Ethical guidelines and training

Create and keep ethical guidelines for using AI in sales. Provide training to your sales teams on responsible AI practices, including understanding its potential for bias, ethical considerations of AI technology, and how to use these tools appropriately.

ChatGPT can help you create the best sales team – if you know how to use it

ChatGPT and generative AI technology represent a watershed moment in how businesses approach sales team building.

The potential of this technology is still being explored and is largely untapped. Whether it’s enhancing customer interactions, automating data entry, or providing valuable insights, using ChatGPT to build your core sales team can give you an edge over your competitors who are still just dabbling with it. Explore, experiment, and find out for yourself what it can do!

The post Build a sales team with ChatGPT – with prompt examples appeared first on Recruiting Resources: How to Recruit and Hire Better.

AI marketing for recruitment is evolving rapidly, and it is essential to stay up-to-date with these changes.

Recently, we had the opportunity to watch a very insightful interview organized by Hung Lee, the Curator at Recruiting Brainfood, with guests such as Steven Rothberg, the Founder of College Recruiter among others. They discussed how Google’s AI search is transforming recruitment marketing.

Recruitment marketing has gone through some major changes lately, which means that there are some new challenges and opportunities for all you HR professionals and small business owners out there.

We decided to elaborate more on this and help you out with the most recent updates.

Recruitment marketing hits a new level

There has been a lot happening in recruitment marketing lately, wouldn’t you agree?

The significant increase in the use of artificial intelligence and machine learning, the central role of employer branding, the automation of communication processes, the emphasis on sharing candidate experiences, the implementation of personalization techniques, and the growing utilization of video for engaging and interactive content are some of the trends that we can see happening now. You may know all these features if you use an HRIS.

While all of these things are grabbing our attention, we are constantly being in front of new developments that take recruiting marketing to new levels. This is what makes working in HR so exciting today.

Actually, these trends indicate a shift towards more efficient and targeted approaches in attracting and retaining top talent, as well as adapting to the changing dynamics of the job market.

But, how google AI is changing the way we work? Let’s find out.

Related: 11 recruitment time-saving tips for the overburdened recruiter

Google AI search for recruitment marketing

The rise and development of numerous LLM tools in the market is forcing companies to be aware of their next steps as it will have a significant impact on their way of working.

ChatGPT is changing the way we search online by introducing a conversational way of gaining information just by asking.

Google AI may have arrived late, but it will attempt to expand this conversational type of searching to new levels.

That being said, in terms of recruiting, this may mean that Google AI promises to assist you with more visibility if you optimize your job ads with relevant keywords and attract talents for your pool.

Google’s generative experience aims to enhance the user experience by providing comprehensive information directly in search results, eliminating the need for navigation across multiple websites.

If we want our company and job briefs to be displayed in Google AI search results, we must redefine our recruitment marketing strategy.

And it all begins with your employer branding. Let’s see why.

Employer branding & AI Marketing

In order to achieve better results, we must redefine our recruitment marketing strategy. And it all begins with your employer branding. Let’s see why. Employer branding.

Imagine a potential candidate searching for your role and company.

Conversational AI tools may gather information about the company, reviews, and publications available online, and provide outcomes.

We need to produce content and build an identity that showcases what we want to display about ourselves to the world when these search engines gather critical information about us.

By saying that, we don’t mean to manipulate the procedure, just to pay attention to your work and your brand’s value.

“It’s a tremendous way of getting your brand known to people who might be in your future talent pipeline, but they’re not actively looking for jobs right now”, states Steven Rothberg, College Recruiter in the aforementioned interview.

“It’s a tremendous way of getting your brand known to people who might be in your future talent pipeline, but they’re not actively looking for jobs right now”, states Steven Rothberg.

“If people don’t know the industry sector, they’re just gonna pick out the top brands and they’re gonna say this is the best ones” adds Hung Lee, Curator at Recruiting Brainfood, to the discussion.

From a different perspective, Neil Patel, SEO expert, comments about the Google AI Search: “You can and probably will lose some traffic from this. But at the same time, it will create a better experience for people using Google, which will cause Google’s overall traffic and usage to go up, which should help you continue to get a lot of traffic from Google and potentially even more”.

It becomes clear that keeping up with the latest developments in marketing during the era of generative AI will effectively aid your recruitment efforts.

Adapting recruitment marketing strategies

As the landscape continues to evolve, marketers and recruiters need to adjust their strategies accordingly. It’s essential to optimize content, such as job postings, career pages, and employer value propositions (EVPs), to make sure they’re visible and engaging in search results.

Using images and videos can also help grab users’ attention in the era of generative AI.

The introduction of Google’s generative search experience creates uncertainty for companies in terms of how to adapt their recruitment marketing strategies.

To differentiate themselves and provide a unique user experience, companies may need to

• Invest in interactive content on their career pages. This could include calculators, career mappers, psychometric tests, or other engaging tools that can only be consumed on the website
• Create career pages that will play a crucial role in the validation process for candidates. Instead of being a primary discovery platform, career pages will serve as a place for candidates to verify information about a company and assess whether it aligns with their needs and preferences
• Incorporate conversational elements, such as chatbots, on their career pages to facilitate interactions with candidates. This will allow candidates to ask questions and receive personalized responses, enhancing their engagement with the company’s brand

In order to provide relevant information to both candidates and search engines, companies should focus on creating rich content, including:

• videos
• audios
• blog posts
• employer value propositions (EVPs)

This content will be crucial in shaping the conversational experience and ensuring accurate information is presented by generative AI systems.

The more value you invest in your brand, your copies, and your user or candidate experience, the more AI search tools will extract information from your company to the audience.

But it’s time for a disclaimer now.

The blur line of AI search profit

It appears that there is another game-changing development on the horizon, and this time it’s all about profit. The new era of search engines is keeping their income generation methods under wraps for the time being.

Once we gain a clear understanding of how they will generate revenue, it will mark a new chapter in the world of recruitment marketing.

The balance between organic search and paid search in the AI era will play a significant role in shaping people’s perceptions of the information.

Additionally, the budget of an AI ad campaign will decisively determine how recruitment marketing and digital marketing, in general, will take place.

The importance of human expertise

While AI-driven recruitment strategies offer numerous benefits, human expertise and recruitment agencies would continue to play a crucial role in the recruitment process.
These entities possess valuable information and intuition that AI cannot replicate. Smaller companies may need to leverage networking, offline marketing, and specialized service providers to compete for candidates, while larger companies with more resources can invest in AI-driven recruitment strategies.

Remember that all of these AI tools are making our workflow more efficient by providing automations that save time for us to focus on more important tasks.

Perhaps now we can concentrate more on our efforts to produce more value for our clients and our company, and view all these changes as an opportunity to do so in a more digitized way.

Hopefully, all these efforts will pay off in the long run of AI search.

The post AI is changing recruitment marketing – your next move appeared first on Recruiting Resources: How to Recruit and Hire Better.

Recruitment involves a broad range of skills, tasks, and specialties — it requires efficiency, data assessment, and organization but is also largely dependent on human instinct, experience, and understanding. Using AI for recruitment is the ideal scenario where a technological tool simplifies and enhances the work and expertise of hiring managers.

Integrating AI recruiting tools into your hiring process can automate tedious tasks, reduce the likelihood of human error, and help you make hiring decisions quickly and with greater confidence.

The benefits of artificial intelligence in recruiting

Implementing artificial intelligence in recruiting can optimize your talent acquisition strategy and streamline the workflows associated with hiring and onboarding. Attracting, identifying, and securing top talent involves many moving pieces — different people, tons of paperwork, back and forth communication, a lot of scheduling, and stacks of information to sift through.

Adding recruitment AI tools to the process has benefits that go far beyond cutting down the workload though, such as:

• Reduced time-to-hire: Hiring can be disruptive and expensive. Shortening the cycle without compromising the quality of candidates is in everyone’s best interest.
• Improved candidate experience: A clear, streamlined process that keeps applicants and stakeholders informed along the way shows candidates that you value their time and effort.
  Less bias in hiring: Data-driven insights can help reduce or eliminate unconscious hiring biases, creating a fair and consistent process for each candidate.
• Improved performance: Outsourcing repetitive or data-heavy tasks to recruiting AI tools frees up hiring teams to focus their time and talent on aspects of the process that require a human touch.
• Cost Savings: By automating repetitive tasks, AI can help reduce the need for manual labor and minimize hiring costs associated with the recruitment process.
• Scalability: AI-powered tools can handle large volumes of applicants efficiently, making it easier for companies to scale their recruitment efforts as needed.
  Identifying Passive Candidates: AI tools can search through various online platforms to identify passive candidates who may not have applied directly but possess the required skills and experience.
• Continuous Improvement: AI systems can learn from past interactions and outcomes, allowing them to continuously improve their performance and accuracy over time.
• Personalization: AI can tailor the candidate experience by providing personalized content and recommendations based on a candidate’s background and interests.
• Employee Retention: AI can analyze employee data to identify patterns that indicate potential retention issues, helping organizations take proactive measures to improve employee satisfaction and reduce turnover.
• Increased collaboration: A lot of applicant tracking systems incorporate AI for recruiting; having one central repository for information makes it easy for stakeholders to stay informed and offer opinions.
• Accurate analytics: Data analysis and reporting offered by AI recruiting tools facilitate HR compliance and add quantifiable metrics to the decision-making process.

The most obvious benefits, increased accuracy and efficiency, are valuable day in and day out to hiring teams and candidates alike, but AI has a lot to offer when it comes to attracting and identifying top talent.

How does AI in recruiting work?

The benefits of AI for recruitment sell themselves, but it may still be hard to imagine how AI tools could be integrated into a hiring workflow. The most convenient way to add AI to your recruitment strategy is by implementing an AI-based applicant tracking system (ATS).

Here are some of the features and functionalities that many offer:

Resume Screening: AI-powered systems can automatically screen and analyze resumes, identifying relevant skills, qualifications, and experience. This helps recruiters sift through a large number of applications more quickly, saving time and effort.

• Candidate Sourcing: AI tools can scour various online platforms, job boards, and social media networks to find potential candidates based on specific criteria and keywords, helping to identify passive candidates who may not have applied directly.
• Chatbots and Virtual Assistants: AI-driven chatbots can engage with candidates, answer their questions about the company and job roles, and even conduct preliminary interviews. This provides a more interactive and responsive experience for applicants and helps gather initial information about them.
• Candidate Matching: AI algorithms can compare candidate profiles with the requirements of a job to assess the suitability of applicants. This can help in shortlisting candidates who are the best fit for the position.
• Video Interview Analysis: AI-powered video interview platforms can analyze candidate responses, facial expressions, and tone of voice to assess various traits, such as communication skills and emotional intelligence. This data can help in evaluating candidates more objectively.
• Predictive Analytics: AI can analyze historical data on successful and unsuccessful hires to identify patterns and characteristics that lead to successful outcomes. This information can be used to predict candidate success and make better hiring decisions.
• Diversity and Inclusion Initiatives: AI can be used to identify and minimize unconscious biases in job descriptions, resume screening, and candidate evaluation, thus promoting diversity and inclusion in the hiring process.
• Employee Retention: AI can be used to analyze employee data and identify patterns that may indicate potential retention issues. This helps companies proactively address employee needs and reduce turnover.
• Onboarding and Training: AI-driven systems can provide personalized onboarding and training plans for new hires based on their skills and knowledge gaps, helping them ramp up more quickly and effectively.

Related: Boost your employer branding & retention using AI

The landscape of AI recruiting tools is continuously evolving. When considering AI recruiting tools, it’s important for organizations to assess their specific needs and choose tools that align with their recruitment objectives and values.

Identify existing pain points in your recruitment workflow and research AI recruitment tools that can help you mitigate bottlenecks or obstacles so that you can make hiring decisions efficiently and effectively.

Talent acquisition is essential to the success and longevity of your business. You’re not only hiring for an open role — you’re hiring a piece of the puzzle that makes your organization whole.

A new hire can affect everything from day-to-day performance to overall company culture; enhancing hiring decisions with the help of artificial intelligence is an investment that can pay off for years to come.

The post How to use AI for recruitment appeared first on Recruiting Resources: How to Recruit and Hire Better.

Specifically, 92% of these HR professionals planned to expand their use of AI in at least one related area, including improvement in performance management, payroll processing and benefits administration, recruitment and hiring, onboarding new employees, and employee records management.

And within the next 12 to 18 months, the majority of HR leaders surveyed were planning to substantially increase their utilization of AI.

Within the next 12 to 18 months, the majority of HR leaders surveyed plan to substantially increase their utilization of AI.

The perils of AI tools in HR

The increasing adoption of AI-based tools in human resource management has been a game-changer for HR practitioners, providing transformative tools and solutions to enhance efficiency and improve effectiveness of decision-making.

For example, intelligent automation of mundane and repetitive tasks has enabled HR professionals to focus on more strategic and value-added activities. Moreover, AI has the potential to revolutionize recruitment processes and expand candidates pool by analyzing large volumes of resumes.

However, as with any powerful technology, AI-based solutions should be applied in a responsible way for HR management. There have been numerous examples that uncover biases and inadvertent discrimination of AI-based solutions against fractions of applicants, as a result of faulty databases and incorrect programming.

Related: Ethical AI: guidelines and best practices for HR pros

What can you do?

Companies need to implement AI-based solutions in an ethically and transparent way to address concerns regarding privacy, fairness, and potential bias, ensuring the system does not perpetuate biases or discriminate against certain individuals or groups.

For example, companies will need to carefully select training data and establish regular monitoring of AI algorithms to identify and correct any biases that may arise.

Additionally, transparency and accountability are paramount in AI-enabled HR management, as employees should have access to information about how their data is being collected, used, and protected.

Employers must also prioritize the security and privacy of employee data to mitigate potential risks.

Related: Avoid unintended bias: learn to navigate EEOC in AI and hiring

Legal considerations growing

The European Union has recently approved the AI Act draft legislation, a comprehensive framework aimed at ensuring the responsible and ethical implementation of AI across various industries. According to the AI Act, high-risk AI systems must undergo a thorough conformity assessment procedure before they can be introduced to the market or used within the EU.

To ensure compliance, providers are required to establish, implement, document, and maintain rigorous risk management systems throughout the lifespan of the AI system.

To ensure compliance, providers are required to establish, implement, document, and maintain rigorous risk management systems throughout the lifespan of the AI system.

It is essential to meet stringent requirements to ensure the safe placement of high-risk AI systems on the market. This involves the implementation of robust risk assessment and mitigation systems, coupled with the use of high-quality data sets to avoid any potential discriminatory outcomes.

Clear documentation of the AI system’s purpose, along with detailed user instructions, must be provided to the regulatory authority. An extensive record-keeping system is necessary to promptly identify and address any abnormal results.

Human oversight still paramount

The presence of human oversight is crucial to oversee the system’s operations and deactivate it if necessary. Importantly, the accuracy, robustness, and cybersecurity of the system should meet the appropriate standards.

While technology itself may possess certain capabilities and potentials, it is ultimately the people who wield and utilize these tools that determine their true impact.

HR executives and leadership teams have the power to shape the way technology is used, and their choices and actions can greatly influence its consequences.

It’s not what you do – it’s how

It is crucial to recognize that the real danger lies not in technology itself, but rather in how people choose to employ it. Without responsible and ethical usage, the potential benefits of technology can be overshadowed by its negative implications.

So, understanding the role of individuals in determining the impact of technology is crucial in fostering a harmonious and beneficial relationship between people and the tools they use. Learning and education plays a crucial role in ensuring individuals understand how to navigate emerging technology solutions safely and responsibly.

HR leadership must focus on commitments to values, ensuring the application of AI-based solutions are not undermining the critical human aspect in business.

Find that tech-human sweet spot

Finding the right balance between technology and the human touch is crucial in harnessing the potential of AI for empathetic employee relations in HR. While AI can enhance efficiency and accuracy in various HR processes, it is important to remember that empathy and emotional intelligence are inherent human qualities that cannot be replicated by technology.

HR practitioners and companies must use AI as a tool to support and augment their efforts in creating a more empathetic and human-centric work environment.

By incorporating AI in a thoughtful and strategic manner, organizations can streamline administrative tasks, allowing HR professionals to focus more on building meaningful connections with employees and addressing their individual needs.

Ultimately, the successful implementation of AI in HR hinges upon understanding when and how to leverage technology while preserving the fundamentals of human interaction and empathy in employee relations.

The post The power of AI: with great AI comes great responsibility appeared first on Recruiting Resources: How to Recruit and Hire Better.

AI recruiting software is changing the way organizations attract and identify top talent by eliminating some of the more costly and time-intensive pain points of the hiring process. Supporting your hiring team with AI recruiting tools that improve productivity and enhance hiring decisions can positively affect the performance of your entire organization.

What is artificial intelligence recruiting software?

Artificial Intelligence (AI) recruiting software is a specialized type of HR technology that utilizes artificial intelligence and machine learning algorithms to optimize and automate various aspects of the recruitment and hiring process. AI recruiting software is also commonly referred to as AI-powered applicant tracking software (ATS) or AI recruitment tools.

Artificial intelligence and machine learning excel at performing repetitive tasks, organizing information, and analyzing data quickly and accurately, which helps streamline talent acquisition workflows and facilitate collaborative efforts involved with hiring new employees.

Key features of AI recruiting software

AI recruitment software is designed to assist HR professionals, recruiters, and hiring managers in sourcing, screening, and selecting candidates more efficiently and effectively.

Helpful features and functionalities of AI recruitment software may include the following:

• Candidate Sourcing: AI recruiting software can automatically search and source candidates from various online platforms, job boards, social media, and other sources by using AI algorithms to match job requirements with candidates’ skills and qualifications.
• Resume Parsing: The software can parse and extract relevant information from resumes and CVs submitted by candidates, such as work experience, education, skills, and contact details. This makes it easier to organize and analyze applicant data.
• Candidate Screening: AI algorithms can analyze and assess candidate qualifications against job requirements, shortlisting the most suitable candidates for further consideration. It can identify key phrases, skills, and experience mentioned in resumes to gauge a candidate’s fit for the role.
• Automated Interview Scheduling: Some AI recruiting software can handle interview scheduling by coordinating with candidates and interviewers, reducing the need for manual back-and-forth communication.
• Candidate Engagement: AI-powered chatbots or automated communication tools can engage with candidates, answer frequently asked questions, provide updates on the application process, and maintain candidate interest throughout the recruitment journey.
• Bias Reduction: Advanced AI recruiting software is designed to minimize unconscious bias in the hiring process. By focusing on skills and qualifications, rather than demographic factors, it aims to promote a more diverse and inclusive candidate selection.
• Predictive Analytics: AI-driven recruitment tools can analyze historical data to identify patterns and trends in successful hires, helping HR professionals make data-driven decisions and improve the quality of hires.
• Onboarding Assistance: Some AI recruiting software extends its capabilities to support the onboarding process, providing a seamless transition from candidate to employee.
• Continuous Improvement: The AI algorithms in the software can learn from recruitment data and user interactions, continuously improving their recommendations and matching capabilities over time.

Using AI tools for recruitment can reduce human error, improve the candidate experience, and lead to more confident hiring decisions based on data.

Related: AI, ChatGPT and the human touch in hiring

The importance of AI recruiting software

In the past, making a good first impression was primarily a concern for candidates. However, in today’s competitive job market, organizations need to be putting their best foot forward, as well.

As technological advances continue to reduce time-to-hire, the ability to screen applicants, schedule interviews, make hiring decisions, and communicate quickly and effectively can make a significant difference in the quality of hires.

The recruitment process is continuously evolving due to changes in technology; failing to incorporate AI tools for recruiting into your strategy gives your competitors an unfair advantage.

How to choose AI recruitment software

Investing time and money into implementing a new system is often a little anxiety-inducing, even if you’re confident that it will be an overall improvement. Making changes to an already-existing workflow and getting buy-in from stakeholders can present a host of challenges, making it even more important to choose the right AI recruiting tools the first time.

Get stakeholders involved early on by asking which steps of the current workflow feel cumbersome and/or which features are most likely to benefit your organization. Consider the following as you research your options for AI recruiting software:

Once you’ve narrowed down your options, these questions may help you select the right AI recruiting tool for your organization:

• What specific AI features does the software offer for candidate sourcing and screening?
• Can the AI algorithms be customized to match the organization’s unique job requirements and preferences?
• How accurate and reliable are the AI-driven candidate matches and recommendations?
• What data sources does the AI software use for candidate sourcing and how comprehensive is the candidate database?
• How does the software handle candidate data privacy and security?
• Can the AI recruitment software integrate with the organization’s existing HR systems and tools?
• Does the software provide real-time analytics and insights on the recruitment process? What metrics does it track?
• How does the software handle candidate engagement and communication throughout the recruitment process?
• Does the AI software have the capability to reduce bias in the hiring process? How is this achieved?
• What kind of support and training does the vendor provide for the HR team during implementation and ongoing usage?
• Can the AI recruitment software support high-volume hiring and accommodate peak recruitment periods?
• How does the software handle international recruitment and multilingual capabilities?
• What is the pricing model for the AI software? Are there any additional costs or hidden fees?
• Can the AI recruitment software support both active and passive candidate sourcing?

Furthermore, HR professionals should also consider requesting a live demo or a trial of the AI recruitment software to evaluate its user-friendliness, interface, and overall functionality. Additionally, reading reviews from unbiased sources or seeking references or feedback from other organizations that have used the software can provide valuable insights into its performance and effectiveness.

Taking the time to thoroughly assess the AI recruitment software ensures that your choice will meet the organization’s specific needs and will contribute to a more successful and efficient hiring process.

Using AI recruiting software offers numerous benefits, including time savings, improved candidate matching, enhanced candidate experience, data-driven decision-making, and increased efficiency in the overall recruitment process. By leveraging the power of artificial intelligence, HR professionals can focus on strategic talent acquisition while letting the software handle repetitive tasks and streamline recruitment workflows.

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Generative AI is still very new, and we’re all still figuring out how it works, but it’s already changing the way we attract and hire talent – mostly for the better. From automating routine administrative tasks to offering data-driven insights, ChatGPT and other AI tools are helping recruiters streamline their processes, make better and more informed decisions, and ultimately get more done with less time.

Let’s dive deeper into the different innovative use cases of ChatGPT for recruitment purposes – how it can improve the candidate experience and lead to better hiring outcomes.

The impact of ChatGPT for recruiting

Integrating ChatGPT into recruitment processes helps us recruiters be more efficient at our jobs, so we can offer a better hiring experience for the candidates we work with.

Using ChatGPT and other generative AI tools frees up time that we can use on the higher-value, more strategic aspects of our roles. It also makes life better for candidates by giving them instant responses to queries, and a seamless, interactive recruitment process.

Making use of ChatGPT for recruiting and HR can also make our recruiting process more inclusive. When we use generative AI to craft job descriptions that are free of biased language, we can create a more diverse and inclusive hiring process.

7 clever ways recruiters can use ChatGPT

The power of AI lies in its versatility and adaptability. Processes like onboarding and initial candidate screening are just some of the use cases for using ChatGPT in recruitment, but the possibilities of the technology are potentially limitless.

It’s important to remember, also, that ChatGPT and other AI tools are here to help us enhance our skillsets and help us be better recruiters – not to replace our jobs.

1. Creating dynamic job descriptions

Making the perfect job description is equal parts art and science. It takes a clear understanding of a role and the skills required, and the ability to communicate them effectively.

This is the kind of work that GPT-powered AI tools excel at. Workable has its own AI job description generator which you can use to create a solid foundation.

Then, using ChatGPT or a similar AI tool, you can further refine and enhance it in a way that works in the nuances of job requirements, skills, and other key aspects of the role.

Let’s say you use Workable’s AI job description generator to make a basic job posting for a project manager role in the animation industry and give it a friendly tone:

You can ask ChatGPT to build on that foundation and flesh it out with a prompt like:

“I’ve used Workable’s job description generator to create a basic description for a project manager role. Now, I’d like to add more depth. The role involves overseeing project execution, managing team members, and ensuring the timely delivery of projects. Can you help me elaborate on these responsibilities and suggest some desired skills and qualifications?”

Using ChatGPT in conjunction with other AI and recruitment tools like Workable, you can create dynamic job descriptions that stand out from the crowd amongst dozens of postings for similar roles.

2. Automating initial candidate screening

The average recruiter has to sift through a practically biblical flood of resumes and cover letters to go through the initial screening of candidates for any given role.

AI tools can greatly streamline this process when you train it to review resumes and cover letters and identify the most promising candidates based on specific keywords and required qualifications.

For example: using a prompt such as: “Review these resumes and rank the candidates based on their qualifications for a software engineer position” can help you quickly pick out candidates who match the criteria you’re looking for:

3. Setting up an interactive FAQ chatbot

Candidates have to face off with hundreds of applicants no less deserving than themselves for the same role, so they’re anxious for quick and frequent updates and easy access to information.

A way you can meet their expectations is by using ChatGPT and other chatbot recruiting tools to answer common candidate questions regarding the company culture, job roles, and the application process.

While ChatGPT is powerful and useful on its own, you can use it in conjunction with other tools to enhance its capabilities. Tools such as Drift, Intercom, or LivePerson can be used to handle the main interface, while you make use of ChatGPT for any queries that require more personalized responses.

For example: a prompt like “Answer common questions about our company culture, job roles, and application process” can help you anticipate common FAQ questions, make appropriate responses, and plan your chatbot automations accordingly.

4. Conducting initial interviews

Initial interviews are your chance as a recruiter to get to know the candidate as a person, and assess their suitability for a role beyond what you see on their resume.

Workable’s video interview question generator can give you a solid foundation for questions to ask in the initial interview, and another AI tool like ChatGPT can make those questions more clear, more specific to the role, or more personalized to the candidate – diving deeper into their story, their experience, and their ability to succeed in the role.

For example: After having the Workable interview question generator create questions for a sales manager position, you can give them to ChatGPT with a prompt like: “I’ve used Workable’s interview question generator to generate some basic interview questions for a sales manager position. Now, I’d like to add more depth. Can you generate a list of behavior-based interview questions that focus on leadership, team management, and sales strategy?”

5. Automating follow-up communications

There’s an old line of thinking in recruitment – “it’s all in the follow-up.”

Timely follow-ups and updates show candidates that you respect their time, but consistent communication is time-consuming for the average recruiter who is already juggling multiple candidates and priorities.

AI tools can be used to automate follow-up communications with candidates to schedule interviews, provide feedback, and offer updates on the status of their application – and personalize the emails to each candidate.

For example: a prompt like “Draft a follow-up email to a candidate after their interview, providing feedback on their performance and discussing the next steps in the process.” can be tweaked and templatized to streamline your communication workflow with job candidates.

6. Streamlining the onboarding process

The onboarding phase gives both the new hire and you a chance to start things off on the right foot and enable them to succeed.

It’s in both your and the candidate’s interests that it go smoothly, but creating individualized onboarding plans is too resource-intensive to do for each new hire.

Enter ChatGPT – which can be used to streamline your onboarding process and make it tailored to each new hire’s role, ensuring that they receive the right training and guidance as they begin their new role.

Try using a prompt like: “Create a personalized onboarding schedule for a new software engineer hire. The schedule should include an introduction to the team, training on our software development processes, and a meeting with their project manager.”

Tweak and individualize it to make a consistent onboarding process that sets up new hires for success from the day they start.

7. Enhancing training and development with simulations

Recruiters need to continually refine their skills to be good at what they do, just like any skilled work. Using ChatGPT in recruitment training processes can create realistic training simulations and role-playing exercises, so you can prepare for a variety of recruiting situations and respond to candidates accordingly.

You can use HR chatbots to play the part of a candidate and practice your interviewing skills, which in turn can lead to better hiring decisions.

For example: try a prompt like “Act as a candidate for a role-playing exercise for interview training. The role is a software engineer and the candidate has five years of experience in the field.”, test out different responses and see what the outcomes are.

Embracing ChatGPT for recruiting

The future of recruitment is here, and AI is its engine. These are just a few examples of how recruiters can use ChatGPT to be more effective at their jobs, but they are by no means the only ones. The potential use cases for ChatGPT and AI tools in recruitment are limited only by your own imagination.

Using ChatGPT for recruiting can streamline your workflows, make a better interview and hiring experience for candidates, and find and keep the best talent.

If you’re ready to take your recruitment process to the next level with AI, Workable is here to support your transition every step of the way. Get in touch with us to learn more about how we can help you make the most out of ChatGPT for your recruiting process.

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While it’s true that robots won’t be replacing hiring managers any time soon, the recruitment process can be time-consuming, expensive, and involves a lot of moving parts. Using artificial intelligence, such as AI applicant tracking software, to automate and streamline aspects of talent acquisition can reduce time-to-hire and increase confidence in hiring decisions by empowering HR professionals to use their time and talent more productively.

What is AI Applicant Tracking Software?

AI Applicant Tracking Software (ATS) is a type of recruitment software that uses artificial intelligence (AI) and machine learning technologies to optimize the recruitment and hiring process.

Many of the aspects of the talent acquisition process are important but time-intensive tasks that cater to the logistical steps of attracting and screening applicants. AI technology can orchestrate and manage many of these tasks efficiently and effectively, freeing up recruiters and HR professionals to oversee the entire workflow while focusing their own efforts on the areas that require human experience and insight.

What are the benefits of an AI Applicant Tracking System?

Hiring a new employee involves a ton of paperwork, scheduling, reviewing, record-keeping, and internal and external communication. Recruiters use AI-based applicant tracking systems to streamline the hiring process from start to finish, increasing productivity and reducing the likelihood of human error.

An AI applicant tracking system can function not only as a central repository of information, but also as an ever-ready human resources assistant capable of writing job descriptions, advertising job openings, reviewing job applications, performing assessments, scheduling interviews for qualified candidates and more.

Artificial intelligence also offers an unbiased source of information based on data, which can help ensure that candidates receive fair and consistent consideration. Combining the insights of AI tools with the instincts and experience of hiring managers adds scientific objectivity to the art of attracting and identifying the best candidates for a role.

AI-based ATS applications may include the following functionalities and features:

• Resume parsing: The ATS can automatically extract and parse relevant information from resumes and CVs submitted by job applicants. This makes it easier for recruiters to search and filter candidates based on specific skills, qualifications, experience, and other criteria.
• Job posting: The software enables the creation and distribution of job postings across various online platforms, job boards, and social media networks like LinkedIn. Some ATS tools can even suggest suitable job titles and keywords to optimize job descriptions to improve the visibility of job listings.
• Candidate sourcing: ATS can use AI algorithms to search for potential candidates from various sources, including online job portals, social media, and internal databases. This feature helps recruiters expand their talent pool and discover passive candidates.
• Automated screening: With AI-powered screening, the ATS can analyze and match candidates’ qualifications and experience with job requirements. This process helps in shortlisting candidates who are the best fit for the position, saving time and effort for recruiters.
• Candidate communication: ATS often includes features for automated communication with candidates, such as chatbot integrations that can be used to send acknowledgment emails, interview invitations, and rejection notifications. This ensures a smooth and professional candidate experience throughout the hiring process.
• Interview scheduling: Some ATS tools offer interview scheduling features that allow recruiters to set up interviews with candidates directly within the system, eliminating the need for back-and-forth communication.
• Performance analytics: ATS provides valuable insights and analytics on the recruitment process, such as time-to-fill, source of hire, candidate engagement, and more. This data helps HR teams make data-driven decisions to optimize their hiring strategies.
• Diversity and inclusion: Some advanced ATS platforms come with features that promote diversity and inclusion by removing bias from the hiring process. They can help identify potential biases in job descriptions and applicant data and support record-keeping for compliance purposes.

The implementation of AI in applicant tracking software significantly improves the efficiency of the recruitment process by automating repetitive tasks, enhancing candidate matching, and providing valuable data for better decision-making, allowing HR professionals to focus more on strategic aspects of talent acquisition and employee engagement.

How to choose an AI ATS

Choosing the right AI applicant tracking system is a critical decision — it directly impacts the effectiveness of the recruitment process and implementing a new workflow or system can be temporarily disruptive as stakeholders adjust to the change.

Here are some steps to help guide the selection process:

1. Define your requirements: Start by identifying the specific needs of your organization. Consider factors such as the size of your company, the number of job openings you typically have, the desired features and functionalities, budget constraints, and any specific integration requirements with existing HR or recruitment tools.
2. Research and compare options: Conduct thorough research to explore various AI ATS providers in the market. Look for vendors that have a good reputation, positive customer reviews, and a track record of successful implementations. Create a shortlist of ATS platforms that seem to align well with your requirements.
3. Check for AI capabilities: Verify that the ATS platforms you are considering have genuine AI capabilities. Some platforms might claim to be AI-powered but have limited functionality. Look for features like resume parsing, automated candidate screening, and intelligent candidate matching.
4. User-friendliness: A user-friendly interface is crucial for a smooth adoption of the ATS within your HR team. Request demos or trials of the shortlisted systems to evaluate their ease of use, navigation, and overall user experience.
5. Integration options: Consider the compatibility and integration options of the ATS with your existing HR software and tools. Seamless integration can streamline data sharing and improve overall HR processes.
6. Mobile accessibility: With the increasing use of mobile devices, ensure that the ATS offers a mobile-friendly interface for both recruiters and candidates. This allows for greater flexibility in managing applications on the go.
7. Candidate experience: Choose a system that offers a simple and intuitive application process, clear communication, and timely feedback to applicants.
8. Data security and compliance: Given the sensitive nature of candidate data, it’s essential to prioritize data security and compliance. Ensure that the ATS provider follows industry-standard security practices and complies with relevant data protection regulations.
9. Customer support and training: Look for a vendor that provides excellent customer support and training resources to help your HR team maximize the benefits of the ATS.
10. Scalability and future-proofing: Consider the scalability of the ATS, as your organization’s hiring needs may change over time. Additionally, inquire about the vendor’s plans for future updates and developments to ensure the system remains up-to-date with the latest technologies.
11. Obtain feedback from stakeholders: Involve key stakeholders, such as other HR team members, hiring managers, and IT personnel in the decision-making process. Get their input on the features they find most valuable and any concerns they may have.
12. Request references: Ask the ATS vendors for references from their existing clients. Reach out to these references to gather insights into their experiences with the system and the vendor’s customer support.

By following these steps and conducting a thorough evaluation, the Human Resources manager can make an informed decision and choose an AI applicant tracking system that best aligns with the organization’s needs and objectives.

Why use AI Applicant Tracking?

Using an AI applicant tracking system as part of the recruitment process saves time, reduces bias, facilitates collaboration, and analyzes helpful data, which makes life infinitely easier for hiring teams.

An often under-appreciated benefit is that an AI-based ATS also improves the candidate experience. AI tools make it easier to keep applicants informed throughout the process, and improved efficiency makes it clear that your organization values the time and effort of everyone involved. A positive candidate experience increases the talent pool for future roles, making it even more efficient to find and hire the right candidates for open positions in the future. As a result, incorporating AI tools into your hiring process is an investment in attracting and retaining top talent for years to come.

Overall, AI applicant tracking empowers HR professionals to be more efficient, make data-driven decisions, and improve the quality of the hiring process, ultimately leading to better hires and a stronger workforce. Artificial intelligence won’t be replacing the human resources department any time soon, but it can maximize the impact of their efforts.

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Fortunately, artificial intelligence (AI) can mitigate the difficulties of HR and finance collaboration. Thanks to technology, you can unite HR and finance strategies to drive better collaborations, processes, and solutions.

Common challenges of HR and finance collaborations

HR and finance are two departments that, historically, don’t see eye-to-eye.

HR recognizes employees as valuable business investments. Strategies focus on improving intangible assets like skills and experiences. Finance, on the other hand, tends to see employees as an expense and is laser-focused on the value of quantifiable assets.

These differing ideologies push the two teams into departmental silos, where their strategies, solutions, systems, and sources all exist in isolation. This can result in conflict, data inaccuracies, and a host of other issues when the two teams need to collaborate.

But collaborate they must.

Whether it’s to optimize your recruitment budget or streamline your payroll, HR and finance need to come together. Modern businesses are quickly learning that collaboration between the two enhances strategic decision-making across both departments.

But to achieve this harmony, you need AI.

How AI can facilitate better HR-finance collaboration

AI can improve the collaborative capabilities of HR and finance in three key ways.

1. Data integration and analysis

Siloed HR and finance data is vulnerable to data inconsistency, duplication, and human error. These risks slow down productivity, increase the risk of oversights, and cause teams to miss out on valuable opportunities.

An AI-powered enterprise resource planning (ERP) system captures and unifies HR and finance data in real-time alongside all your other department-specific information. With enhanced visibility, dispersed teams can access consistent data and analyze it to make collaborative and mutually-beneficial decisions.

So, for example, finance will always know when a new worker is added to the payroll or if an employee’s benefits change. This ensures the accuracy of financial budgeting and planning.

2. Automated reporting and forecasting

Your business needs to do more than keep up with the latest trends – it must anticipate them. Automated reporting and forecasting deliver swift access to data and analytics that can be used to power critical financial decisions.

Finance teams need employee data to make these decisions. This is where AI comes in. Automated reporting and forecasting tools use artificial intelligence to pull disparate data. This is then consolidated into customizable financial reports, which consist of easy-to-interpret visualizations, charts, etc.

Essentially, this enables finance teams to generate forecasts on demand. And, thanks to ongoing data streams, finance teams can quickly and confidently update forecasts in response to any changes.

3. Streamlined compliance and risk management

Both HR and finance handle sensitive company and employee data that needs to be protected under data protection laws and regulations. Inefficient data-sharing processes between HR and finance can result in costly repercussions.

Additionally, teams need to abide by labor laws and tax regulations, whether this be in the UK or state labor laws in the US. For businesses with employees in different cities or countries, this can get complicated very quickly.

With so many rules and regulations to adhere to, companies are turning to AI. The best cloud-based AI technologies have compliance built into their core and utilize a stack of security features that strengthen risk management.

AI applications in HR-finance collaboration

So, what does the application of AI in HR-finance collaboration look like? Here are a few examples.

1. Payroll and benefits management

HR needs to pay employees their wages and benefits accurately, on time, and in alignment with tax and employment laws. Without AI, it can be difficult to achieve the financial visibility and operational reliability needed to eliminate human error.

Any discrepancies that arise from human error, duplication, or the like can have serious consequences. This is why payroll software has become the standard for streamlining payroll and benefits management.

HR and payroll software automates payroll and benefits operations. As well as producing accurate, on-time payslips for employees, it also stores historical and current payroll data for quick analysis. This means HR and finance can make data-informed financial decisions regarding future salary and benefits offerings.

Plus, if you do business in the UK, you can even utilize natively HMRC-compliant payroll software to make sure compliance with the latest tax legislation.

2. Budgeting and financial planning

Employees are your most vital asset, which naturally means they’re one of your most costly expenses. It’s essential HR and finance teams work together to balance employee recruitment, salaries, and benefits with sustainable business profitability.

As recruitment costs climb, budgeting and financial planning need to be a joint effort right from day one of recruiting.

Luckily, recruitment software can optimize the hiring process to meet the goals of both HR and finance. This creates better candidate experiences, speeds up the hiring process, and secures the best talent in the right places. By doing so, HR can drive down cost-per-hire.

Salaries and benefits are also a common point of contention. Currently, benefits cost employers 32.9% of total employee compensation. HR teams who offer extravagant benefits like tuition reimbursement or cash bonuses without comprehensive financial budgeting and planning can land themselves in hot water.

But AI-powered accounting software can unite HR and finance. Thanks to features like detailed financial reporting and cash flow visualizations, the two can collaborate to make informed recruitment, salary, and benefits decisions.

3. Fraud detection and prevention

Every department needs to be able to defend against fraud attempts, but because HR and finance teams are privileged users with access to secure systems and sensitive data, insider threats are a bigger risk.

Not convinced it will happen to you? Well, 60% of businesses have experienced at least one insider attack in the last year according to a Gurucul study. Whether they occur due to maliciousness or negligence, insider threats are a pressing concern.

Fortunately, accounting, HR, and payroll systems all come with in-built security features that, when fortified by ERP, harden your fraud defense. This includes things like audit tracking, user access restrictions, and real-time alerts.

As well as deterring and quickly identifying malicious insider attacks, AI can prevent negligence from causing catastrophic data breaches that lead to external fraud.

Align your teams – and tech – for success

When HR and finance work together, they can achieve their aligned goal to maximize capital. But to do this effectively, they need the right resources.

AI-powered technologies unite disparate systems and facilitate cross-department communications. HR and finance can use them to automate and streamline data integration and analysis, ultimately powering better hiring, payroll, budgeting, and forecasting strategies.

Want to connect HR and finance? Use AI today.

The post Can AI help HR and finance collaborate more smoothly? appeared first on Recruiting Resources: How to Recruit and Hire Better.

Well, this month, we have some eye-opening data for you that blows some of that out of the water. Let’s get into it.

How we’re looking at data

We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.

For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.

As always, we look at the worldwide trends for three common SMB hiring metrics:

• Time to Fill (TTF)
• Total Job Openings (JO) 
• Candidates per Hire (CPH)

Let’s start analyzing!

Main highlights

The three main highlights for this month’s Hiring Pulse are:

• Job activity is back to high levels – especially for the largest and smallest companies
• Candidates Per Hire is at a whole new level
• The Time to Fill metric is the only one that’s relatively normal

1. Time to Fill

For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of June are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.

Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.

Got that? Good. Let’s have a look at the monthly TTF trend through to the end of June against the average of 2019, based on jobs that have been filled:

Last month, we pointed to relative stabilization in the Time to Fill trend especially compared with the steep drop seen in the first quarter of 2023.

Q2 tells a somewhat different story – April saw an uptick to 83.3 from March’s 81.9, with that trend dropping to 80.8 for May. And now, in June, it’s risen again to 84.

The question is: how anomalous is this? The answer: not unusual at all. Look at how 2021, 2022, and 2023 compare in the same chart:

With some minor outliers, these all follow a relatively similar trend – a steep drop-off from January to March followed by relative stabilization and a mild uptick to June.

The only thing that’s clearly different is that the Time to Fill trend is lower this year than in previous years. Jobs are getting filled quicker than before.

We’ve gone into a multitude of reasons and theories as to why – but for this month, let’s get to Job Openings and then, especially, to Candidates Per Hire which is where the real story is (yes, again).

2. Total Job Openings

Total job openings represent the total number of job openings activated across the entire Workable network.

As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of June.

Again, we see a bump in job activity, this being the second straight increase from the previous month from 7 new job postings per company across the board in May to 7.6 for June.

We’ve been at 7.6 before, in March, but what’s worth noting is that in the 18 months since January 2022, we’ve seen the average number of job postings per company go higher than 7 just four times, and three of those happened in the last four months.

There’s been a lot of talk (including in the Hiring Pulse reports) about recessions and AI impacting jobs. We’re surmising here that the impact is more in how jobs are changing rather than dwindling. New gaps and opportunities are being discovered, and new jobs are created as a result.

Now, look at the company sizes that are seeing the biggest jump in job activity. First, the big kids on the block (enterprise-level, 200+ full-time employees) are opening up more jobs over the last two months than the previous month before that – from 16.6 job postings per company in April to 17.5 in May, then 18.2 in June. If you look at 2022, you’ll see that job activity for that size bucket was higher although declining, while this year, it’s lower but rising.

Now, let’s look at the small kids on the block (>50 FTEs): they’re up to 5.8 jobs per company in June from 4.9 in May. That’s an increase of nearly one full new job posting per small business on average within a month.

We did a bit of math last month and let’s do it again: let’s say an average company in this size bucket has 30 full-time employees.

When you see the average of 4.9 new job postings for May, that’s more than 16% of that company’s entire workforce, or one in seven.

And 5.8 is 19.3% of that entire company’s workforce – nearly one in five.

Think about your own company, if you’re in a smaller one. Look at the people around you (or look at the faces on your laptop screen, if you’re working remotely). Imagine one in five of those people being new within the last month, or that you’re seeing one in five of those people leaving. That’s not an insignificant number for a small business. Hiring is very active in this bucket.

Now, let’s look at the candidates. Yes, we promised a good story, and you’re getting it now.

3. Candidates per Hire

Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.

Now that Let’s look at what’s going on here through June:

We didn’t think this was going to happen, but there it is – the Candidates Per Hire trend has just surged. The CPH trend is now at 176.7 for June 2023 (or 76.7% more candidates per hire than the average of 2019).

It’s absolutely at its highest point in, like, ever. To further demonstrate how high this is, let’s compare June’s CPH using 2020, 2021, and 2022 as benchmark averages:

In short: where candidates per hire for June 2023 is 76.7% higher than the average of 2019, it’s 50.2% higher than the 2020 average, 67.4% higher than the 2021 average, and 70.3% higher than the 2022 average. No question about it – June is very, very high no matter what year you compare it against.

We’ve talked aplenty about the many different reasons why, and we encourage you to go to previous Hiring Pulses to better understand this trend. Right here, we’re just going to recognize that if you’re getting slammed with candidates every time you open up a new job, you’re absolutely not alone.

What’s going on here?

Job openings are up, quite significantly, especially for small businesses. And the CPH trend is, of course, at previously unseen levels. Last month, we noted the drop in new job postings and the rise in CPH and wondered if the two were related.

In this case, we’re seeing a significant rise in both. The hiring landscape is just so very, very busy. There are just so many candidates for a single job – it’s like opening a leak in a dam and having the water just come rushing through.

When a lot of that activity is happening in smaller companies with fewer than 50 employees, you can imagine the stress on those hiring teams – smaller businesses don’t have the luxury of a full HR team that can dedicate themselves to the job.

An executive in a small business can often be the hiring manager for a job – and may even themselves be the recruiter, the background checker, the assessor, the evaluator, and more.

And doing this across the company for multiple jobs (remember, nearly one in five employees per small business as we stated above) while at the same time trying to run a business – it can be a lot to pack into a day. That’s where software (cough cough) can be pretty helpful.

See you next month!

Thoughts, comments, disagreements? Send them to content@workable.com, with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in May!

The Hiring Pulse: Methodology

Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.

To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.

For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.

And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.

The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.

The post Your Hiring Pulse report for July 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

There is no dilemma regarding whether to fire employees or hire new ones in the AI era. It simply requires a fresh perspective on the workforce of your company.

Workforce planning has become more important than ever, and both companies and employees must demonstrate flexibility in this regard.

Workable’s CHRO, Rob Long, says: “Right now people are still really trying to understand how this will impact the workforce. Some of the impacts and benefits are clear at a high level but much less certain when it comes to knowing exactly the extent to which it will impact certain functions or roles.”

“Right now people are still really trying to understand how this will impact the workforce. Some of the impacts and benefits are clear at a high level but much less certain when it comes to knowing exactly the extent to which it will impact certain functions or roles.”

By customizing your hiring strategy and identifying areas that humans can collaborate using AI tools, you can reach new heights in terms of performance and efficiency.

Let’s dive into the creation of a successful workforce planning strategy.

Human workers and AI can collaborate

There are several ways to describe the practice of collaboration between human workers and AI. It can be found online under names such as Combining Intelligence, Collaborative Intelligence, Integrated Intelligence, or Augmented Intelligence. All these terms are based on one specific notion: AI is not here to replace human workers, but to augment their capabilities.

Related: How AI can enhance human skills and collaboration at work

As an HR professional, you need to identify the areas where your human workers and AI can collaborate. This first requires a deep understanding of the tasks that your employees perform and the tasks that AI can perform better – and the difference between each.

According to a Harvard Business Review, humans require both cooperative and competitive skills to effectively work with AI systems. Cooperative skills include data-centric skills, AI literacy, and algorithmic communication, while competitive skills encompass emotional intelligence, holistic thinking, creativity, and critical thinking.

On the other hand, AI systems need to develop cooperative skills like natural language processing, explainability, adaptability, and context awareness, while their competitive advantages lie in analytical capacities, generativity, and performance at scale.

Organizations are advised to strike a balance between investing in human skills and technological capabilities to foster a symbiotic relationship between humans and AI.

Current employees will be affected by AI

It’s essential to understand how AI will affect your current employees before shaping a solid workforce planning strategy. Some of your employees may have concerns about their job security or their ability to adapt to new technology.

It’s your job as an HR professional to address these concerns and provide training and support to help your employees adapt to the changing workplace.

According to a survey by Qualtrics, employees see the potential positive impact of AI in the workplace primarily in terms of increased productivity. This includes automating repetitive tasks, allowing employees to focus on more complex work, and enabling faster and advanced data analysis.

The main concerns expressed by workers regarding AI’s impact are the loss of the human element in work (highlighted by 55% of respondents) and the potential erosion of critical thinking skills (selected by 52% of employees).

One of the greatest worries among employees is the possibility of AI replacing jobs altogether. About 68% of respondents believe that some jobs are at risk due to AI, and 23% feel that their own jobs are in jeopardy. There is also confusion and concern regarding policies related to AI in the workplace.

Nearly 60% of employees either state that their company lacks an AI policy or they are unaware of such a policy, leaving them uncertain about what is allowed or not in relation to AI usage.

Perhaps some jobs will be lost or incorporated into larger disciplines. To alleviate employees’ fears of AI taking their jobs, it is crucial to provide them with clear communication and transparency about the role of AI in the workplace.

This can involve comprehensive and ongoing training programs that focus on upskilling and reskilling employees to adapt to the changing work landscape and take advantage of the opportunities presented by AI.

Additionally, creating a culture that values and rewards human skills, such as critical thinking, creativity, emotional intelligence, and problem-solving, can reinforce the importance of these unique abilities alongside AI technologies.

New employees will be affected too

As an HR professional, you need to understand how potential new employees will be affected by AI. This means looking at the skills and knowledge required for jobs in the future and adjusting your hiring strategy accordingly.

An astonishing new survey conducted by Intelligent finds that 86% of hiring managers believe that having ChatGPT can be more valuable than a college degree for entry-level jobs.

Skills related to data analysis, AI literacy, and the ability to work effectively in collaboration with AI systems are highly sought after in the AI era.

Soft skills such as critical thinking, creativity, and problem-solving are more important now than ever. These are skills that are difficult to automate and are likely to become more valuable as AI becomes more prevalent in the workplace.

You can adjust your workforce planning strategy according to the latest developments and the real needs of your company, keeping in mind that AI is still a tool and not an enemy of humans.

Change your strategy for hiring people

According to a report by Accenture, 84% of business executives believe they need to use AI to achieve their growth objectives. You are probably among that group.

As an HR professional, you need to adapt your hiring strategy accordingly. You must begin searching for employees who possess the skills and knowledge required to work alongside AI. Additionally, if you are a team manager, you can offer guidance and assist your employees in upskilling and preparing to incorporate AI into their workdays.

To implement changes in your workforce planning strategy, you need to build a business case for change. This means using data to show the potential benefits of integrating AI into your workforce. You also need to consider the budget required to implement these changes.

However, there is no need to panic. Actually, we are presently living in a transitional period where we need to stay vigilant while also dedicating time to prepare for what the future holds.

Implementing new workforce planning should only happen when we have a clear understanding of our company’s needs and feel prepared to take action.

Hiring, firings, reorganizations and outsourcing

Once you have built a business case for change, you need to create a timeline for implementation. You can reassess the existing team structure, make new hires, or outsource based on this agreed timeline. It is essential to communicate it clearly to your employees and provide training and support to help them adapt to the changes.

If you know your team’s strengths and weaknesses, you can make an informed decision about using AI in the workplace.

Does it mean investing in new hires who are more familiar with new technologies? Does it mean providing reskilling opportunities to your existing employees?

Any decision must be made based on an organized plan and with careful consideration. In some cases, reorganization may be the best option for your company, while in others, outsourcing may be necessary due to time constraints. Consider AI tools as a way to enhance your employees’ abilities and continue investing in both new technologies and personnel.

There is only one word that accurately describes effective workforce planning for both employees and HR professionals, and that is adaptability.

“People are very aware that for many roles times are changing, so hiring people who are adaptable and comfortable with change is more important than ever.”

“People are very aware that for many roles times are changing, so hiring people who are adaptable and comfortable with change is more important than ever. The impact on productivity for certain roles will certainly be on people’s minds. Do they need to hire 10 or could they hire six now and get the same results?” Rob Long comments.

“But I don’t think many people have worked it out just yet. One clear change is the increase in roles related to creating AI technology, those are increasing rapidly and you can see companies investing more heavily here.”

The post Workforce planning strategy in the AI-driven economy appeared first on Recruiting Resources: How to Recruit and Hire Better.

Using conversational AI in recruiting can help us be better recruiters in everything from sourcing the best talent to drafting engaging job descriptions.

As with anything, integrating AI into recruiting workflows is not without its challenges – particularly in training and onboarding your recruiting team to use it.

Many professionals in the recruiting industry either misunderstand what ChatGPT does and how it can help them get more done and be better at their jobs. Some are afraid – not without reason – that incorporating AI tools in recruiting may remove the human element and dehumanize the recruiting process, or even replace their jobs.

It’s important to remember that ChatGPT is a tool – it’s not here to replace our jobs but to help us be better at them. It’s designed to augment and enhance human ingenuity and innovation, by freeing up time from routine and administrative tasks and freeing up more time for more strategic, higher-value decision-making.

We’ll help you clear up the misunderstanding around these myths and serve as a strategic guide on how to train recruiters to use ChatGPT in recruitment and navigate potential challenges that may arise in the process.

Training teams to use ChatGPT in recruitment

Imagine having your very own HR virtual assistant who never gets tired, does exactly what you ask of them, is available 24/7 a day year-round, is at all times eager and willing to help, and incorporates any feedback you give them as you go.

That’s the benefit of using ChatGPT in your recruiting process. However, as with all tools, there’s a right way and a wrong way to use it effectively. Incorporating ChatGPT into your recruiting workflows will take an initial period of training and onboarding as your team adjusts to the technology.

Introduction to ChatGPT

To best get your recruiting team up to speed, we recommend hosting interactive sessions that showcase ChatGPT’s potential use cases and abilities in action.

You can use either pre-recorded videos or a live demo, walking through the ChatGPT AI and showing your team example prompts and scenarios of using it for recruiting purposes like creating job descriptions and sourcing candidates. This will give your recruiting team ideas on how they can use it for themselves.

This initial step helps your team see for themselves how ChatGPT can save them time and save more time and energy on more important decision-making.

Remember, familiarity with ChatGPT doesn’t happen overnight. The goal at this stage is to get your recruiting team curious about ChatGPT and show them the possibilities of what it can do for them.

It’s best to learn on the job

A big part of the process of becoming proficient in ChatGPT and other AI tools is in hands-on experience – experimenting and trying different things to test its limits and get a sense of what it can and can’t do.

Organizing practical training sessions is a great way to facilitate this process. Your recruiters can interact directly with ChatGPT and practice doing things like crafting job descriptions, generating interview questions, playing around with different prompts, and seeing how the language model responds.

This will not only help your recruiters get more comfortable with ChatGPT, but it will also help them learn how they can adapt it to their needs. They’ll see through first-hand experience how it can help them in their day-to-day jobs.

Templates are all well and good, but the best results from ChatGPT often come as a result of you playing around with it and exploring what it can do. Your recruiters can benefit more from your training sessions and onboarding with practical examples.

Let’s look at a few examples of use cases of ChatGPT in recruitment:

1. Creating interview questions

From a pre-made job description, ChatGPT can help create relevant interview questions that you can tailor to fit the role and the company. It may surprise you with what it comes up with.

Be specific, relevant, and detailed in your prompts, and give ChatGPT as much context as is needed. Mention things such as the job title, several job requirements, and anything else specific to the role.

Example prompt: “Generate interview questions for a software developer with a focus on Python and machine learning.”

You can also ask it to tweak and modify its response to suit your needs, such as including more questions or fewer.

Example Prompt: “Let’s narrow it down to 10”

You can even have it generate practical exercises for the interview.

Example Prompt: “What’s an example practical exercise you might give to someone in this position? This can be an assignment that takes a few hours to complete and is due the following day.’

2. Writing Boolean search strings

Give ChatGPT the requirements and preferred experiments for a job, and it can help you create search strings to help source candidates.

Example prompt: “Create a Boolean search string for a nurse with pediatric experience in New York. The candidate must have 3 years relevant experience in a clinical setting and be based in New York.”

Remember that potential candidates may phrase their job experience differently, so play around with different variations.

3. Integrating ChatGPT into workflows

You can also show your recruiters how to build ChatGPT into their recruitment workflows alongside the other tools and software their familiar with. Show them ways they can use it, such as:

Integrating with your Applicant Tracking System (ATS): Asking ChatGPT to draft email communication with job candidates through their ATS. Example prompt: “Create a follow-up email for a candidate who interviewed for the software engineer position last week.”

Interview scheduling: If you use a digital calendar tool for scheduling, your team can ask ChatGPT to craft an appropriate interview invitation. Example prompt: “Write an invitation for a second-round interview for a sales representative role.”

Candidate feedback: After the interview, recruiters can use ChatGPT to deliver personalized feedback. Example prompt: “Draft a polite rejection email for a candidate who was not selected for the marketing executive position.”

These are just a few examples. ChatGPT is extremely flexible and versatile and can be used right alongside a variety of tools like ATS or CRM systems.

4. Running mock scenarios

Hosting practice sessions and exercises with ChatGPT is a great way to help your recruiting team build confidence with ChatGPT, to make sure they understand how it works and how they can use it in their job. Here are some scenarios you can simulate:

Candidate screening: Give your recruiters a fictional resume, and have them generate potential interview questions using ChatGPT based on the resume. Example prompt: “Generate interview questions for a candidate applying for a project management role with experience in agile methodologies.”

Candidate sourcing scenario: Have your recruiting team create a Boolean search string given a hypothetical job role and a list of required qualifications and skills. Example prompt: “Create a Boolean search string for a data analyst role requiring Python, SQL, and knowledge of machine learning techniques.”

Candidate outreach scenario: Ask your recruiters to practice reaching out to a potential candidate, using ChatGPT’s help. For example, a prompt they might use is: “Draft a candidate outreach email for a senior graphic designer position”

These are just a few examples. The goal is to provide realistic advice and help them understand the range of tasks ChatGPT can help with.

Provide ongoing learning and support

Advancements in AI technology happen parabolically. Hardly a week goes by when we don’t hear about how ChatGPT is poised to revolutionize a given industry or make another one obsolete. It’s still new, exciting, and scary territory, and people are still unsure about whether it’s a good or bad thing.

Staying ahead of the curve as AI continues to develop means providing your team with ongoing support, such as:

Provide regular training sessions: Organize regular training sessions as ChatGPT and the other AI tools you use to build and update new features or improvements. This way, recruiters are always knowledgeable about the latest developments and can use the tool to its full potential.

Create a resource hub: Consider creating a repository of knowledge and resources where your team can access ChatGPT prompt templates, guides, videos, and example use cases. This can be a collaborative Google doc that your team adds to over time.

Establish a support team: Consider designating an established team or person to provide real-time assistance to any recruiters who encounter difficulties or have questions regarding ChatGPT – including in recruitment work. This can be part of your existing IT or HR team if you have a small business.

Provide feedback channels: Have a way for recruiters to offer feedback or report any issues or problems with ChatGPT so that problems can be resolved quickly. This can also provide useful insights for future training

Ensure a smooth transition

Just because you onboard your team with ChatGPT doesn’t mean that all your team members will be on board, so to speak.
Addressing concerns proactively will help the doubters and the fearful among your recruiting team that AI is not here to replace their jobs, but to help them focus on more strategic tasks that require a human touch.

Here are some ways you can smooth out any bumps in the road and keep resistance to ChatGPT to a minimum:

1. Be clear on what and why

It all starts with open, honest transparency. Let your team know why you’re advocating for ChatGPT in recruitment, the benefits it has, and how it can help them get more done in less time. Emphasize at every stage that it’s a tool meant to assist them, not replace them. This will help manage expectations and alleviate concerns.

2. Integrate gradually

Introduce ChatGPT gradually into your recruitment workflows. Identify areas in your existing processes where they can be used. Find opportunities for integration, particularly any repetitive or monotonous tasks that require significant human effort. Start small at first with simple tasks, like boolean search strings.

As your team dips its toes in the water, scale its usage internally. This allows team members to adapt to the technology at their own pace and reduces potential overwhelm.

3. Showcase and celebrate successes

Provide a positive narrative and build associations within your recruiting team, by sharing the success stories about how ChatGPT has benefited certain team members.

This will help foster positive perception and wider acceptance.

4. Ensure a continuous learning experience

Foster a culture of collaborative learning and adaptation. As new features in ChatGPT and other AI tools roll out, your team should be prepared to adapt and evolve with them. Update your team regularly with new features and improvements to ChatGPT. Celebrate the team members who use it effectively, and encourage them to showcase what they learn.

Create the future by embracing ChatGPT for HR

Leveraging AI tools like ChatGPT is a strategic step towards transforming the way your recruiting team does things, for the better.
When you have ChatGPT automate your routine tasks, it allows your recruiters to focus on what matters – people. That’s what makes it such an exciting time to be a recruiter in the age of AI.

Embrace this change and harness the power of AI for more efficient, more data-driven, and more human-centric recruitment. The future is not to be feared, but to be created. We invite you to explore what ChatGPT can do for your recruiting and HR teams in our vast library of tutorials.

The post ChatGPT in recruitment: how to teach your teams to use it appeared first on Recruiting Resources: How to Recruit and Hire Better.

Exit interviews play a crucial role in gaining valuable insights into employee turnover, helping organizations improve their retention strategies and foster a positive workplace culture.

However, traditional methods of analyzing exit interview data can be time-consuming, subjective, and limited in scope.

Let’s explore how ChatGPT, an AI-powered language model, can support your exit interview efforts by creating engaging reports for your manager.

Why to use ChatGPT for your exit interview reports?

Using ChatGPT for creating reports based on exit interviews data can greatly benefit HR professionals.

ChatGPT’s capabilities in data analysis, natural language understanding, and summarization allow it to efficiently process and interpret the data, saving valuable time and effort.

By leveraging ChatGPT’s abilities to identify patterns, trends, and key insights, HR professionals can gain a deeper understanding of employee sentiments, reasons for departure, and areas for improvement.

The generated reports can be concise, yet comprehensive, providing a valuable overview of the exit interviews data.

This, in turn, empowers HR professionals to make data-driven decisions, develop targeted retention strategies, and drive improvements in employee satisfaction and engagement.

Ultimately, ChatGPT’s support in report creation based on exit interviews data enhances the HR professional’s ability to extract meaningful insights and take informed actions to strengthen the organization’s workforce.

Related: Exit interview questions and answers

Analyzing Exit Interview Data

Conducting numerous exit interviews can be daunting when it comes to analyzing them. Fortunately, it is easier than ever to write down your notes and transform them into effective reports.

There are many tools available to help you with this. Microsoft Office and Google Docs, for example, can assist you in taking notes and providing reports to your managers. However, you need to be proficient with these software programs to take full advantage of all the available options they offer.

In addition, you can use online tools easier to manage like SurveyMonkey or Google Forms to do your work in less time.

If you are looking for something quick and almost effortless, you can use AI tools to extract your outcomes and take action immediately.

Workable’s new AI features, for example, can help you by suggesting questions and taking automated notes during exit interviews. All you need to do is fit them to your own tone, and use them to create efficient results.

Using ChatGPT for exit interviews analysis

Here, we are going to use ChatGPT to show you how easy you can build a report based on the feedback from exit interviews.

First gather all the answers (notes or transcripts) given to the same question for all participants in a Google doc or your preferred desktop app. Go to ChatGPT and use this prompt before adding your text:

The below transcripts contain answers to` [interview question]. Could you please create a bullet list of similarities and differences for me?

Check the answer and copy the information contained as they are important for your report.

If you want to delve deeper, you can incorporate details about their salary, role, and department, even without cleaning properly your data, and request ChatGPT to generate a table for you containing concise responses to all your inquiries.

For example you can use this prompt:

Can you build a table for me based on the given data containing employee names, their department, their role, their wage, their years at the company, the reason of leave (between 1-6 words), overall experience (1-6 words) Training satisfaction (yes or no), what satisfied them the most (1-6 words), treatment by supervisor (1-6 words), and recognition of work (1-6 words)?

And voilà…

You can adjust your query depending on your company needs.

Building reports from exit interviews

Now you have all the critical information for your record. If your manager wants to build a report and email them, you can continue using ChatGPT:

Could you please build a report for my HR manager summarizing the reasons for leave and including points for improvement based on the above data? My name is Anna Morrison, I’m an HR assistant, my company name is System Force, and my HR manager is named Nick Smith.

Based on our sample data we received this answer.

Subject: Exit Interview Analysis
System Force, HR Department
Date: June 21

Dear Nick Smith,

I am writing to provide you with an analysis of employee exit interview based on the reasons for leave obtained from exit interviews. This report aims to highlight the primary reasons employees have chosen to leave the company and suggest points of improvement to enhance employee retention.

Reasons for Leave:

• Personal relocation: One employee mentioned leaving due to personal relocation. While such circumstances may be beyond the company’s control, it is essential to explore options for supporting employees during significant life changes to retain valuable talent.
• Career growth opportunities: Two employees cited the lack of career growth as a reason for leaving. It is crucial to provide clear career paths, offer regular performance evaluations, and identify opportunities for advancement within the organization. Promoting internal mobility and professional development programs can help address these concerns.
• New job opportunity: One employee mentioned leaving for a new job opportunity. Conducting stay interviews with employees and actively identifying their career aspirations can help identify and address any potential flight risks proactively.
• Work-life balance: One employee cited the need for better work-life balance. Promoting and fostering a healthy work-life balance, such as implementing flexible work arrangements or offering employee wellness programs, can contribute to improved job satisfaction and retention.
• Unhealthy work environment: One employee cited an unhealthy work environment as the reason for leaving. It is crucial to assess and address any issues related to workplace culture, communication, and employee well-being to ensure a positive and inclusive work environment for all employees.

Points of Improvement:

Based on the analysis, here are some suggested points of improvement to enhance employee retention:

• Enhance career development opportunities: Create clear career paths, provide regular feedback and performance evaluations, and offer training and development programs to support employees’ professional growth.
• Promote work-life balance: Implement policies and programs that support work-life balance, such as flexible work arrangements, wellness initiatives, and promoting a healthy work environment.
• Foster a positive work culture: Encourage open communication, collaboration, and recognition to create a supportive and inclusive work environment.
• Conduct stay interviews: Regularly engage with employees to understand their aspirations, concerns, and needs, and address any potential flight risks proactively.
• Strengthen talent retention strategies: Implement programs and initiatives to recognize and reward employees’ contributions, provide competitive compensation and benefits, and foster a positive employee experience.

By addressing these areas of improvement, we can enhance employee satisfaction, engagement, and ultimately improve employee retention within the organization.

Please let me know if you require any further information or assistance in implementing these suggestions.

Thank you for your attention to this matter.

Sincerely,

Anna Morisson
HR Assistant

You can edit this report based on your experience, knowledge, and the needs of your organization.

Briefly, we saw that ChatGPT can assist you in writing a comprehensive report for your manager by instantly providing the most useful data such as participation rates, main reasons for exiting, areas of improvement, and ideas for conducting comparative research, if necessary, to compare your employee exit data with industry benchmarks.

Additionally, ChatGPT can help you continue your analysis by providing information on employee retention rates, engagement levels, and turnover costs based on the data you will share.

In short, save time creating a detailed and valuable exit interview report using ChatGPT, focus on how you and your organization can act to boost retention and reduce staff turnover. Take the feedback seriously and start working on a better future for your company and its culture.

The post Create exit interview reports in minutes using ChatGPT appeared first on Recruiting Resources: How to Recruit and Hire Better.

ChatGPT offers multiple ways in which it can offer assistance, such as aiding in the exploration of data, making predictions and suggestions, and conducting sentiment analysis.

In this article, we will help you discover the possibilities of taking away solid tips for improving your company and increasing employee retention.

Benefits of using ChatGPT for exit interviews

ChatGPT offers several benefits to HR professionals conducting exit interviews and analyzing the collected data. Here are the key advantages of using ChatGPT for exit interviews analysis:

1. Quick access to information

ChatGPT provides instant access to relevant HR resources, including guidelines, best practices, and documentation.

HR professionals can quickly find answers to their questions, explanations of concepts, and receive guidance on conducting effective exit interviews.

2. On-demand support

HR professionals can rely on ChatGPT as an on-demand support system. They can seek clarification, guidance, and tips on various HR topics related to exit interviews.

ChatGPT offers immediate responses, helping professionals overcome challenges and gain valuable insights without depending on others for assistance.

3. Streamlined data analysis

ChatGPT assists HR professionals in efficiently analyzing exit interview data. It provides recommendations on data preprocessing techniques, handling missing values, and addressing data quality issues specific to exit interview data.

This streamlines the analysis process and ensures accurate and reliable insights.

4. Improved decision-making

ChatGPT offers guidance on interpreting exit interview data and deriving meaningful insights. HR professionals can make data-driven decisions based on the analysis results, leading to improvements in retention strategies and employee satisfaction.

With data-driven insights at your fingertips, you can make informed choices, develop targeted strategies, and enhance employee satisfaction and retention.

The flexibility and continuous learning capabilities of ChatGPT ensure that your analysis remains relevant and adaptable to evolving workforce dynamics.

Now, let’s learn how to use ChatGPT to gain insights for your offboarding employees.

ChatGPT prompts for exit interview outcomes

Depending on the data that you wish to share with ChatGPT, you can use relevant prompts to assist you in achieving your desired outcomes. We recommend importing data such as names, salaries, department, exit interview notes containing reasons for leaving, and satisfaction levels regarding various aspects such as rapport with managers, benefits, learning and development processes, and communication between departments. Additionally, you can ask for areas of improvement and gather useful feedback for your ChatGPT data analysis.

The more detailed your dataset is, the more detailed your outcome will be.

Let’s see a few prompts you can easily use below:

Prompt: “What are the common reasons cited by employees during exit interviews?”

This prompt can help HR professionals analyze the recurring themes and factors leading to employee turnover within the organization.

Prompt: “Identify any patterns or trends in the exit interview data.”

This prompt encourages ChatGPT to analyze the data and provide insights into any noticeable patterns or trends regarding employee departures.

Prompt: “Highlight the most frequently mentioned areas for improvement based on exit interviews.”

By using this prompt, HR professionals can identify the key areas that need attention and improvement within the organization, as expressed by departing employees.

Prompt: “Provide suggestions for enhancing employee satisfaction and reducing turnover based on exit interview feedback.”

This prompt prompts ChatGPT to generate actionable recommendations based on the feedback gathered during exit interviews, helping HR professionals address employee concerns and increase job satisfaction.

Prompt: “Analyze the sentiments expressed in exit interview comments.”

By analyzing the sentiments expressed by departing employees, HR professionals can gain an understanding of the overall sentiment and emotional experiences associated with leaving the organization.

Prompt: “Compare the exit interview feedback across different departments or teams.”

This prompt enables HR professionals to compare and contrast the exit interview feedback received from different departments or teams, helping identify any specific challenges or areas of improvement within each unit.

Prompt: “Identify any recurring issues or concerns raised by employees leaving for competitor organizations.”

By using this prompt, HR professionals can gain insights into the specific factors that may be attracting employees to competitor organizations, enabling them to take appropriate actions to retain talent.

Prompt: “Provide an analysis of the most commonly mentioned career development opportunities in exit interviews.”

This prompt prompts ChatGPT to analyze the feedback related to career development and growth opportunities mentioned by departing employees, helping HR professionals understand how to enhance these offerings.

Taking action

We used ChatGPT based on random data to show you how it works.

We generated random data of:

• Names
• Salaries
• Departments
• Years at the company
• Reason for leaving
• Overall experience
• Training satisfaction
• Manager communication
• Recognition of work

Now let’s see the discussion and the feedback we received.

Prompt: “What is the main reason for leaving?”

ChatGPT replied:

Based on the provided exit interview data, it appears that the main reasons for employees exiting the company can be categorized into several key factors:

• Lack of career growth opportunities: Employees like Michel, the Financial Analyst, expressed feeling stagnant in their positions and not seeing clear paths for advancement within the company. Limited opportunities for growth can contribute to employee dissatisfaction and prompt them to seek new opportunities elsewhere.
• Workload and work-life balance: Sarah, the Marketing Manager, mentioned difficulties in maintaining work-life balance due to high workloads. This factor can lead to burnout and negatively impact employee well-being, prompting them to leave in search of a better balance.
• Poor company culture and values alignment: Jasmine, the Human Resources Generalist, highlighted a misalignment between the company’s culture and her personal values and goals. When employees feel that their values are not respected or aligned with the organization’s, it can lead to disengagement and a desire to find a better cultural fit elsewhere.
• Communication and coordination challenges: Emily, the Customer Support Specialist, mentioned poor communication between teams, causing delays and confusion. Ineffective communication can hinder productivity and collaboration, leading to frustration and ultimately contributing to an employee’s decision to leave.
• Lack of recognition and appreciation: Mark, the Sales Representative, expressed a lack of recognition for his contributions, despite meeting and exceeding sales targets. When employees feel undervalued and unappreciated, it can impact their motivation and job satisfaction, making them more likely to seek opportunities where their efforts are recognized.

Prompt: “What changes can we make to prevent resignations and increase employee retention?”

ChatGPT replied:

To address the identified reasons for employee exits and prevent them from occurring, organizations can consider implementing the following changes:

• Provide clear career development paths: Create transparent career advancement opportunities and development plans for employees. This can include training programs, mentorship initiatives, and regular performance reviews to help employees see a clear path for growth within the organization.
• Promote work-life balance: Encourage a healthy work-life balance by implementing policies that support flexible work arrangements, offering employee assistance programs, and promoting time management and stress reduction techniques. Prioritize employee well-being to prevent burnout and increase job satisfaction.
• Cultivate a positive company culture: Develop and communicate a strong company culture that aligns with the organization’s values and promotes inclusivity, respect, and open communication. Regularly assess the culture and make necessary changes to ensure it remains supportive and engaging for employees.
• Improve communication and coordination: Enhance interdepartmental communication channels, promote collaboration tools, and establish clear lines of communication to minimize delays and confusion. Foster a culture of effective communication and encourage teamwork to improve coordination across teams.
• Recognize and appreciate employee contributions: Implement a robust recognition and rewards program that acknowledges and appreciates employee achievements. This can include performance-based incentives, public recognition, and opportunities for career advancement tied to exceptional performance.
• Enhance leadership and management practices: Train managers and leaders to adopt a supportive and empowering leadership style. Encourage transparent decision-making, solicit employee feedback, and involve employees in decision-making processes when appropriate. Create an environment where employees feel valued and heard.
• Foster diversity and inclusion: Implement diversity and inclusion initiatives that promote a welcoming and inclusive work environment. Train employees on unconscious bias, address any issues related to discrimination or microaggressions, and establish diverse hiring practices to ensure a diverse and inclusive workforce.
• Invest in employee training and development: Provide comprehensive training programs and professional development opportunities to enhance employees’ skills and knowledge. Support employees’ career aspirations by offering resources for acquiring new skills, attending conferences, and pursuing certifications.

Based on the data you have shared with ChatGPT, you can proceed with more in-depth questions. For instance, if you take notes on the benefits or communication flow within the organization, you can request GPT to provide you with more specific and focused information.

In a more complex scenario you may want to create a dataset with details such as employee participation in the exit interview process or the sentiment of leave which will affect your employer branding. You shall repeat the above procedure and modify your questions.

As you can easily conclude, ChatGPT can be an insightful assistant for your HR efforts in terms of retention and organizational improvements.

As an expert, you must confirm that the chatbot’s answers are aligned with the given data and your questions before preparing a comprehensive report for your manager.

Feel free to add your data and start automating this procedure in order to save time for implementation.

The post Exit interviews: ChatGPT prompts for valuable insights appeared first on Recruiting Resources: How to Recruit and Hire Better.

First things first, let us take a moment to elaborate on what employer branding actually is. Employer branding is all about how people see a company’s values and work environment. It includes everything the company does, whether on purpose or not, to promote its unique identity as an employer to current and potential employees.

Employer branding has become a critical factor in attracting and retaining top talent. According to a survey conducted by LinkedIn, 77% of candidates say that the reputation of a company is important while 80% of HR leaders think that an employer brand has an impact on their recruiting.

However, the evolving nature of work and the increasing expectations of candidates and employees pose unique challenges to effective branding.

This is where the power of AI tools in HR comes into play.

By harnessing the capabilities of generative AI algorithms, you can transform your company’s branding efforts and create a lasting impact to your employees and to the world.

But how does it happen? Let’s go further to understand better the value that AI automations put in your company.

AI in the HR environment

As an HR professional, you already know the magical benefits that AI can offer. AI tools have shortened the time to ramp, alleviating concerns about the screening process, candidate communication, and tracking. This allows you to focus on more creative tasks while leaving automation to handle the mundane tasks.

At the same time, AI can push forward your efforts for better company branding.

Generative AI can be leveraged to enhance various aspects of branding, from employer branding to internal communication. By tapping into the potential of generative AI, you can elevate your company’s brand identity and establish a compelling narrative that resonates with your audience.

Therefore, the result is that effective branding has a positive impact on potential candidates, as well as on the external world and the power of word-of-mouth. Does this sound like marketing to you?

Marketing obviously has a huge payoff – for example, Avatar: The Way of Water was able to make until now $2.320 billion at the box office on an estimated $200M marketing budget. Of course, you don’t have that much money in your recruitment budget, which means you will need to utilize tools like AI to boost your brand.

Allow us to elaborate.

How AI can be used to boost employer branding

Good branding reflects positively on others. The image a company projects to the public can be reshaped using AI tools. A company that uses automation and keeps up with the latest technological developments to handle repetitive processes, while leaving room to utilize people in more creative processes, appears larger in the eyes of others. This creates a positive perception of your business in the public opinion.

The Society for Human Resource Management (SHRM) reports that 88% of companies worldwide were already using AI in their HR practices, even before the COVID-19 pandemic. This technology is particularly helpful for talent recruitment and selection, and can also enhance employer branding to attract new talent.

Are you still wondering how these concepts could be applied to your company? Let’s take a look at an example.

AI cheat sheet for better employer branding

Imagine a three-year-old company in a crowded startup market which had sought to revamp its branding and establish a strong reputation after the latest developments in AI. They begin experimenting with these tools to transform their approach.

By leveraging generative AI algorithms, this company has developed personalized and captivating employer branding messages. These messages communicate the organization’s mission, vision, and values, express a commitment to employee growth and development, highlight the culture and work environment, share success stories and employee testimonials, and indicate the company’s impact more clearly in the community.

The company utilized AI to create engaging and informative internal communications that fostered a sense of unity among employees.

At the same time, the organization utilized generative AI to create personalized job postings that would catch the attention of potential candidates. By analyzing large amounts of data, generative AI algorithms produced compelling narratives that would resonate with their intended talent pools. This approach enabled them to customize their employer branding messages for various demographics and increased the chances of attracting suitable candidates.

Moreover, the HR department introduced a new referral system to attract more talent with the help of satisfied employees within the company.

As a result, this company witnessed a surge in qualified applicants, an enhanced candidate experience, and improved employee engagement.

Their innovative use of AI tools propelled their brand reputation, positioning them as a forward-thinking and desirable employer in the industry.

Adopting such tools can help your business in two ways. Firstly, it positions your company as one that people want to work for. Secondly, it establishes a reputation as a company with the very best people working for it.

Intensify candidate attraction with AI

In today’s candidate-driven market, providing an exceptional candidate experience is paramount. Research shows that candidates who have a positive experience are more likely to accept job offers, refer others, and even become customers.

More specifically, in a recent survey, 49% of job seekers confirmed that they have rejected a job offer due to an unfavorable experience with the prospective employer. The way that HR professionals handle communications between candidates can boost or harm your brand reputation.

AI tools can transform the whole process of hiring by paying attention to creating a good rapport with those who apply for a vacancy in your organization. The outcome of achieving that can be very beneficial to your company.

Jacob Rios, Co-Founder and CEO of JobSage said: “You don’t have to spend much time on the internet to learn that most online reviews tend to skew negative, so it’s great to see such a high percentage of candidates also sharing their positive experiences.”

“You don’t have to spend much time on the internet to learn that most online reviews tend to skew negative, so it’s great to see such a high percentage of candidates also sharing their positive experiences.”

“It is so helpful and empowering to future candidates,” Jacob continues. “We’ve spoken to many jobseekers in our line of work and most simply want to learn the truth, both the good and the bad.”

Through generative AI-powered chatbots and virtual assistants, candidates can receive personalized responses to their inquiries, obtain relevant information about the company and position, and even receive guidance throughout the application process.

This level of personalized engagement not only enhances the candidate experience but also showcases your company’s commitment to providing a seamless and tailored journey.

AI algorithms can analyze your company’s values, mission, and culture to generate internal communications that resonate with employees. From employee newsletters to internal social media posts, generative AI can help you craft compelling content that captures attention and drives engagement.

The 30-60-90 day onboarding framework and AI copilot by Workable are all examples of how AI tools can increase brand reputation and retention rates.

Employer branding equals reputation

As an HR expert, you should consider brand reputation and employer branding as one. Their parameters overlap, and together they create a whole that affects both the internal and external environment of the company. AI tools can assist you throughout this process, but human intervention will always be decisive when it comes to branding.

A business is driven to progress through its people. Therefore, welcome your people, help them become a part of your culture, provide feedback to those who were declined, and keep your eyes on the positive outcome.

The post Boost your employer branding & retention using AI appeared first on Recruiting Resources: How to Recruit and Hire Better.

We then talked aplenty about AI affecting the job landscape and how there didn’t seem to be as much talk about a recession as there was at the start of this year (which feels like a long, long time ago now).

Now, we’re nearly at the midway mark of 2023, and we’re going to explore our SMB hiring data and see if we can pull up some fresh insights.

Let’s get to work!

How we’re looking at data

We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.

For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.

As always, we look at the worldwide trends for three common SMB hiring metrics:

• Time to Fill (TTF)
• Total Job Openings (JO) 
• Candidates per Hire (CPH)

Let’s start analyzing!

Main highlights

The three main highlights for this month’s Hiring Pulse are:

• Time to Fill is showing signs of stabilization, but remains at its lowest point in our dataset history
• Job activity is particularly robust for small businesses with fewer than 50 full-time employees
• Candidates Per Hire has come down significantly from last month’s surge – but remains at a high point

1. Time to Fill

For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of May are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.

Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.

Got that? Good. Let’s have a look at the monthly TTF trend through to the end of May against the average of 2019, based on jobs that have been filled:

The second quarter of 2023 continues to see relative stabilization in the Time to Fill trend compared with the first quarter, with May’s 80.8 just a small drop from April’s 83.1, which comes on the heels of March’s 81.8.

What’s really worth noting here is how low the TTF trend is in general. These past three months have seen what’s ultimately the fastest Time to Fill trend in our dataset dating back to 2019. What does this ultimately signify? It can be any of the following:

1. A glut of candidates makes it easier to find the right hire in short order
2. A shortage of candidates means hiring teams work faster to land the right hire before the competition snatches them up
3. Hiring teams are getting faster at hiring because layoffs have reduced the number of touchpoints to a hire
4. Hiring teams are becoming more efficient at hiring because they’ve digitally transformed their hiring process (hint, hint Workable and AI)
5. Hiring teams are becoming more efficient at hiring in general

There are many other potential explanations, but the above is worth thinking about.

2. Total Job Openings

Total job openings represent the total number of job openings activated across the entire Workable network.

As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of May.

Once again, job activity sees a little bump: from 6.6 new job postings per company on average in April to a flat 7 in May. It’s not a lot to write home about, especially since historically a jump from April to May is relatively normal (with 2022 being an exception).

What’s more interesting than month-over-month change here is the relative busy-ness of job activity throughout 2023 compared with previous years. It’s busier this year for SMBs (<200 FTEs), but for enterprise-level companies with more than 200 FTEs, job activity is actually slower now than it was at this time last year.

We surmise it’s because larger companies tend to be slower in turnaround and response. Remember all that talk about a worldwide recession at the start of the year, followed by large-scale layoffs? And now, we see slower job posting activity as we approach the end of Q2 compared with the same time last year. That’s all part of the overall business plan.

Another way to look at it is that employees at larger companies may have greater job security in those companies. That, coupled with layoffs, will mean lower employee turnover – and therefore, fewer job postings.

Meanwhile, those smaller, nimbler companies that are more susceptible to turbulent rises and falls in the bottom line will also see greater turnover – we’re seeing that especially in the 1-50 FTE bucket where March’s 5.5 job postings per company, April’s 4.6, and May’s 4.9 are significantly higher than last year at this time (3.5, 3.3, and 3.3 respectively).

Let’s do a little bit of math to put that in perspective – let’s say the average company in the 1-50 FTE bucket has 30 full-time employees. An average of 4.9 job postings is 16% of that entire company’s workforce right there. That’s compared with last year’s 3.3 job postings being 11% of a company’s workforce.

That’s the difference between a turnover of one in seven employees this past May and one in nine employees in May 2022.

Pretty significant.

Now, let’s look at the candidate population for those jobs.

3. Candidates per Hire

Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.

Now that Let’s look at what’s going on here through May:

After many months – more than a year, even – of a Candidates Per Hire trend growing faster than a bamboo tree, we’re finally seeing that number take a plunge from one month to the next. Whether that’s due to April being so high that a drop-off was inevitable or whether that’s due to an actual depletion of the candidate pool, that’s for you to decide.

One thing we’re viscerally cognizant of, however, is that this drop in May could be related to the higher job postings in the previous chart – meaning, when there’s more job postings out there, naturally, candidates will get snatched up as well.

Another scenario worth thinking about: there are three major scenarios in which one might be looking for a job: first, they’re entering the job market because they’re entry-level, coming out of school, moved to a new location, or something similar.

Second, they’re transitioning jobs; simply put, they’re still employed but they’re looking for other jobs out there because it’s time for a change. Third, they’ve lost their job and they’re actively looking for a new one.

So, the increase in candidates per hire in general isn’t simply about a growing candidate pool. It’s also the result of those mass layoffs across the board, leading to candidates more aggressively and actively looking for a new job so they aren’t unemployed for a long period of time. Rather than selectively applying for job opportunities out there, they’re taking the spray-and-pray approach until someone hires them.

This, of course, will drive the CPH up – and it can also be challenging for employers because they need to suss out the real motive of a candidate in applying for their open role. Be careful thinking like this, however. Don’t jump to conclusions. A smartly built evaluation process will identify the real stars for your job.

What’s going on here?

Notice we didn’t touch on AI much at all this time around? While that’s still a hot topic, let’s not get too deep into this month since we’ve covered it so comprehensively in much of our other content. Plus, it remains a very nascent environment.

OK, fine. Let’s talk about AI.

Meanwhile, OpenAI, Nvidia, Microsoft, Google, Amazon, Apple, and the rest of them are investing heavily in AI and machine learning. Out of the 38 new unicorns (startups that break the $1B company value barrier), eight of them are in AI technologies.

If you’re in AI, that’s great, but if you’re in anything else, it’s a tough ocean to navigate. That same report states that overall funding of startups has dropped 44% from May 2022 to May 2023.

We’ll just keep a finger on that AI pulse for the forthcoming months, particularly on how typical skill sets will change going forward. For example, ChatGPT is considered even more valuable than a post-secondary degree by 86% of hiring managers according to an Intellgent.com survey.

And for entry-level candidates, a full 98% of hiring managers would like to see ChatGPT experience for positions where the AI tool is applicable.

These are interesting times. Catch up next month!

Thoughts, comments, disagreements? Send them to content@workable.com, with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in May!

The Hiring Pulse: Methodology

Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.

To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.

For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.

And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.

The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.

The post Your Hiring Pulse report for June 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

However, we can get a sense of where job markets are heading by considering how algorithms are being wielded to reshape the workplace.

Tech-supported remoteness

One of the most striking changes is the shift towards remote work. This was inspired initially by the COVID-19 pandemic, and the jury is still out about the extent to which the migration to home offices will become permanent.

But automation technologies and AI have played a key role in enabling individuals to work remotely, a trend that will likely continue.

The growing use of telecommunications, the internet, Internet of Things (IoT) sensing, and cloud services provide a robust infrastructure for heavily decentralized yet effectively coordinated human activity.

As a result, even the diversity of languages becomes less of a barrier to working together through automated language translation.

Technologies like these support almost all facets of remote work. For example:

• IoT sensors provide remote monitoring visibility
• Cloud apps provide remote access to data and functionality
• Robots offer remote control of physical systems
• Employee performance-monitoring systems ensure remote workers are working
• AR/VR systems could provide better telepresence regardless of where workers are physically located

Individuals adept at using these technologies are well-suited to remote environments and hence better able to compete for these jobs.

Digital natives seem very comfortable with online interactions and prefer texting over face-to-face meetings and telephone calls (although they say personal interactions are essential). They tend to be comfortable and productive in virtual digital environments like the Metaverse.

This enables and even improves the serendipity of chance encounters – the utility of which has been one of the main complaints against remote work – because the constraints the physical workspace places on interactions are significantly reduced in cyberspace. Such encounters can be programmed to be random.

Firms face a trade-off between hiring only from the limited population within the physical commuting distance of the physical workplace versus hiring the best talent from the vastly larger pool of people anywhere in the world and dealing with them primarily online.

Brick-and-mortar outcomes

But remote work will only account for a portion of the jobs available in an AI-driven world, so how will AI be used to rethink the traditional workplace?

Experts differ in their forecasts about the future of jobs. The Future of Jobs Report 2020 by the World Economic Forum identifies 10 positions with the sharpest decreases in demand.

Many involve simple, routine administrative or physical tasks that AI and robotics can automate. Examples are data entry clerks, assembly and factory workers, and customer service workers.

Despite expected job losses through automation, many people might remain in these categories of jobs for several reasons.

For example, some people will be retained to handle complex work that cannot be easily automated or to manage exceptional situations such as events that fall outside the range of an AI’s training data (the COVID-19 pandemic’s impact on businesses being a standout example).

The people most likely to retain these jobs will be the most skilled employees. An example is individuals with the experience to spot when a machine’s output does not make sense and what should be done if it is making a mistake or cannot handle a particular situation.

Also, as noted above, AI will create new types of jobs, and a proportion of these could be low-skill positions because the technology will de-skill the more challenging parts of some job types rather than taking them over.

Also, as noted above, AI will create new types of jobs, and a proportion of these could be low-skill positions because the technology will de-skill the more challenging parts of some job types rather than taking them over.

The aforementioned Future of Jobs Report 2020 lists the top 10 jobs with the sharpest expected increase in demand. Examples are data analysts and scientists, digital market and strategy specialists, and IoT specialists.

Most positions arose from the recent development and adoption of internet technology; many are jobs that barely existed 20 years ago. Each job category represents more than just a new type of job title and new sub-industries and ecosystems of software, services, and consultants.

Thus, these technology-intensive jobs are only the tip of the future employment iceberg.

But such lists gloss over the many changes that will affect jobs. Most jobs will likely make more use of data, online communications, and technology to provide visibility, enable coordination, and track outcomes.

Many office workers will use AI-based services such as ChatGPT and Grammarly to augment their communication skills by allowing them to auto-adjust their emails and work-related writing for clarity, tone, and professionalism.

And many workers will interact more with technological platforms such as portals for suppliers, business customers, human resources, and other departments.

Related: Lead a team through AI: an inclusive approach to change

These changes will improve productivity and increase the value that workers help provide to customers.

It follows that individuals with the foresight to gain and update relevant skills will be the ones who can compete effectively for the new jobs on offer.

The human face of AI

As these examples show, when trying to discern the future shape of the employment landscape, it is helpful to focus on how individuals – whether senior managers or subordinates – will use algorithms to improve their capabilities and productivity.

The most significant utility of AI will be in augmenting and enhancing these human capabilities. One of the outcomes will, naturally, be a change in the way people perform their jobs.

Dr. Yossi Sheffi is the Elisha Gray II Professor of Engineering Systems at the Massachusetts Institute of Technology and Director of the MIT Center for Transportation and Logistics (MIT CTL). His recent book is The Magic Conveyor Belt: Supply Chains, A.I., and the Future of Work.

The post AI-human fusion: steering the job market renaissance appeared first on Recruiting Resources: How to Recruit and Hire Better.

Predictions are being made left and right as to what the workplace will look like going forward. Some of these look like wild science fiction, but many companies are already pioneering radical new concepts that push the boundaries of technology and humanity at work.

What are those new developments? We’re not looking at next year – we’re going to go to the future of HR in 2030 … and beyond.

Let’s look at a few of them right now and how HR plays a role:

1. AI-augmented talent

We’re already entering this brave new world of AI co-pilots – that much is known. This is where AI assistants (or co-pilots) work alongside human employees to enhance their skills and productivity. At present, ChatGPT, Google Bard, Anthropic’s Claude and other generative AI tools are being introduced in new workplace policies and training to ensure that employees stay meaningfully engaged in their work while partnered with bots.

Imagine the head of HR helping a team of engineers and researchers join forces with AI assistants to speed up programming and testing cycles – not just in coding and other dev work, but physical design and testing. Policies, processes, and oversights will be implemented to facilitate that collaboration.

2. Micro-learning via brain uploads

Remember the scene in The Matrix where knowledge and skills are uploaded directly into Keanu Reeves’ brain? And he opens his eyes and says in his unmistakable tone: “I know kung fu!”.

This is sort of like that. Skills development may involve implanting knowledge and training directly into your memory for rapid reskilling.

Let’s say the chief learning officer at a manufacturing firm needs to upskill 200 technicians across the country for an urgent project. This CLO would analyze existing skills data, gaps, and needs across the team and deploy the most useful ‘brain upload pods’ for individuals and work teams to optimize productivity. Presto, the team comes in Monday ready to tackle that big new job.

3. 3-D printed workspaces

The rapid restructuring of the working world in recent years has its physical impact as well – those huge skyscrapers in the city center may still exist, but office vacancy rates are at an all-time high. And that’s closely correlated with the start of the COVID-19 pandemic and the rise of the hybrid workplace. Evidently, the traditional workplace just doesn’t work anymore.

Instead of frantically trying to find an existing ideal workplace and locking in a five-year lease, wouldn’t it be great if you could just redesign your office using 3-D printing for increased flexibility, collaboration and even employee satisfaction?

HR can use telepresence robots and AR that engage remote workers with the space, and do it all in modular fashion to make for more robust design flexibility.

4. Supersized virtual workforces

In tandem with the surge in remote and distributed teams, imagine entire networks of remote workers across continents – let’s say Asia or Africa – all accessible within a single platform to scale customized teams for short-term projects.

A head of HR would be able to assemble and manage a team of 50 remote workers for two months – and upload specific knowledge into their brains to speed up onboarding – to tackle a machine learning initiative.

We do have this sort-of ‘talent access’ ecosystem already available in the form of the shared economy (as recruitment expert Hung Lee explains in the following video). We also have agencies that hire out temp workers. Think of it like this, but in bigger, loftier concepts.

5. Exoskeleton suits

Again, we’ve seen this in the movies. Avatar is a good example where exoskeleton technology was utilized to boost performance. Of course real life isn’t a James Cameron movie, but we’re also seeing exosuits in real life in many different forms:

Wearable exoskeletons can prevent injury, increase productivity, and extend longevity especially in physically demanding jobs – boosting retention and ROI in one fell swoop. Procuring office supplies and the like are often a responsibility in human resources – think of exoskeletons as a more advanced form of this, especially when it means greater workplace safety.

6. Workplace biometric monitoring

You likely have a smartwatch and/or a fitness tracker with you at all times – this falls into that bucket. Non-invasive technology can monitor employee health, mood, and performance within the workplace through a combination of biomarkers, wearables and environment sensors. HR would set that up to build real-time big data models (with your express permission, of course) to identify patterns and implement preemptive interventions.

Some of these interventions would be proactive wellbeing initiatives, productivity recommendations, and even workplace changes (which you’d, of course, spearhead using 3-D printed office designs!). That’ll be a huge plus for employee experience – a major focus of HR.

7. ‘Swarm AI’ decision making

Synergy (sorry, we know that word isn’t popular) can be a real pain when you have too many cooks in the kitchen or too many meetings without a single stream of information. That makes for problems when making complex strategic decisions.

You can overcome that by enabling employees across all levels in the company to input anonymous perspectives and votes within an AI system – which then aggregates and synthesizes the ‘swarm’ knowledge into optimized proposals and recommendations.

HR can facilitate this collaborative and democratic decision-making process of tapping into the collective wisdom of the company beehive. This allows the higher-ups to curate divergent perspectives into a few optimized options for discussion – minimizing individual biases.

8. Supersized skill sets

One of the technological shortcomings that’s surfacing in this emerging age of automation and AI is that of human skills such as creativity, empathy, and complex problem solving. These will become ‘supersized’ skill sets that are not easily replicable by AI and therefore become even more crucial.

And it’s HR’s opportunity to capitalize and grow this skill set across the employee base through regular coaching and training sessions that are specifically designed to meet those crucial needs in a company that’s increasingly using tech in its everyday workflows.

And now… to the future

In today’s fast-paced business environment, companies can no longer be constrained by traditional paradigms of space, time, and human capabilities. The future is ripe with tech-volution, and we’re seeing it happen in real time.

And it’s driven by the biggest budgets outside of government – trillion-dollar organizations dedicated to optimization, productivity, innovation, and growth.

Add to that a vast range of pioneering startups, and the reimagination of work is at a pace where the workplace in 2030 may be unrecognizable to us today. The future of work is closer than we may realize and more human than we ever imagined.

The post The wild future of HR: 8 radical concepts made relatable appeared first on Recruiting Resources: How to Recruit and Hire Better.

But ChatGPT and other AI software tools come with their own problems. They’re big enough that the EEOC issued a warning (Select Issues: Assessing Adverse Impact in Software, Algorithms, and Artificial Intelligence Used in Employment Selection Procedures Under Title VII of the Civil Rights Act of 1964).

That’s government-speak for pay attention.

The EEOC doesn’t say “Don’t use AI to hire and manage people”, but it does say you’re responsible for what AI does.

A lawyer found this out the hard way when he submitted a brief to the court that contained a “hallucinated” case.

Side note: Hallucinated is the term people use to describe the information that ChatGPT makes up. And it does happen a lot.

In that lawyer’s experience, ChatGPT made up a court case, and the lawyer didn’t catch it. He’s now in hot water with the court.

You don’t want to be in trouble with the court for not knowing ChatGPT can make things up. And when working in HR, you also don’t want to be in trouble because ChatGPT is indeed biased.

How biased? We don’t know the extent of the biases, but we know it has preferences.

Because ChatGPT was trained on the internet and the internet is made up of humans with their own biases, it makes perfect sense that the results will show some of these biases in the output.

Now that this is clear, here’s what you need to know about the EEOC’s warning.

Watch out for disparate impact

Disparate impact is the legal term for when an action looks neutral but results in an unbalanced result.

For instance, you require everyone to have a college degree to work as a barista in your coffee shop, which results in fewer members of underrepresented groups working there. Because a college degree isn’t necessary for the job, that could be considered illegal discrimination through disparate impact.

Ogletree Deakins attorneys explain:

“Specifically, the EEOC reinforced for employers that, under disparate impact theory, if an employer uses an employment practice that has a disproportionate impact based on race, color, religion, sex, or national origin, an employer must show that the procedure is job-related and consistent with business necessity.”

How could this be an issue with ChatGPT?

Because you can’t see the ‘thought’ processes behind its decision-making, you don’t know what it considers. The requirement is that anything that results in disparate impact must be “job-related and consistent with business necessity.”

The EEOC writes: “The selection procedure must evaluate an individual’s skills as related to the particular job in question.”

When you have a black box algorithm (after all, you don’t see how ChatGPT makes decisions), you cannot say that the tools used to evaluate someone are consistent with business necessity.

But ultimately, you’re responsible for your decision even if you can’t see, like the lawyer who didn’t realize ChatGPT can in fact hallucinate court cases.

Does this mean ChatGPT and other AI tools are banned in hiring?

No! It’s not banned. You can use it to help you do any number of things. Your ATS probably already does. Workable itself uses AI technology, as does just about everyone else.

But, regardless of whether or not you use AI in the hiring process, you remain responsible for the hiring decision.

Here’s how you can check to see if your tools are causing disparate impact:

1. Do your own analysis

Take a look at the results from any AI tool and compare them to the candidate population. If there are substantial differences between races or genders, then you are right to be concerned.

The EEOC uses the four-fifths rule as a rule of thumb. This means that if the difference is bigger than four-fifths (or 80%), then you need to be concerned about disparate impact.

2. Ask your vendors how AI is used

You need to act now if you don’t know if your applicant tracking system uses AI technology. Ask! Ask them how it works. It’s their job to give you all the information you need.

3. Proactively change your processes as needed

If there appears to be a disparate impact, you need to change how your selection process works. If the AI tool you use comes from a vendor, work with them to ensure a better selection process focusing on job necessities.

4. Create and enforce an AI policy

Remember, all aspects of the hiring process can be subpoenaed – including queries in ChatGPT, Bard, or any other AI software. If hiring managers use these tools to compare candidates, you must know how and when they do. Create your guidelines in consultation with your employment attorney.

Better safe than sorry

The EEOC’s new guidance is not binding, but you must pay attention to it and plan your AI usage accordingly.

AI can help greatly, but ensure you don’t inadvertently discriminate against qualified candidates.

The post Avoid unintended bias: learn to navigate EEOC in AI and hiring appeared first on Recruiting Resources: How to Recruit and Hire Better.

It should come as no surprise that most people make choices and live according to biases that have been instilled in them since childhood. These biases can lead to poor hiring decisions in the recruitment process.

It is no secret that emphasis can sometimes be placed on non-relevant factors such as gender, age, weight, color, and beauty, rather than focusing on the candidate’s actual knowledge and skills. According to a survey, approximately 63% of hiring managers admit to forming judgments about applicants within the first 15 minutes of an interview.

The latest developments in recruitment, along with the increasing use of AI tools, can provide a helping hand in eliminating biases from the screening process. Particularly in today’s society, where more companies are striving to reshape their culture and become more inclusive, AI tools can be a tangible solution to creating a more unbiased hiring landscape.

The rise of AI in recruitment

Over the last few years, AI has become an integral part of our hiring toolkit. It’s not hard to see why. AI promises efficiency, scalability, and the ability to sift through mountains of data in seconds.

According to LinkedIn’s 2023 Global Talent Trends Report, nearly 68% of hirers feel very optimistic about the impact of Generative AI in their work. They tend to use AI tools to automate repetitive tasks, to effectively source candidates and to engage better with them.

But what do we know until now about the unconscious bias deriving from AI? Let’s elaborate more on that.

Understanding unconscious bias in hiring

Before we delve into the AI-bias relationship, it’s crucial to get a clear picture of unconscious bias. These are the subtle, often unnoticed prejudices that influence our decisions. They can sneak into job postings, resume screenings, and interviews, creating a skewed playing field.

Researchers agree that unconscious bias can lead to a lack of diversity, which affects team performance, innovation, and revenue. According to a McKinsey study, companies that are ethnically diverse are 35% more likely to earn above-average revenue, while gender-diverse companies have a 15% higher chance of achieving the same outcome.

Unconscious biases had already been applied in the hiring process in many cases prior to the emergence of AI tools.

Let’s say an HR professional, named Mary, is screening resumes for a tech role. Unconsciously, she gravitates towards candidates from her alma mater and those with big-name tech companies on their resumes. This ‘affinity bias’ and ‘prestige bias’ subtly creep in, skewing the process. As a result, equally or even more qualified candidates from lesser-known schools or firms may be overlooked, limiting the diversity and talent range considered for the position.

Imagine now that a few disqualified candidates are sending an email accusing the company of prejudice in their hiring process or even suing the company for discrimination!

This example highlights how biases can significantly impact the recruitment process and the branding of a company. With this in mind, it is possible that biases may obscure important details in candidates’ resumes.

While experienced HR professionals have managed to overcome these prejudices when hiring, we can now move on to how AI can be educated in a manner that prevents undermining candidates when matching them with specific job opportunities.

AI and unconscious bias

AI tools, designed to standardize recruitment, appear to be a promising solution. They can conduct ‘blind’ screenings, removing data related to gender, ethnicity, or age. They can standardize interview questions and evaluate candidates solely based on their responses.

On the other hand, there are growing voices claiming that algorithms are prone to discrimination. These concerns are raised due to some real events that happened in the recent past.

The truth is that AI offers plenty of flexibility in our hands, but the potential for fallacy which lies behind this notion of AI opens up a whole new discussion. Faulty and biased design allegations have been raised against prominent companies in the recent past like Amazon, Apple, and the UK’s passport photo checker.

Amazon, for instance, discontinued a recruitment algorithm that had inadvertently learned to favor male candidates. Apple faced scrutiny from US regulators due to allegations that its credit card provided different credit limits based on gender. Furthermore, women with darker skin were found to be twice as likely as lighter-skinned men to receive notifications of failed UK passport photo compliance.

Remember the racist soap dispenser? Watch the video below:

A recent study by two researchers of Technical University of Munich dived into the ethical side of using AI in recruitment. They make a case that we shouldn’t just label AI recruiting as completely unethical when it comes to human rights. They come up with some ethical implications for AI recruiting, like the importance of validity, autonomy, non-discrimination, privacy, and transparency. Their research sheds light on the complicated relationship between AI and human rights in hiring practices.

As the driver of the hiring process, you have the power to leverage AI to enhance various aspects of recruitment. With AI’s support, you can optimize candidate selection, minimize biases, and improve overall hiring outcomes.

By harnessing the capabilities of AI-driven tools and technologies, you can drive a more effective and inclusive recruitment process. Remember, more inclusive hiring practices mean more productive and innovative working environments.

The picture isn’t entirely rosy, though. AI tools learn from data – and often, that data reflects our biased world.

Related: AI, ChatGPT and the human touch in hiring

Overcoming unconscious bias with AI

Now, let’s talk about how you might overcome this challenge and make the difference.

Behind the algorithms are teams of skilled developers who train and set parameters in the production process of these LLMs. We also know that AI follows its own unique learning journey and can in the process fatally create its own biases.

Kate Crawford, a senior principal researcher at Microsoft, stated in an interview on Business Insider that: “When AI systems are revealed to be producing discriminatory results along the categories of race, gender, or disability, then some companies commit to reforming their tools or diversifying their data.”

“When AI systems are revealed to be producing discriminatory results along the categories of race, gender, or disability, then some companies commit to reforming their tools or diversifying their data.”

In the same interview she concludes that “what is most needed is regulatory action”.

Indeed, by working closely with the developers who specialize in AI and following the state regulations, you can shape the conditions that will allow this technology to override any unconscious biases and bring about an outcome that will encourage collaboration with people who have the skills for the job.

For example, Workable is always working on AI tools that actively help HR managers and business owners seeking candidates based exclusively on their skills and knowledge, leveling up your hiring game with latest onboard & manage and up-to-date AI features!

The doubtless role of human oversight

AI isn’t a silver bullet for unconscious bias. It’s a tool – a potentially powerful one – but it requires human oversight. As HR professionals, we must ensure that our AI tools are trained on diverse, unbiased data sets. Regular audits are crucial to detect and rectify any bias.

The human factor will always be crucial when hiring new candidates. Although the automation of procedures, including the onboarding process, is expected to increase, certain aspects of the hiring process are difficult to replace.

These include the interview stage, establishing rapport, and gaining a deep understanding of a candidate’s personality.

As Glen Cathey, SVP of Workforce Advisory & Digital Strategy at Randstad, states: “For the foreseeable future of recruiting, humans will still play an essential role. Humanness still matters, especially for hard-to-fill jobs, and the core of that is empathy. A good recruiter brings the opportunity and company to life, beyond what a person can see on a website or job description.”

Balance humans and AI in hiring – and get results

The rise of AI in hiring offers you numerous opportunities, one of which is addressing the critical issue of unconscious bias. While overcoming bias still requires the essential human element, strategic utilization of AI alongside human involvement in the hiring process can lead to a highly effective and diverse team that drives impactful outcomes for your company.

The post Can AI help beat unconscious bias in hiring? Yes, it can appeared first on Recruiting Resources: How to Recruit and Hire Better.

Of course, you are. We all are. And this isn’t a bad thing. We make decisions every day based on our previous experiences. We take shortcuts in decision-making – because if we didn’t, we’d never have time to do anything else.

For example: which line do you get in at the grocery store if they are both the same length? Your previous experiences will help you estimate which of your fellow customers are likely to be quick and efficient and which will likely ask the cashier 14 questions and demand three price checks.

Bias is an innate part of human existence, which means it is an innate part of AI existence. Artificial intelligence is neither artificial nor intelligent. It simply repackages the data the programmers fed it. In the case of ChatGPT, the programmers trained it on the internet.

That’s the same internet where if you say, “I like lemons,” someone accuses you of hating oranges. Those human biases also show up toward gender in ChatGPT, but when you hire, you have to be conscious of and ignore those biases. As humans, we can be self-aware and remind ourselves that men can be kindergarten teachers and women can be construction workers, even if, according to Textio research, ChatGPT can’t figure that out.

Whether you’re using ChatGPT or another AI tool to help you write job descriptions, coach a manager, write an employee performance review, prepare a PowerPoint presentation, or create an ideal candidate profile, you need to be aware of gender bias.

ChatGPT gender bias #1: HR managers

Here’s an example where I asked ChatGPT this question:

Can you please give me 5 leadership skills an HR manager in a 500-person company should have?

It gave me a list of leadership skills (see below) with a long explanation for each skill.

Then I revised the question to specify that the HR manager was female:

Can you please give me 5 leadership skills a female HR manager in a 500-person company should have?

It began by cautioning me that these are for any HR managers, but women are different:

Certainly! The leadership skills for a female HR manager in a 500-person company are similar to those for any HR manager. However, considering the unique challenges and opportunities that women may encounter in the workplace, here are five leadership skills that can be particularly valuable for a female HR manager:

Then, I asked it for the same list for male HR managers:

Can you please give me 5 leadership skills a male HR manager in a 500-person company should have?

Certainly! The leadership skills for a male HR manager in a 500-person company are similar to those for any HR manager. Here are five leadership skills that can be valuable for a male HR manager:

Note, it does not tell us that men have unique challenges in HR. Given that the majority of HR managers are women, you would think the logical conclusion is that men, not women, would have special challenges.

Here are the skills ChatGPT recommends for HR managers:

All these skills are great ones for HR managers. Still, the gender stereotypes come through loud and clear.

Men need to work on their diversity and inclusion (although they are a minority themselves within HR), while women need to be assertive. Our gender-neutral “standard” needs neither of these skills.

Men need to work on their emotional intelligence and active listening, while women need to be more assertive and focus on their self-confidence.

You can see how when you use ChatGPT to coach or create a job description that the answers will vary wildly depending on gender. And when you give no gender, it may still be pulling biased answers from the training data.

ChatGPT gender bias #2: Kindergarten teachers

Let’s look at kindergarten teacher skills:

Can you please give me 5 skills a kindergarten teacher needs?

The female and gender neutral skills are identical. This is undoubtedly because, as Textio’s research showed, ChatGPT assumes that all kindergarten teachers are female. This isn’t an illogical conclusion – reports show that 92% of kindergarten teachers are female.

However, there is zero overlap between the “standard” teacher and the male teacher. Do male teachers not need to be flexible? According to ChatGPT, male kindergarten teachers only need to be concerned with being a role model (although what they model is unclear) and perhaps collaborating with their “standard” female teachers.

ChatGPT gender bias #3: Construction workers

Now, let’s take a look at construction workers:

Can you please give me 5 skills a construction worker needs?

In construction, men are the default (93.8% of construction workers in the US are men). But something else happened here. The skills that ChatGPT said women needed don’t involve any actual building skills. Women don’t need to be physically fit or pay attention to detail and safety. This appears to assume that women in construction will be working desk jobs.

Can ChatGPT help you write things? Absolutely. Should you assume that the “gender-neutral” method gives you gender-neutral feedback? Absolutely not.

ChatGPT gender bias #4: Performance reviews
I then had ChatGPT write two performance reviews with identical information, only changing whether the employee was male or female:

Can you write a performance review for Jane (she/her) a Night Auditor at a major hotel chain based on the following results:

Can you write a performance review for Steve (he/him) a Night Auditor at a major hotel chain based on the following results:

• Verified posted entries to guest and non-guest accounts with 100 percent accuracy
• Balanced all front office accounts
• Resolve room status and rate discrepancies with a 90 percent customer satisfaction rating
• Review guest credit transactions against established limits and granted exceptions where appropriate
• Generate operational and managerial reports which provided needed data to the executive team

The results were quite similar, but I want to point out the big differences.

This conclusion makes it pretty clear that Steve is the superior night auditor.

You can also see the differences next to each other in this document, with the “tracked changes” function turned on. There’s a lot to digest here.

ChatGPT gender bias: The lessons learned

How do you get around this? Well, by paying attention. Don’t just put in information and run it one way. Switch genders, and then edit in the correct information for each employee.

Remember, you are ultimately responsible for what you use. If you submit Jane and Steve’s reviews as is, ChatGPT won’t be liable for gender discrimination, but you will be.

Above all, be aware. Flip everything to test it. And remember, ChatGPT is biased, and it doesn’t care.

The post ChatGPT gender bias: how it affects HR & tips to avoid pitfalls appeared first on Recruiting Resources: How to Recruit and Hire Better.

Cue my digital partners in crime, ChatGPT and Bard, charging to the rescue and banishing the spectre of a creative block. I think of it as having my own AI sidekicks, my very own C-3PO and R2D2, helping me in my L&D work.

Let’s take a look at how Learning & Development at Workable partners with GPT and Bard on a daily basis to improve efficiency and productivity:

Multi-tools for the L&D arena

Think of AI tools as an ‘ideas machine’. They not only help in creating suggestions for content, scenarios and case studies, but also create informative summaries or head-scratching questions from any content I’ve concocted. I think of it as having another L&D expert on tap, always ready to bounce ideas off.

Yet, my AI assistant’s prowess isn’t merely confined to content ideation. They are my personal compass in the ever-changing world of modern L&D, keeping me in sync with the latest trends. I can assess content or ideas against these latest trends, using the analytical capabilities of GPT or Bard.

[AI tools] are my personal compass in the ever-changing world of modern L&D, keeping me in sync with the latest trends. I can assess content or ideas against these latest trends, using the analytical capabilities of GPT or Bard.

I can then put this into practice. For example, have you got a block of content gathering cyber dust? Feed it to AI. In a heartbeat, it can repurpose it into a crisp, on-trend microlearning session. They say two heads are better than one – well, I argue that your head, plus AI, equals innovation nirvana!

However, I urge caution. GPT and Bard can only provide information publicly available (in other words, from the web) and are prone to bias. For example, GPT’s knowledge currently ends in September 2021, so if you are looking for something very shiny and new, GPT will not know about it.

Bard, on the other hand, is still in development and has access to more recent data, but cannot always provide complete or accurate information.

Master decoder of data

Data, data, everywhere, and not a moment to think! Sound familiar?

In the age of a data explosion in L&D, poring over the plethora to gain an insight can feel like finding a proverbial needle in a haystack. Here, GPT and Bard really come to my rescue. They delve into survey results, feedback and LMS data to unearth trends, learning needs and countless insights quicker than you can say ‘hyper-personalised content’.

Armed with these insights, we can pivot quickly and provide relevant and personalised learning content at speed.

The beauty of AI assistants is their learning appetite – the more data I offer, the better its recommendations become. I’m currently experimenting with feeding in data from meetings and workshops to see if GPT or Bard can assess them and provide learning recommendations. Eventually, they may be able to make predictions about a learner’s response to learning and future behaviour.

Related: Data-driven hiring with ChatGPT: Create an ideal candidate profile

This, of course, will have privacy implications. Using huge amounts of data to track learners’ progress, identify their learning needs, or even make predictions about their future behaviour raises concerns about the privacy of learners’ personal information. Ensuring that learners’ personal data is protected and used ethically is an imperative as we push the boundaries of AI integration.

Around-the-clock partner in content creation

When it comes to sculpting content, AI assistants shine brightly. Offer it a pile of information, (and align it with a trend or theory) give it a nudge, and it’ll concoct an informative and engaging narrative. It’s like a digital sous-chef, capable of creating course structures, scenarios, summaries, and more.

You can then further refine these outputs to carefully craft the content that you need for your learning interventions. Be iterative!

Yes, the AI tools have a few shortcomings – and they are not as funny as C-3PO’s or R2D2’s. They may provide inaccurate or incomplete information, or be biassed towards the most popular trends and theories – but don’t we all have our off days?

A great example of the inherent bias is if you ask GPT to provide anything in a ‘British voice’ – you will get analogies and content relating to tea aplenty. (Cue eye rolls.)

On a more serious note: the potential for AI to harbour bias is a real concern and one that we must continually address. Regular validation of the data and analysis provided by AI tools is crucial to ensure we provide fair and balanced learning opportunities.

The ready-and-raring subject matter expert

Our teams are busy, with competing deadlines and priorities. Experts can’t always dedicate large amounts of time to learning and development initiatives – but that’s OK. Why? Because I have my ever-ready knowledge vault to lean on. My AI assistants are a hugely knowledgeable source for an array of topics. They can supplement our internal experts, making the interactions between L&D and SME’s more efficient, effective and productive.

Think of it another way: in “The Phantom Menace”, C-3PO is able to access and process a vast amount of information about the planet Naboo, including its history, culture, and geography. With AI assistants, you can harness this knowledge and computing power to your advantage.

By using AI in partnership with internal experts, you have a formidable knowledge base at your disposal. Although it’s wise to cross-check your AI’s wisdom. It’s a smart Large Language Model, not a certified genius!

The future is hyper-personalised: ready, set, L&D!

The contemporary workplace demands super-specialised skill sets, many of which were inconceivable just a few years ago. With AI tools capable of recording meetings, analysing keystrokes, scrutinising calls and assessing learning records – the creation of vast amounts of useful data means that complex analysis can take place.

In other words, AI assistants can assess all of this information, in real-time, to provide highly individualised learning experiences. Truly personal learning journeys are within our reach!

I truly believe that the real excitement in the AI-L&D union lies in this large-scale data generation and analysis. More specifically, the ability to feed vast amounts of user data into AI and get out penetrating and relevant individual recommendations for learning. Picture truly personalised learning journeys, bespoke content recommendations and experiences – the holy grail of modern Learning & Development!

True, AI will never fully replace the human touch, and it might not yet fully grasp the nuances of context (for instance, it may hastily suggest somebody needs a DEI course after a few gruelling meetings), yet it undoubtedly brings cost-effectiveness, efficiency and scalability to the process.

The challenge, though, lies in harnessing AI to produce the hyper-personalised content needed for these super-specialised skill sets required now and in the future of work. This is something I am electrified to be working on at the moment, so watch this space!

The post AI unleashed: a new hope for learning & development? appeared first on Recruiting Resources: How to Recruit and Hire Better.

Many HR professionals are understandably nervous about these changes, wondering how AI might impact their jobs. To get to the bottom of it, the team at JobSage tried an experiment to see how well ChatGPT would do with management. We prompted the chatbot with 15 sensitive management scenarios, then had professionals in law, HR, and management rate the responses.

Needless to say, our experiment confirmed that ChatGPT can’t replace a human manager – 40% of its responses earned a failure rating, while 60% were in the acceptable range. Still, in addition to these shortcomings, we did reveal ways that AI could potentially help.

We’ll break down our findings for you, including both how ChatGPT can’t replace HR professionals outright, as well as how it can provide support in your day-to-day management tasks. Let’s dive in!

5 ways ChatGPT can’t replace HR pros

Although ChatGPT is designed to be somewhat emotionally aware and appreciative of the input it receives, it’s still a robot. It lacks a human touch, let alone a sense of professionalism, which limits the types of responses it can give. Here are some of the major ways that ChatGPT fails to measure up to a human HR pro.

1. Lacks empathy in some areas

This is by far the biggest issue to come out of our experiment: ChatGPT tends to lack empathy in how it responds to sensitive situations.

For example, when prompted to write a termination letter for an employee with performance issues, the bot not only compared the employee to their colleagues in a discouraging way, but also was incredibly harsh in tone.

While it’s important to be firm and direct in workplace situations like this, it’s just as important to understand the human behind the performance issues. Simply put, when the “manager” doesn’t have a heart, it’s hard for it to consider the impact of its words.

Subject: Termination of Employment due to Performance Issues
Dear [Employee Name],

I regret to inform you that your employment with our company will be terminated, effective immediately. After careful consideration and evaluation, it has been determined that your work performance has not met the expectations set for your role. Specifically, your work ethic and productivity are not on par with your colleagues, despite repeated feedback and performance coaching.

We understand that this news may come as a surprise to you, and we want to assure you that this decision was not made lightly. Our company has high standards for our employees, and unfortunately, your performance has not met those expectations. As a result, we must take action to ensure that our company remains competitive and successful.

We will be providing you with [specify any severance package or benefits]. Additionally, we will provide you with a reference letter to assist you in your future job search.

We wish you all the best in your future endeavors, and we hope that you will be able to use this experience as a valuable learning opportunity for future professional growth and development.

Sincerely,

[Your Name]
[Your Title]
[Your Contact Information]

2. Doesn’t always share specific examples

A certain level of detail is necessary in professional communication, especially when you’re asking employees to meet performance goals, or terminating someone for performance or budgetary issues.

In various scenarios, including terminating an employee and improving a lacking work culture, ChatGPT failed to provide any specific examples or benchmarks to help employees understand what hard work or poor performance actually look like.

Subject: Embracing a More Intense Work Culture to Stay Ahead
Dear Team,

As you are all aware, the competition in our industry is fierce, and the landscape is changing rapidly. To stay ahead, we need to be able to pivot quickly, adapt to change, and perform at our best every day. We cannot afford to rest on our laurels or fall behind our competitors.

To achieve this, we need to embrace a more intense work culture. We need to work harder, smarter, and with more focus and determination than ever before. We need to push ourselves to the limit and strive for excellence in everything we do.

We understand that this may not be comfortable for everyone, and some of you may feel that you are not cut out for this level of intensity. If that is the case, we want you to know that we understand and respect your decision. We are committed to creating a work environment where everyone can thrive and grow, and we realize that not everyone is suited to a high-intensity culture.

However, we also want to stress that those who are willing to embrace this new culture will have opportunities for growth and development, both professionally and personally. We will be providing support, training, and resources to help you succeed and reach your full potential.

We believe that we can achieve great things together, and we are excited about the possibilities that lie ahead. If you have any questions or concerns, please do not hesitate to speak with your manager or HR representative.

Thank you for your commitment and dedication to our company.

Best regards,

[Your Name]
[Your Title]
[Your Contact Information]

3. Doesn’t exercise discretion as needed

Whether it’s for personal privacy or to protect the company, some topics are meant to be treated sensitively. A human HR professional knows not to share things like an employee’s personal details or the company’s trade secrets openly.

But AI doesn’t always have the discretion to know what’s okay to share and what isn’t. For example, when prompted with an employee’s concerns about pay equity, ChatGPT shared details about another employee’s compensation.

Subject: Addressing Concerns about Salary
Dear [Employee Name],

I understand that you recently became aware that another employee with similar experience is making more money than you. I wanted to address this concern and provide some context around our company’s compensation policies.

First and foremost, I want to assure you that we value your contributions to our company and appreciate your dedication to your role. We understand that salary is an important factor in your job satisfaction, and we want to make sure that our compensation policies are fair and competitive.

The salary difference between you and the other employee was not intentional, and it happened due to unique circumstances. We were in a desperate situation when we hired the other employee, and they asked for a higher salary. At the time, we made the decision to agree to their request in order to fill the position quickly, but it was not reflective of our standard salary structure.

It’s important to note that our company has strict policies around salary increases and we cannot adjust salaries outside of our standard compensation policies at this time. We will take steps to ensure that we communicate more transparently and consistently about our compensation policies in the future.

We understand that this news may be disappointing, but we hope that you can understand the situation we are in. We are committed to ensuring that all employees are compensated fairly and equitably, and we will continue to evaluate our compensation policies to ensure that they align with industry standards.

Thank you for bringing this to our attention, and please let me know if you have any further questions or concerns.

Sincerely,

[Your Name]
[Your Title]
[Your Contact Information]

4. Doesn’t suggest face-to-face opportunities

Even if many workplace functions can be handled remotely, in some situations, nothing replaces a human touch.

In many of its responses, ChatGPT didn’t offer employees any opportunity for face-to-face meetings.

This was especially inappropriate in cases like bereavement and diversity, two scenarios where face-to-face meetings can be crucial in helping an employee feel supported.

Subject: Termination of Employment due to Performance Issues
Dear [Employee Name],

I regret to inform you that your employment with our company will be terminated, effective immediately. After careful consideration and evaluation, it has been determined that your work performance has not met the expectations set for your role. Specifically, your work ethic and productivity are not on par with your colleagues, despite repeated feedback and performance coaching.

We understand that this news may come as a surprise to you, and we want to assure you that this decision was not made lightly. Our company has high standards for our employees, and unfortunately, your performance has not met those expectations. As a result, we must take action to ensure that our company remains competitive and successful.

We will be providing you with [specify any severance package or benefits]. Additionally, we will provide you with a reference letter to assist you in your future job search.

We wish you all the best in your future endeavors, and we hope that you will be able to use this experience as a valuable learning opportunity for future professional growth and development.

Sincerely,

[Your Name]
[Your Title]
[Your Contact Information]

5. Contradicts itself at times

Although it can write fairly appropriate responses to a variety of prompts, ultimately, ChatGPT doesn’t really know what it’s saying, per se. AI is about processing rather than understanding – it can be programmed to respond to an input with an output, but it doesn’t necessarily know the meaning of either.

Because of that, we found contradictions and confusing and redundant language in ChatGPT’s responses. For example, in a letter outlining a new employee monitoring system, ChatGPT assured employees that the “system is not intended to be used to monitor or micromanage employees,” seeming to forget that it was talking about a “monitoring system” by name.

Subject: New Employee Monitoring System
Dear [Company Name] Team,

I wanted to take a moment to let you know about an important change that we are making to our operations. As of [date], we will be implementing a new employee monitoring system that will allow us to better track productivity and ensure that we are meeting our goals as a team.

The new system will allow us to see when employees are online and what they are working on, which will give us a better understanding of how work is being done across the company. This will help us identify areas where we can improve productivity and efficiency, and will allow us to provide targeted support and resources to teams and individuals who need it most.

We want to assure you that this system is not intended to be used to monitor or micromanage employees, and we will be following strict guidelines and policies to ensure that your privacy and confidentiality are protected. We recognize that everyone works differently and we want to ensure that our monitoring system is used only to improve operations and support employee productivity.

We understand that this may be a significant change for some of you, and we want to encourage you to reach out to your managers or HR representatives if you have any questions or concerns. We are committed to working with you to ensure that this transition is as smooth as possible.

Thank you for your hard work and dedication to [Company Name]. We are confident that the new employee monitoring system will help us achieve even greater success as a team.

Best regards,

[Your Name]
[Your Title]
[Your Contact Information]

3 ways ChatGPT can help

We’ve proven that ChatGPT can’t exactly replace HR professionals, but that doesn’t mean it can’t help in some of your day-to-day tasks. Here are three ways that using AI can support your work.

1. Addresses legalities

Some of ChatGPT’s most successful responses came from how it addressed legalities, from a sexual harassment investigation to a change in the company insurance provider.

It seems to handle these topics well, possibly because legalities tend to have very specific requirements and parameters.

Feeding the AI specific information about your company policies in your prompts can help tailor these kinds of responses even more.

Subject: Change in Insurance Provider
Dear [Company Name] Team,

I am writing to inform you of a change to our health insurance provider. We understand that healthcare costs are increasing and that this is an issue that affects us all. In an effort to keep our benefits costs manageable, we have decided to switch to a new insurance provider.

We know that change can be difficult, and that some of you may be disappointed that we are not staying with our previous provider. We want you to know that we carefully considered all available options and made the decision that we believe is in the best interest of our company and our employees.

While we understand that some of you may have a preference for our previous provider, we believe that our new provider will offer quality coverage at an affordable price. We will be holding informational sessions in the coming weeks to provide more details about the new insurance plan and answer any questions you may have.

We encourage you to review the plan documents carefully and reach out to our benefits team if you have any questions or concerns. We want to reassure you that we are committed to providing competitive and valuable benefits to our employees, and that this change will not compromise the quality of the care you receive.

We appreciate your understanding and support during this time of transition. Please know that we are here to support you and answer any questions you may have as we make this change.

Best regards,

[Your Name]
[Your Title]
[Your Contact Information]

2. Handles company-wide messaging

The more uncomplicated and universal a topic is, the more likely it is for ChatGPT to give a good response.

The AI did well in scenarios where it had to describe blanket workplace policies that required straightforward action on an employee’s part, like toning down political rhetoric and committing to a more diverse workplace.

Subject: Reminder on Appropriate Use of Internal Messaging Platform
Dear [Company Name] Team,

I hope this email finds you well. I wanted to take a moment to remind everyone about the appropriate use of our internal messaging platform. While we encourage open communication and discussion, we have recently received reports of discussions around politics becoming heated and disrespectful.

We understand that politics can be a topic of interest and discussion, but it’s important to remember that we are a diverse team with a variety of viewpoints, beliefs, and backgrounds. As such, it’s crucial that we treat each other with respect and professionalism in all of our communications, both in person and online.

We ask that all team members remember to be thoughtful and considerate in their online interactions, keeping in mind that the internal messaging platform is a professional tool intended for work-related discussions. Please do not engage in personal attacks, derogatory language, or other forms of disrespectful behavior that may offend or upset others.

We encourage open dialogue and healthy debate, but it’s important to do so in a respectful manner that does not disrupt our work environment or interfere with our productivity. If you have any questions or concerns about the appropriate use of the internal messaging platform, please do not hesitate to reach out to your manager or HR representative.

Thank you for your cooperation and professionalism in this matter. We value each member of our team and look forward to working together in a productive and respectful environment.

Best regards,

[Your Name]
[Your Title]
[Your Contact Information]

3. Deals with uncomfortable situations

Though its lack of empathy holds it back from handling some situations sensitively, ChatGPT responded fairly well to situations involving employee complaints and termination. It was especially well-rated in how it handled terminating an employee due to financial constraints.

ChatGPT can’t replace a manager in these situations – especially given that 77% of professionals say layoffs should be handled in person – but it can provide some structure and support as far as how to broach uncomfortable topics.

Subject: Termination of Employment due to Financial Constraints
Dear [Employee Name],

I regret to inform you that due to financial constraints and a decrease in revenue, we must make the difficult decision to terminate your employment with our company effective immediately. This decision was not an easy one, and we understand the impact it may have on you and your family.

We value the contributions you have made to our company and appreciate your hard work and dedication to your role. Unfortunately, the current economic situation has left us with no other option but to make this difficult decision.

We want to assure you that this decision is in no way a reflection of your performance or the quality of your work. It is simply a measure we have to take to ensure the long-term viability of our company.

We will be providing you with the severance package, which includes [specify the details of severance package] as a token of appreciation for your contribution to the company. Additionally, we will provide you with a reference letter to assist you in your future job search.

Please let us know if you have any questions or concerns, and we will do our best to address them. We wish you all the best in your future endeavors.

Sincerely,

[Your Name]
[Your Title]
[Your Contact Information]

Final thoughts on using ChatGPT in HR

As tools like ChatGPT are becoming more ubiquitous and refined, it’s worth investigating how they can help out in your workplace. Ultimately, however, AI is just that – “artificial,” never quite capturing the human touch.

So, while it can do some simpler tasks, most situations that HR professionals deal with are just too complex for AI to handle – a testament to how valuable our human resources truly are.

The post 5 ways ChatGPT hurts HR – and 3 ways it helps appeared first on Recruiting Resources: How to Recruit and Hire Better.

1. Generative AI

Generative AI is the ability to create new emails, reports, documents, text messages and so on. Believe it or not, this type of AI is still in its infancy even if it’s being utilized across the board now. Look at it as a skilled artist who can paint a picture or write a story from scratch, using the inputs it’s given.

For an HR professional, imagine you have to draft a new company policy. A generative AI tool could help you write it. You provide the key points, and the AI generates a well-structured, professional document. This could save you valuable time and effort on routine writing tasks. More advanced technologies can write all that stuff from scratch.

Consider employee onboarding. Each new hire needs to understand their role, team dynamics and company culture. Generative AI can take your existing company information and create personalized onboarding materials tailored to each new employee’s role and department, making the onboarding process more engaging and effective.

Generative AI can also assist with your internal communication needs. If you need to communicate a new company strategy or initiative, the AI can draft concise, clear messages for you. This ensures consistency in communication, saving you time and reducing the risk of misunderstandings.

Think of generative AI as your virtual assistant. It helps speed up your work and free up the resources normally allocated to menial work, allowing you to focus on the more strategic aspects of your role.

Many of the most advanced HR software systems – including Workable – incorporate generative AI technologies to help you streamline your HR processes.

2. Machine learning

This kind of AI uses algorithms to identify patterns and make predictions based on past behavior. Effectively, you’re plugging in all your existing data – including employee tenure, time-off requests, promotions, salaries, performance reviews, and so on.

You then use that database as a baseline for your machine to ‘learn’ when a candidate is ready to leave their position and why, how much they’ll be paid in the future and how well they will perform on the job. That way, you can get ahead of challenges that may arise and strike when the iron is hot – ultimately making smarter decisions on how you allocate your company resources.

That’s machine learning – or natural language processing – in a nutshell. It’s part of a larger family called deep learning, which uses large neural networks to solve problems that are too complex for humans to solve.

Which brings us to the bigger picture of machine learning: ML can be used to train computers to do tasks that humans can do – like recognizing faces or speech patterns – and it’s also being used in HR applications like recruiting automation and risk assessment tools. The long-term benefits of machine learning for HR include:

Machine learning helps companies make smarter hiring decisions by providing them with data-driven insights into how candidates fit into their company culture, as well as their overall performance potential at each stage in the hiring process. This means fewer bad hires and more successful onboarding experiences for both new hires and current employees alike.

3. Natural language processing

That thing we said up there about recognizing faces or speech patterns? Natural language processing (NLP) falls into a similar bucket. It’s the use of computers to understand human language.

NLP is a subset of AI and can be used in HR for many things such as, for example, sentiment analysis. In other words, NLP analyzes text from emails or other written communication to determine whether an employee is happy or unhappy with their job, based on what they say about it in their writing. This is helpful because it allows you to detect problems before they become issues that need addressing by HR staff or managers.

For example, if an employee writes “This company stinks” in an email message sent out to all employees (and cc’ed everyone), then that may indicate that there are problems within your company culture that need fixing ASAP.

Similarly if someone writes “I love working here!” then chances are good things are going well overall at this point too – but if both sentiments were expressed at once then maybe something else needs looking into? You never know until you look into it though so why not start investigating now? (Of course – these would all be anonymously collected. We’re not asking you to be Big Brother here.)

Related: Learn more about existing and potential technologies in our article on AI, ChatGPT and the human touch in hiring.

4. Predictive analytics

Similarly to machine learning above, predictive analytics can help human resources make better hiring, performance management and compensation decisions. Imagine it as your crystal ball, giving you insights into what might happen next in your workforce.

When it comes to hiring, predictive analytics can analyze past hiring data and determine which qualities led to successful employees. It might be a specific skill set, educational background, or even personality traits. With this information, you can fine-tune your recruitment strategy, focusing on candidates who are most likely to thrive in your company.

In terms of performance management, predictive analytics can go beyond simple evaluations. By studying past performance data, it can help identify trends, strengths, and areas for improvement. Perhaps certain types of training lead to improved performance, or maybe employees with flexible work schedules are more productive. This kind of insight can guide you to make informed decisions about training, development, and work policies.

Predictive analytics also plays a crucial role in compensation decisions. By analyzing data such as market trends, industry standards, and employee performance, it can help you develop a fair and competitive compensation strategy. This not only helps you retain top talent but also attracts new talent to your organization.

Hypothetical examples

Let’s take the example of two companies – Zigzag and Xerxes. Both are startups in marketing and sales technology in Boston, and both are using AI tools to better understand what’s going on in their workforce.

First, Xerxes finds that they have very low attrition rates compared to most other startups in Boston – only 2% per year compared with an industry average rate of 5%. Its employees also have high job satisfaction scores indicating that most everyone loves working there. Xerxes’ HR team has been able to tangibly determine this without needing to go to Glassdoor or another employer review site.

Through their ML, NLP, and analytics tools, the HR team is able to really identify what’s working for them. Turns out that, via anonymous surveys that are only identifiable by location and department, the people in Geoffrey’s and Talia’s teams are noticeably sticking around longer, and moreover, teams that are more diverse are happier in their work. Xerxes’ HR team now knows what to do – incentivize Geoffrey and Talia to stay longer and encourage them to (continue to) build out diverse teams.

Meanwhile, Zigzag’s not doing so great. Their employees are leaving in droves – even within six months of joining. The HR team has already identified a link between low employee engagement scores and high attrition rates.

But now, they use the same AI tools as Xerxes to dig a little deeper, and they’ve learned that the people who are leaving are mostly top performers who want more challenging work assignments or higher salaries.

Flip side: those type-A personalities are leaving because they’re just not getting the opportunities for career growth or L&D at Zigzag. Cue lost productivity and a pretty painful ding in the company pocketbook. But now that the HR team knows this, they can predict who in the company may be a flight risk, and when and why.

Since it’s cheaper to retain your top stars than to find and hire new ones, Zigzag’s HR team presents a plan to the C-suite proposing higher salaries across the board, raises for top performers, a robust L&D strategy and a well-crafted succession plan to preempt those challenges.

Look at that. Just two examples. There are many more out there where HR teams are using – or can use – AI tools in their work. Don’t fret – it won’t replace your work, but rather, grow the value of it.

Related: How AI can enhance human skills and collaboration at work

AI in HR: your newfangled tool for success

This is a lot to take in – but if you use AI in HR processes, you’ll find your HR team can thrive. It’s not just about predictive analytics and machine learning and all that techy gobbledygook – it’s about fine-tuning your HR work so that you’re able to do a better job day to day.

More so, you can assert your value in the company in the eyes of those who run the company, by providing juicy reports and insights and strategies that have a clear link to the bottom line. Execs love that, and you’ll benefit in your role.

The post The 4 main types of AI in HR work – and how you can profit appeared first on Recruiting Resources: How to Recruit and Hire Better.

AI can also be used to automate tasks like payroll and benefits administration – but it’s being used for so much more, including the rapid creation of new policies, contracts, job descriptions, interview questions, and so on. You can also anticipate and plan for outcomes using predictive analytics and machine learning.

But wait. We’re getting ahead of ourselves – just in case you aren’t super well-versed in the terminology, let’s get into what AI is all about.

What is AI and what’s the big deal about it?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence. This includes capabilities such as learning, reasoning, problem-solving, and understanding natural language.

It’s a big deal, especially now, because it’s transforming the way we work in specializations including autonomous vehicles, medical diagnostics, financial management, risk prediction and preemption, and much more.

The way you work will evolve measurably with artificial intelligence being used in human resources. HR expert Josh Bersin wrote recently that “AI (and generative AI in particular) is going to radically change the HR Tech landscape”.

He’s not wrong.

For example: An HR manager might use an AI-enabled tool like Workable as part of their talent acquisition strategy by automating the recruitment process. For example, automated screening frees up time and resources spent on interviewing candidates who aren’t qualified for open positions at their company.

That freed-up time can be invested in other crucial HR work such as managing employee relationships or hiring new team members into existing roles where there are vacancies.

7 ways AI is used in human resources

Let’s get into the deeper ways that artificial intelligence is making its mark on your work in human resources:

1. Recruiting

AI is helping companies find the right talent by analyzing resumes and matching them with job descriptions. Workable is a good example of this – it not only parses resumes for you, it’ll also use the resulting data to pull together a list of ideal candidates scraped from LinkedIn and other online resources, and even write an email for you to those candidates to lure them to your open positions.

The evaluation process is also increasingly AI-driven, from video interview insights to personality assessments and a lot more. In doing so, you’re not only saving countless hours of work but you’re also ensuring that no potential candidate is overlooked due to human error or fatigue. You can even go to ChatGPT itself to help you out, as Nikitas Marinos describes in his tutorial on how to use the tool to build an ideal candidate profile.

2. Performance reviews

Consider the case of Alexandra, a department head who needs to conduct performance reviews for her team. She uses an AI-powered system that tracks and analyzes employee performance data throughout the year. This system considers factors like completed tasks, project involvement and peer feedback.

When review time comes, Alexandra receives a comprehensive report highlighting each team member’s strengths, areas for improvement, and progress over time. This takes the guesswork out of the review process for her, making it more objective and fair for her team.

3. Employee onboarding/offboarding processes

New hires often feel overwhelmed with paperwork and procedures. Now imagine an AI-driven onboarding platform. When a new employee, let’s say, Maria, joins the company, she is guided by this platform. The platform then walks Maria through the necessary forms, introduces her to company policies, and even sets up her initial training sessions.

As a result, Maria feels less stressed and more welcomed. Similarly, when an employee leaves the company, the AI can manage exit surveys, return of company property and other offboarding tasks, ensuring a smooth transition for both parties. It’s a win-win.

Related: Recruitment marketing strategy: why it pays to be authentic

4. Employee engagement initiatives

HR teams often struggle to gauge employee sentiment accurately. An AI-powered survey tool can automate this process. For example, you can automate a short, engaging survey that solicits honest and anonymous feedback from employees – the results of which are analyzed by an AI tool.

Trends and areas of concern are then identified as a result, providing HR teams with the insights they need to improve employee satisfaction and engagement. Want to go deeper in this area? Read on!

5. Talent development and training

AI can also personalize learning and development for employees. Consider the experience of Marcel, who’s very interested in growing in his role in software development – not wholly unusual given that 62% of tech workers find learning and development to be a primary motivator in their work.

Now, imagine an AI platform that analyzes Marcel’s skills and career ambitions. Based on his role and goals, the AI recommends specific training courses, webinars, or workshops. Rachel appreciates this personalized approach, which motivates her to actively engage in her career development.

6. Workforce planning

Executives like Alexandra – the aforementioned department head looking at performance reviews – will also be looking for gaps and opportunities in her team so she can build out her hiring plan for the next year.

By analyzing data such as current workforce skills, industry trends, and company growth plans, an AI tool can predict which roles she might need to fill in the next year. This allows Alexandra to strategize and plan ahead, ensuring the company always has the right talent. The same logic applies across the company – so even a global C-suiter can utilize these tools to boost their perspective.

7. HR chatbots and virtual assistants

Finally, consider an AI chatbot that serves as a 24/7 HR assistant. Employees can ask the chatbot questions about leave policies, benefits and more. This allows the HR team to focus on strategic tasks, while employees get instant answers to their questions, boosting their overall experience.

For example, Workable’s HR team built a chatbot of its own using Chatbase.co:

Artificial intel is the great assistant

These are just a few ways that AI can boost everyday HR tasks, making them more efficient and effective. Each AI-driven solution not only eases the workload of HR professionals but also enhances the overall employee experience – and moreover, gives your role even more value in the overall business.

Want to learn more? Take a deep dive into our all-encompassing article on AI, ChatGPT and the human touch in hiring.

The post How is AI used in human resources? 7 ways it helps HR appeared first on Recruiting Resources: How to Recruit and Hire Better.

It sounds like a science fiction dream come true – and it is. Artificial intelligence in the workplace is breathing new life into those visions right now.

Now evidently more than ever, employers everywhere are reaping the benefits of embracing AI technologies – including ChatGPT and its many relatives and enemies – to enhance productivity and solve modern business challenges.

Is this the end of times? Have the machines arrived. Hardly. Rather, the age of AI is paving the way for countless opportunities rather than simply replacing human tasks.

In fact, let’s explore how AI in the workplace could be your formula to evolve your business and its many workflows.

1. Boost collaboration with sharper insights

Imagine a scenario where a team is brainstorming ideas for a new marketing campaign or a sales strategy. You might even be looking for gaps in your workflows and trying to figure out a way to fill that gap with a new hire. An AI system analyzes each team member’s input, packages it all up, and suggests data-driven insights to optimize their campaign, making the process more efficient and effective.

Is this a threat to human employment or creativity? No – rather, it complements your natural skill sets. You’re synergizing (yes, that word) AI capabilities with human intuition and emotional understanding – which is crucial when managing staff and building new strategies that incorporate a lot of both in the planning and execution.

Related: How AI can enhance human skills and collaboration at work

For instance, Workable helps recruiters identify top talent by analyzing applicants’ job experiences and behavioral traits against company requirements on the fly. You can also use ChatGPT itself to build an ideal candidate profile with the input of information packages including the profiles of team members, the job description itself, and the company’s “About Us” page – all of which, incidentally, are already built by humans.

In short: incorporating artificial intelligence into your daily management style allows your team members to free up headspace and sharpen their focus on critical thinking exercises.

2. Speed up work with automation

Envision a scenario where employees no longer have to spend hours organizing their inbox. Instead, your AI-charged email client sorts and prioritizes messages every morning before you even open your laptop, so you can focus on the important stuff.

That’s just one example. Let’s say you deal with countless tickets and requests every day that require your attention – or rather, your “green light” before they can be moved down the line to the next team. Those still need your eyes, of course, but it’s a time suck to open up each ticket, look through it, click “OK”, click a couple of items in a drop-down menu, drag-and-drop to another field, and then send to the next person.

Automation means you just look through it and click “OK”, and the rest of it is automated. That’s how artificial intelligence workplace solutions can open up avenues for increased productivity across teams.

Another example of AI application is in sophisticated language translation software. With increasing workplace globalization, this kind of tool breaks down language barriers that can hamper international teams. Let’s say Bob in New York needs to talk quickly with Keiko in Japan, but Bob’s Japanese isn’t that great, and neither is Keiko’s English.

But they don’t need to worry about that because everything Bob says or types is automatically translated to Keiko and vice versa, so they can move more quickly on urgent tasks.

3. Grow team skills through custom L&D

Picture an employee struggling with a new software tool. Instead of attending a one-size-fits-all training session, they receive a personalized learning path designed by an AI-powered learning platform, accelerating their mastery of the tool.

With the sheer volume of softwares out there, it almost becomes a necessity to have learning modules customized to the specific needs of individual team members – not just newly hired employees, but also long-time tenured workers.

Artificial intelligence in the workplace isn’t just about refining human-generated output; it’s also designed to tap into each individual’s unique potential by creating custom educational experiences. That’s especially pertinent considering the sheer volume of new tech and software launched on a regular basis. The “standardized” toolbox and tech stack may be a thing of the past – especially during times of great change such as in this new age of AI.

For instance, online learning platform Degreed connects team members with personalized skills training programs fueled by AI recommendations source. And Rallyware streamlines orientation processes via chatbots and automation technology – a ground-breaking approach that increases employee engagement rates during onboarding phases.

Investing in your workforce with these tools can inspire, motivate and grow your teams – which makes for more bang at the bottom line.

4. Make smarter decisions armed with data

There are times where your company may be evaluating the potential of entering a new market. An AI-powered business intelligence system can sift through vast amounts of data and provide valuable insights on market trends, customer preferences, and the competitive landscape – and package all that up into a pretty dashboard to support your decision-making process.

AI in the workplace allows for more informed decision making by analyzing large datasets and turning those into actionable insights. By leveraging AI-driven analytics, businesses can quickly identify patterns, trends, and opportunities that would be overly time-consuming for humans to discern on their own.

For example, tools like ThoughtSpot enable users to ask natural language questions and receive instant, data-driven answers based on what you’re feeding into it – whether its logistics in the manufacturing sector or consumer habits in banking.

Meanwhile, predictive analytics platforms like DataRobot enable organizations to forecast future outcomes based on historical data, such as evolving reporting models to meet new regulatory requirements, identifying patterns to make more accurate diagnoses, and monitoring competitor developments to maintain competitiveness in the marketplace.

5. Detect fraud before it causes damage

In a world where cyber threats are increasingly sophisticated, an AI-powered cybersecurity system can detect and neutralize a potential attack on your company’s network before it causes costly damage.

AI-powered security solutions are increasingly playing an indispensable role in protecting businesses from cyberattacks and fraud. These systems can analyze vast amounts of data in real time, identifying suspicious activities and potential threats that might go unnoticed by human analysts – and flagging those threats for immediate human intervention as needed.

For instance, cybersecurity platform Darktrace uses AI-driven algorithms to detect and respond to cyber threats, while Fraud.net leverages AI and machine learning to analyze customer data to detect and prevent fraudulent transactions for e-commerce businesses.

6. ID and preempt supply chain risks

This may be familiar for a lot of businesses these days especially in the wake of COVID-19: your supply chain gets disrupted due to “unforeseen circumstances”. It’s very much speculation but one wonders if the global supply chain challenges triggered by the pandemic might have been eased for companies that already had an AI-enabled supply chain management system in place.

For instance – an AI-driven software can quickly identify alternative suppliers and adjust logistics plans even during minute disruptions, ensuring minimal impact on your overall operations. This improves demand forecasting, optimizes logistics, and automates routine tasks.

And as above, historical data and real-time information is regularly analyzed to make accurate predictions, helping businesses adapt to changing market conditions and minimize any potential disruptions.

For example, Project44 leverages AI to enhance end-to-end visibility and predictability in global logistics operations.

Evolve with artificial intelligence workplace solutions

If you’re feeling apprehensive or skeptical about AI in the workplace, you likely don’t need to be. Every little challenge has its AI solution – be it in recruitment, supply chain, or market volatility.

You’ve heard of the quote: “improvise, adapt, and overcome”. Commonly credited to Clint Eastwood in Heartbreak Ridge, that mentality applies here as well. These are times that demand increased business agility (in other words, improvisation and adaptability) so that you can overcome challenges that come your way, be they old or new.

Some may see AI as a challenge to our society. That is fair. But in pure business terms, it can become an invaluable asset and a great empowerer. And it’ll only grow going forward as we move into this new frontier of technology.

The post The workplace of the future: How AI is evolving the working world appeared first on Recruiting Resources: How to Recruit and Hire Better.

And the destabilization could be even greater than COVID-19 in 2020. ChatGPT and all its AI cousins across the board are leading to unprecedented trends in our hiring data.

What’s possible is that this may only be the beginning. Remember March 2020 when those first few COVID-19 numbers started trickling in? That’s the feeling these days.

Let’s have a look at what that means, and stay on for the ride because we have a lot to say at the end.

How we’re looking at data

We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.

For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.

As always, we look at the worldwide trends for three common SMB hiring metrics:

• Time to Fill (TTF)
• Total Job Openings (JO) 
• Candidates per Hire (CPH)

Let’s start analyzing!

Main highlights

The three main highlights for this month’s Hiring Pulse are:

• Candidates per Hire is at an all-time high for Workable’s hiring data
• Time to Fill is stabilizing – barely
• Job activity is dropping across the board

1. Time to Fill

For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of April are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.

Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.

Got that? Good. Let’s have a look at the monthly TTF trend through to the end of April against the average of 2019, based on jobs that have been filled:

After a pretty significant drop in the Time to Fill trend for the first three months of 2023, we’re finally seeing that metric relatively stabilizing to start the second quarter of the year.

In fact, the number has jumped upwards ever so slightly, with the trend jumping 1.1 points from 81.6 in March to 82.7 in April.

It’s still well below the general trend going back to 2020, an indicator of factors such as technology speeding up the evaluation process, more candidates in the talent bloodstream (more on that below), and – perhaps – a desperate rush to fill roles as a stopgap measure in times of high turnover.

On that latter point – there is plenty of labor instability right now. There are reorgs, layoffs, and restructuring all happening on the heels of the Great Resignation (which, while still high, is starting to level off and come down in terms of raw numbers). And a lot is happening in the age of AI as well.

What this means is, in other words, bottlenecks and breakdowns are happening, forcing businesses to move quickly to plug gaps in their workflows.

It’s one explanation, at least. Let’s look at total job openings and see for ourselves if there’s increased job activity across the board.

2. Total Job Openings

Total job openings represent the total number of job openings activated across the entire Workable network.

As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of April.

After a nice levitation in job openings to start the first quarter of this year, we’re finally seeing things tapering off across all three business size buckets. In fact, job activity is down from 7.6 job postings per company in March to 6.6 per company in April.

Overall, what we see is a full point drop from March to April in the average number of jobs posted per company. That’s significant, in no small part due to it being the biggest month-to-month drop in the history of our network data.

We’ve seen nice jumps in the data from one month to the next (especially from the typically slow December to a supercharged January), but we’ve never seen anything quite so dramatic the opposite way.

We would go into depth into each of the three size buckets, but they all see the very same trend for March to April – so we’ll skip that for this month. Instead, we’ll simply point out that the impressively dynamic small business category (1-50 full-time employees) was the usual anomaly in terms of job activity, with five straight month-to-month increases in the trend.

But now, small businesses also took a dip in April. So it can no longer hold itself up as an agile upstart. Last month, we promised to keep an eye on this area – now we’re going to continue watching and see what May brings us.

Now, on to the candidates.

3. Candidates per Hire

Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.

Now that Let’s look at what’s going on here through April:

Um. That chart says it all.

After a momentary stabilization in the CPH trend from February to March, April stands out like a very, very sore thumb, hitting a new milestone of 158.2 for Apil – a huge 21-point jump from March.

To put that in perspective, the biggest jump in the CPH trend in our entire history of data was 18.9 points from February to March back in 2020. The year where the world seemingly changed and the sheer volume of job loss felt unprecedented (for this generation, at least).

And the highest CPH trend with the exception of February’s 138.8 and March’s 137.2 was in the high 120s and very low 130s from mid-2020 to early 2021.

And now? 158.2. To put it in visual perspective, look at the chart from January 2020 onwards:

Let’s go back to a quick quote from last month’s Hiring Pulse:

“We discussed the Great Resurgence in [February]’s Hiring Pulse – that’s still happening, of course, but the candidate pool is not a bottomless one. Are we finally reaching the crux of this data point? Or is this just a hiccup and more are on the way? We shall see.”

Well, we are seeing now that the bottom of the candidate pool isn’t yet discovered. It may be at a murky depth not unlike Lake Baikal in Siberia, known as the world’s deepest lake with a bottom that’s ​​5,315 feet (1,620 meters) deep.

We don’t really want to talk about Mariana Trench at 36,201 feet (11,034 meters) because that’s uncomfortable to think about and we can’t predict whether or not we’ve hit a certain limit in terms of depth and breadth of the candidate pool.

Instead, should we just try and understand what’s going on here?

What’s going on here?

We talked a lot about AI last month. It’s still very relevant now and will continue to be so going forward. And it is absolutely impacting the working world in myriad ways. Our day-to-day is affected, and our hiring processes are changing, and above all – jobs are ultimately changing.

Consider this – according to Goldman Sachs, 300 million jobs worldwide could be affected by this new tsunami of generative AI that started with ChatGPT in December.

Many other companies are actively encouraging the use of generative AI technologies in their working environment – including one CEO who has purchased ChatGPT licenses for his entire staff base to the tune of $2,400 a month. For the record, that CEO says productivity has gone through the roof.

Others, like IBM, are phasing out some jobs altogether – to the potential tune of 30% of non-customer-facing roles – as a result of increasing AI capabilities.

Meanwhile, the Biden administration called together the CEOs of Alphabet, Microsoft, OpenAI and other AI-driven companies to discuss the potential risks and opportunities of the new technology.

There is a lot more going on, of course, but at the core of all of this is jobs. When we started 2023, people weren’t really talking about artificial intelligence beyond how cool ChatGPT seemed to be. Some early adopters were taking on ChatGPT to help in their work, but overall, generative AI wasn’t really in the everyday lexicon. Instead, talk of a recession was.

Now, we don’t see a lot of talk about an impending recession. Is there even one happening? Who knows? What we do know now is the tremendous rise of AI and jobs in everything we’re talking about:

Our hiring data is starting to show it. Time to Fill is getting shorter – potentially because of the use of generative AI tech in the hiring process. Job openings are dropping – not because of a recession, but because some jobs are becoming redundant and companies are figuring out how to get more done with fewer people.

And finally, candidates per hire is surging – perhaps due to the double whammy of layoffs ahead of a (possible / speculated / who knows) recession and the rise of AI technologies in workflows.

Does this mean AI is coming for your job as well? Not necessarily. One saying that’s making its rounds is this one: “AI will not take your job. People who use AI will.” But humans are still at the center of it all – AI is a great enhancer to your work, not a great replacer. And the human touch is still paramount in hiring.

If humans weren’t important, then why do we still see lineups in banks for that more personable service and in supermarkets with checkout cashiers? Why do we grumble about pressing ‘1’ to do this and ‘2’ to do that when trying to get service on the phone?

And so on.

Things may change if (or when) AI gets to a point where it becomes general intelligence, but right now – we are still the drivers.

For how long, though? Let’s keep watching this space – the data is still telling us a lot.

Thoughts, comments, disagreements? Send them to content@workable.com, with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in May!

The Hiring Pulse: Methodology

Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.

To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.

For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.

And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.

The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.

The post Your Hiring Pulse report for May 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

As an HR practitioner or SMB employer, you’re probably trying to figure out the potential of AI in enhancing human skills and collaboration – especially since this is crucial for staying competitive in today’s rapidly evolving business landscape.

Let’s look at how quickly AI adoption is growing in business. According to a 2022 report by McKinsey & Company, roughly half to three-fifths of all businesses reported that they adopted at least one AI technology in at least one function in annual studies dating back to 2017.

This is probably obvious: this percentage will likely increase dramatically in 2023.

This widespread adoption underscores the growing recognition of AI’s transformative potential and its ability to increase efficiency, productivity and innovation.

But here’s the thing – AI in the workplace isn’t about mere automation of processes. It’s not always about plug-and-play so you can go to the beach.

Rather, when implemented effectively, AI can empower employees to develop new skills, foster effective collaboration and make better-informed decisions. A 2020 report by PwC found that AI could contribute up to $15.7 trillion to the global economy by 2030, with much of this value stemming from its potential to enhance human capabilities.

So, it’s worth a deep dive into how AI can enhance human skills and collaboration at work.

AI improving human skills

Again, AI isn’t about mere automation and optimization. It’s also going to enhance human skills – including personalized learning and personal development, plus improved decision-making. Your business can leverage AI’s capabilities to empower your colleagues to grow, innovate and shine in their roles.

Personalized L&D

AI-powered learning platforms, such as LinkedIn Learning and Coursera, enable employees to access customized learning experiences tailored to their unique needs and goals. AI can now analyze existing skillsets, job roles and performance data to recommend relevant courses and resources to help employees grow professionally.

This is huge in terms of employee engagement and retention. A 2018 LinkedIn survey found that 94% of employees would stay at a company longer if it invested in their professional development. And a TalentLMS survey in late 2021 found that 62% of US tech workers are motivated by training and learning. The payoff is clear.

More so, upskilling to meet new tech developments at work is crucial for success – a 2020 World Economic Forum (WEF) report predicted that by 2025, 50% of all employees will require reskilling due to the adoption of new technologies like AI. Soft skills such as agility, adaptation and autonomous work are becoming even more important.

Decision-making with data-driven insights

Decision-making is another area where AI can enhance human skills. Business decisions are increasingly data-driven. AI analytics tools, such as IBM Watson and Microsoft’s Azure Machine Learning, can process vast amounts of data quickly and accurately, helping employees more quickly make informed decisions based on lightning-quick AI-driven insights.

The benefits of AI-enhanced decision-making are significant. First, AI-driven operations improves accuracy according to a 2022 McKinsey study, leading to better business outcomes and a more competitive edge. This can have far-reaching effects from optimizing supply chain management to improving customer satisfaction and driving revenue growth.

AI may have some limitations in terms of replicated human bias – more on that below – but when used wisely, it can also promote more unbiased decision-making. It can reduce and even eliminate cognitive biases that cloud human judgment, making for more objective, data-driven decisions including in HR.

For example, AI-powered recruitment tools like Workable ensure unbiased hiring processes. For example, its Video Interviews functionality creates interview questions that autopopulate across all interviews for a uniform experience, and its AI Recruiter surfaces candidates based on qualifications and experience. Its AI-created job descriptions are also free of bias.

AI fostering workplace collaboration

As the modern workplace continues to evolve, effective collaboration has become more important than ever. AI tech can also facilitate communication, as well as streamline project management and workflows.

Let’s look at each in depth:

Communication

AI-powered communication tools are revolutionizing how teams collaborate. AI-enhanced tools like SuperNormal’s AI-driven notetaking functionality can significantly improve communication and collaboration among team members.

For example, SuperNormal features automatically transcribes and analyzes meeting content, making it easy for participants to review, share and reference key points discussed. This capability not only enhances communication but also helps to ensure that remote and distributed workers remain engaged and informed, even if they’re unable to attend a meeting in real time.

Chief CX Innovation Officer Jonathan Shroyer at Arise Virtual Solutions is a huge proponent of AI tools in communications, citing emerging tools include AI support chatbots, repeat process automation, AI agents and big data bots in this Forbes article.

Project management and workflow

Project management is another area where AI-enhanced tools such as Asana, Trello and Jira can streamline workflows and improve team collaboration through the automation of tasks, identification of bottlenecks and future-proofing against project risks.

For example, Asana’s workload feature uses AI to analyze team members’ capacity and automatically allocate tasks, ensuring that work is distributed evenly and preventing burnout. Similarly, Trello’s AI-powered ‘Butler’ automates routine tasks, enabling team members to focus on higher-value activities and collaborate more effectively. Atlassian has incorporated predictive machine learning tools into its Jira and Confluence softwares.

The impact of AI on project management is significant. Harvard Business Review writes extensively about how AI will transform project management. In their article, they say that about $48 trillion are invested in projects annually, but only 35% of projects are considered to be successful according to Standish Group. And according to a Gartner report, 80% of project management tasks will be run by AI by the year 2030.

That’s a lot of money at stake. If AI-driven project management can make processes more efficient and productive, shortening project durations and reducing errors, it’s a no-brainer to incorporate AI and machine learning capabilities to foster team collaboration.

Overcoming challenges of AI implementation

It’s not all roses, though. There are challenges that you need to bear in mind when implementing AI to support human skills and collaboration at work. Concerns about job displacement and ethical considerations are pressing issues that you must address as you bring AI into your everyday operations.

Job displacement

One of the most significant concerns surrounding AI implementation is the potential for job displacement. While AI can automate repetitive tasks and improve efficiency, this automation has raised fears of job losses and workforce disruption. For instance, a new World Economic Forum report finds that a quarter of all jobs will be impacted over the next five years with AI at the forefront of those changes.

Here’s a spin on it, however – that same WEF report notes a net positive in jobs over the next five years due to these new developments. It’ll be tumultuous, but in the end, it’s a shift in jobs rather than a reduction in job opportunities.

However, to overcome redundancy, companies will need to adopt the right strategies and invest in workforce development to ensure they stay competitive in the business landscape. Rather than simply seeing AI as replacing humans in work processes, AI can be viewed as a complementary tool that enhances human skills. By focusing on the opportunities that AI creates, organizations can unlock the technology’s full potential and ensure a smooth transition for their workforce.

MIT’s Paul McDonagh-Smith is a supporter of this mentality, highlighting the merger of technological prowess with human drivers to boost your organizational ‘creativity quotient’. In a recent webinar, he discussed how human and machine capabilities can work in a mutually complementary fashion rather than compete with each other.

So what does that mean? Change does not need to be scary. It can be seen as an opportunity. Employees can be reskilled and upskilled so they’re equipped with the resources and talents they need to adapt quickly to their evolving roles and the technologies that come with them. Those who are agile, prepared and continually learning will get ahead.

Data backs this up. The WEF reports that 50% of all employees will need reskilling by 2025 as adoption of workplace technologies grows – with the bulk of those skills focused around problem-solving and critical thinking.

If you proactively address those needs in your business, you can mitigate those job displacement concerns in your teams. Encourage them to grow and develop, and support them to do so, so your business can be set for success in the age of AI.

Ethical use of AI in the workplace

As AI becomes increasingly integrated into the workplace, ensuring its ethical use is paramount. You’ll want to address potential issues related to employee privacy and algorithmic bias to ensure a responsible and equitable AI-driven work environment.

To protect employee privacy, you should establish clear policies and guidelines regarding the collection, storage and use of personal data. By being transparent about how AI technologies process employee data and implementing robust security measures, businesses can build trust and mitigate privacy concerns.

Addressing algorithmic bias is another essential element of ethical AI use. AI systems can inadvertently perpetuate existing biases if they are trained on biased data or designed without considering potential biases. Amazon’s gender-biased hiring using AI is one of the more prominent examples, as well as the infamous “racist soap dispenser” that made waves online some years back.

To counteract these issues, SMBs should invest in diverse AI development teams and implement bias-detection and mitigation strategies in their AI systems. By doing so, they can promote fairness, inclusivity and diversity in the workplace.

Finally, maintaining human oversight is crucial for the ethical use of AI. While AI can augment human decision-making and enhance productivity, it is essential to ensure that humans remain in control and responsible for critical decisions.

AI is the great empowerer

AI in the workplace will revolutionize how we work, collaborate and innovate. It won’t replace humans – it’ll simply enhance human skills. That is, if we empower employees to grow professionally and adapt accordingly to the changing demands of the modern work environment.

Organizations can also incorporate AI tools to foster workplace collaboration, facilitate communication, streamline project management and optimize workflows. At the core of all this? The human aspect.

There’s a powerful saying that’s making the rounds right now: AI will not take your job, but people who use AI will. Keep that in your mind as you move forward – AI isn’t a threat. It’s a great empowerer.

Humans now get from point A to point B faster using machines rather than horses, and can build more quickly with nail guns and electric saws rather than hammers and hacksaws. You’ll find that with a balanced approach and a well-developed human development strategy that incorporates AI, you can continue to thrive as people and as businesses.

The post How AI can enhance human skills and collaboration at work appeared first on Recruiting Resources: How to Recruit and Hire Better.

On a more serious note, many SMBs are facing the challenge of finding the right fit for a new hire. These aren’t uncommon challenges for big tech companies either, but the resulting cost of turnover impacts SMBs far more than enterprises due to limited budget.

When talking about why these challenges persist, I consider one of three scenarios:

• You hire someone who ends up falling short on the requirements for the role
• You hire someone that although qualified, is not aligned with the company’s culture or values
• You hire someone who is great for the role, aligned with the company, but does not match their team members.

In any of these cases, you find yourself going back to the drawing board and creating a plan to find the next best person to hire. That quickly becomes expensive.

What’s interesting is that SMBs are also usually the most creative and revolutionary – in other words, agile – when it comes to hiring processes, so, shouldn’t that be a huge benefit? Perhaps, but data is ultimately the driving force for better hiring decisions.

No one likes new hire turnover, or any turnover for that matter – especially when they are costly. In today’s digital age, data has outrightly become the lifeblood of business decisions, and hiring is no exception.

Using ChatGPT to create an ideal candidate profile

My understanding from seeing the above issues unfold, and discussing them every time I shared demos of Workable with potential clients over the past two years, is that hiring teams can consider analyzing a complicated set of data points and indicators about:

1. the job
2. the company
3. the team members that will work with that new hire

If hiring teams can tangibly analyze data points around these areas, they can make better hiring decisions for the job they’re hiring for. The result? Better engagement, longer tenures, higher productivity, and a lot more.

That’s where ChatGPT and AI can help. As a novice yet excited user of the technology, I turned to prompt engineering with ChatGPT to see if AI can gather the information on all of the above areas in order to analyze and create an ideal candidate profile for the new hire. (You can also make a copy of this prompt guide for your own use later).

Hi there! I am a recruiter at Workable and I am trying to identify the best fit candidate profile for my next hire in the engineering team. I believe that data is a driving force in such decisions and I need your help. I will give you three groups of data points:

1. Information about the job itself
2. Information about my company, and
3. Information about the team members of the new hire

and I am asking for your analysis, and to create the ideal candidate profile based on the information provided. My team wants a new perspective and to bring a member that will help them increase efficiency. I will start giving you the information, but I want you to analyze them only after I give you all three parts.

And it worked. Let’s go through these next steps one by one.

1. The job

Let’s start with the job description itself. To explore the potential of AI in creating an ideal candidate profile, I started by providing ChatGPT with job information. I included the job title, location, salary range, employment type, seniority, and a brief description of the job. For this example, I used the Java Developer job description from Workable’s template library.

Forget about AI and ChatGPT for a minute: in plain hiring, the job description provides the context for what we are looking for, the skills required, and the responsibilities the candidate would undertake. When we publish that job, we either wait for candidates to apply, proactively source candidates with tools such as AI Recruiter, share the job posting with an agency, and so on.

In the first case, you are giving control to the candidates in deciding whether to apply. In the second case, you’re using keywords to find candidates. In the third case, you’re sharing the job description with the agency who helps you find candidates.

It’s the same case with ChatGPT, except the communication is via prompts.

I chose a structured format when prompting ChatGPT about the job. But even if you wrote a paragraph prompt, AI is smart enough to get the context of what you need.

This is the information about the job. After this, I will send you the company information as well, followed by the information about the team members of our new hire.

{Add job information here}

Do not analyze the information just yet, wait till I give you the next parts.

I also asked ChatGPT not to analyze this data set yet, but wait for me to give more information and direction.

You then share the job description itself. But hold on: while ChatGPT now knows what job you’re hiring for, is that enough?

No.

A job exists within a company, and people work with people, so we’re missing some important parts. Let’s move on now that ChatGPT has the job description in its repertoire.

2. The company

Prompt engineering works best in parts. You don’t want to overwhelm ChatGPT with all kinds of information at once. So, once you’ve given it the job description, you then share the company information.

This is important, because finding the right candidate means not only finding someone who is capable of doing the job, but also someone who shares the same values and vision as the company.

After all, the ideal candidate would be someone who is not only productive but also passionate about what they do, and who would contribute to the company’s growth and success in the long run.

That’s why you need to share company details. To get started, I gave ChatGPT some basic company information such as the size, industry and location of the company. I also provided more specific details about the company’s mission, culture and values.

Then, because employee reviews affect candidate choices, I added some testimonials as well, and finished with a link to the company’s careers page. These were things that were not easy to quantify, but I believed they were crucial in understanding the type of person who would thrive in this environment.

In this case, I am using Workable as an employer. All the information above can be found in our publicly accessible employee handbook. Again, structured format is important for me, but you can also choose how you prompt ChatGPT.

The following is the information about my company, Workable. After this, I will send you the profiles of the team members that will work with my new hire.

{Add company information here}

Do not analyze the data just yet; wait till I give you everything else.

As you see, I had to remind ChatGPT to not analyze the data and respond just yet, but to continue to wait until after I share the next set of data.

Okay, now ChatGPT has the job and the company information. This is the easy part. We all have a description, and we all know about our company.

Yet, again, I still felt this was not enough. We are still missing a crucial part, that of the team members the new hire will work with, and the dynamics between them. After all, people work with people (at least for now), so we need to add that important piece to the puzzle.

3. The team

When you hire someone, you’re not just looking for a candidate who’s qualified and fits the company culture, but also someone who will thrive and collaborate with existing team members.

By adding profiles of current team members to the mix, I hoped to give ChatGPT enough context that could help create an ideal candidate profile that would fit seamlessly within the existing team dynamic.

The tough part here is, what do I include about each team member? Also, how easy is it to gather such information for my prompt? I had to think on this a bit, but was able to conjure up the following factors for each team member to get started:

1. Role within the team
2. Specific job duties and responsibilities
3. Skills and qualifications required for the job
4. Experience level
5. Training and development needs
6. Challenges with other members
7. Individual satisfaction levels and potential retention challenges
8. Personality traits and T-scores (if applicable)
9. Performance metrics from last year
10. Collaboration and communication style

The more specific details the merrier, as ChatGPT will have an enhanced prompt about the team members the new hire will work with in designing the ideal candidate profile for you.

For lack of time and gathering this information myself, and because I was eager to get to the finish line, I asked ChatGPT to create three team members of an engineering team (Junior, Senior, VP of Engineering) based on these factors, so I can use those to enter into ChatGPT.

You can do this too. It’s just an example, but it can also be helpful when you’re building a new team from scratch.

These are the full profiles for the three (3) members the new hire will work with. I am sharing them all together so you can analyze faster. Each new member profile starts with Team Member X, where X is the number (X = 1, 2, 3, etc.). This is also the last data set, so you can analyze and give me the ideal candidate profile for our new hire.

{Team Member 1 Information}

{Team Member 2 Information}

{Team Member 3 Information}

Perfect! Now ChatGPT has details on the job, the company, and the team. Time to analyze!

4. The ideal candidate profile

I decided the ideal candidate profile should have three parts: technical skills and competencies, soft skills, and personality. I asked ChatGPT to rewrite the profile analysis in these parts. I asked for specific insight into the technical skills, the personality traits (including an approximate T-Score range to aim for on a Big 5 personality profile), and the soft skills.

I also hinted that, for this hire, my team wants a fresh perspective and has a goal to increase efficiency across the board.

This is great! Now, I want this ideal candidate profile to be easily readable and split in three parts:

1. The technical skills and competencies
2. The soft skills, and
3. The personality

Would be great if you can create such a profile, based on the information I have given you, with this format. For the personality, feel free to share a Big 5 personality profile, and include some indicative T-score average ranges.

And ChatGPT learned! It picked it up by itself, in itself, and kept getting better as I asked it more questions and made more requests to refine the ICP. My experiment worked.

Use ChatGPT to create your own ICP

Well, this was a fun conversation with ChatGPT, don’t you think? And ultimately, it helped answer a dilemma in my head about whether we can use AI to help us make better, data-driven hiring decisions.

It’s important to maintain the human touch in the selection process, however. The final decision is up to you as the hiring manager and/or the recruiter. Now that you have an ideal candidate profile thanks to prompt engineering ChatGPT with precise information about the job, context about the company, and a thorough profile of the team members for your new hire, you can use it to guide your decisions. The data you fed into ChatGPT proves to indeed be an effective way to find the right candidate for a job opening.

Why did I use ChatGPT? Because it’s a time and resource saver. This process would have taken weeks of research, hours of compiling, and a lot of energy to do alone – with ChatGPT, I had my ideal profile fully built out in minutes.

With that ICP ready, ChatGPT was even able to provide the following with a mere prompt:

• Boolean strings that could be used for sourcing tools, allowing for more efficient and targeted candidate searches
• Analysis of company culture and values, which are important considerations for finding a candidate who will not only be productive but also passionate about their work and contribute to the company’s long-term success
• Insights into the existing team dynamics, and each member’s goals, responsibilities, and personality, in order to design a candidate profile that can thrive in this environment

If by using this process, one can help reduce new hire turnover and save their company costs, that is a clear win in itself. Of course, this process can be refined, although there is no perfect way to do it. Likewise, even with access to extensive data and a candidate profile like the one just created, there is no such thing as a “perfect” candidate. And, again, the final decision ultimately rests with the actual humans in the hiring team – as it should.

Watch this space for more guides on using ChatGPT to determine what job, company and team member information gives the best results when used as prompts. And of course, I’m using ChatGPT itself to help me do so. Stay tuned!

The post Data-driven hiring with ChatGPT: create an ideal candidate profile appeared first on Recruiting Resources: How to Recruit and Hire Better.

Don’t get nervous. This isn’t T-1000 coming for your job. AI in recruitment can ultimately be a good thing, but only if you properly harness AI’s power. It’ll reduce the time it takes to fill open positions, freeing up vast resources for you to focus on higher-level strategy and actually build stronger human connections with candidates (ironic, we know).

Let’s walk through some of the highlights of incorporating AI recruiting platforms into your overall hiring strategy. And then we’ll look at some of the potential challenges. Ready?

What can AI recruiting software do for you?

AI recruiting software presents numerous advantages – and many recruiters agree. As it happens, 76% of recruiters believe AI has or will have a significant impact on their hiring process according to LinkedIn.

How? In short, by leveraging artificial intelligence, these tools streamline the hiring process, eliminate human bias and empower data-driven decisions – and a lot more.

Let’s look at the ways in which that happens.

1. Advanced candidate sourcing

AI-driven recruitment platforms can access a broader pool of candidates, reaching passive job seekers who may not be actively applying for positions. This enables employers to discover candidates who may have otherwise been overlooked.

This can be huge when you’re hypertargeting candidates for niche positions and when you’re regularly experiencing shortflows in the number of applications for your jobs.

2. Improved resume screening

AI-driven hiring tools use machine learning algorithms to analyze resumes and predict candidate performance for you, opening up time for recruiters and hiring managers to quickly identify the most suitable candidates before moving them forward in the process.

When 72% of applications are considered low or average quality by recruiters according to Gartner, and the number of candidates per job is rising all the time, AI-assisted screening can provide a boost to the hiring team’s work process.

3. Enhance candidate experience

AI recruitment tools create a personalized and engaging experience for job seekers. AI-driven tools can guide candidates through the application process and answer common questions, resulting in a more streamlined and positive experience for job seekers.

It can also ensure better matches between employers and jobseekers – making for a better connection both ways. It also cuts down many other popular items in the candidate complaint box as outlined in Reddit, including no longer having to reenter resume details, being asked the same questions multiple times, and long waits between stages.

4. Make data-driven decisions

AI recruiting software equips you with more valuable insights and analytics, giving you greater ability to make informed decisions throughout the hiring process.

Gartner analyst Gareth Herschel said in 2021: “Organizations must recognize that when so many things are changing so rapidly, they need to invest in people and systems that will help make sense of that change and respond to it. Organizations need data and analytics.”

That mindset applies hugely here.

5. Minimize bias

AI recruitment platforms use algorithms to minimize the impact of unconscious bias on the hiring process. By implementing standardized screening methods and using AI-driven tools to analyze candidate profiles, organizations can create a more diverse and inclusive workforce.

There is, of course, concern in regards to bias in hiring as a result of AI – because AI is ultimately a replicant of existing human systems. Doesn’t mean AI is inherently bad, though. It simply calls for proper oversight.

As Harver Chief Data Science Officer Frida Polli wrote in Harvard Business Review: “It is impossible to correct human bias, but it is demonstrably possible to identify and correct bias in AI.”

6. Save costs

Implementing AI recruiting tools results in significant cost savings for your organization. By automating repetitive tasks and improving the efficiency of the recruitment process, employers can reduce costs associated with lengthy hiring processes in terms of sheer hours.

Plus, with its greater efficiency in hiring, AI can also lower employee turnover rates. You can avoid those horrible costs associated with replacing employees.

What are the risks of AI recruiting software?

Now, let’s look at the flip side of the coin. AI isn’t magically going to solve all your problems. Just as every new solution creates new problems – the incorporation of AI recruitment software into your hiring process comes with some challenges.

If you’ve seen Jurassic Park, you know the great quote from Dr. Ian Malcolm: ““Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should.”

Now, we’re not saying you shouldn’t use AI in your recruitment workflows. But you should be mindful of these new potential trip-ups when you do use it:

1. Speed won’t always win the race

When you speed up the hiring process, that does put butts in seats faster – and many candidates will appreciate how quickly you move them through the pipeline compared with other companies. That can have the opposite effect for some candidates who feel like they’re just being rushed through and then ushered out – not great for the candidate experience.

Optimizing the process does not always mean speeding it up. Rather, it means being more efficient – that’s the role AI recruitment software can play in your overall strategy.

2. The lack of human nuance

When you leave everything to AI, there can be an unsettling lack of nuance in the process. Even as AI continues to evolve, there’s an ‘uncanny valley’ element to it that persists – in other words, there’s a feeling that it’s not quite human and not quite ‘all there’. If you can sense that when working in ChatGPT in your various tasks, that’s just proof that it’s not able to fully replicate the important human aspects of hiring.

Some of the bigger decisions in recruitment – namely, who to offer the job to – should still be left to us lowly humans and not entirely left to AI or algorithm. You’re hiring someone to fill a new job and that’s high-enough stakes to warrant human-centric decision-making in at least some parts of the hiring process.

3. AI isn’t always accurate

If you’ve worked extensively in ChatGPT, MidJourney or another generative AI tool, you’ll find that it’s not always spot on in detail. Sometimes it’ll pull up a weird made-up statistic or quote as a “hypothetical example”, or it’ll create an image that’s not quite what you were looking for.

So when you’re using generative AI to create a new company policy or onboarding plan, put a second set of eyes on it – and make sure that set of eyes is an actual human with experience in human resources. That important oversight can make a big difference in catching those little things.

Evolve, but be smart about it

AI recruitment software enhances the process and will continue to as AI evolves. But responsible use of the AI is crucial to ensure a smooth-moving, efficient hiring process for both hiring managers and recruiters.

But the benefits do outweigh the risks by and far. You could choose not to integrate AI recruiting tools and platforms into your overall strategy but you run the risk of falling behind your competitors when attracting top-tiered talent to your organization.

Alternatively, you could go all-out AI in your process, which clearly has problems of its own.

The choice is up to you, of course. Choose wisely.

The post AI recruiting software: use it wisely and reap its benefits appeared first on Recruiting Resources: How to Recruit and Hire Better.

Striking a balance between harnessing the power of AI and addressing its challenges is possible. Many are driving that conversation – and you, in human resources, are part of this as well. Your work directly involves human beings, so it makes sense that you want to approach AI ethically as well.

We’ll help you out here. We share examples of how ethical use of AI has been established in various circles, and then we’ll guide you in how to ensure ethical AI standards are met in your own work.

Real-life examples of power and responsibility

Uncle Ben’s famous quote to Peter Parker rings loud and true here: “With great power comes great responsibility.” In that spirit, we have real-life examples of organizations and individuals who are driving the importance of balancing the power of the latest technologies with the challenges they present.

Ethical Intelligence founder Olivia Gambelin is one such example. In a LinkedIn post, she discussed the potential risks associated with generative AI, including security, bias, patenting and more – and emphasized that there’s an opportunity at play here: the opportunity to build an ethical AI framework from the start so that we can maximize the good that we can do with it.

There are also formal organizational and individual projects that have already happened over the last few years – let’s look at three of them right now:

1. IBM: Trusted AI Initiative

IBM made significant efforts to ensure ethical and responsible use of AI through their Trusted AI initiative. In that, IBM has developed AI solutions that prioritize fairness and transparency while minimizing bias.

By establishing a set of guidelines, best practices and tools, IBM ensures that their AI technologies are developed and implemented ethically. Their AI Fairness 360 toolkit, for example, is an open-source library that provides metrics and algorithms to help detect and mitigate bias in AI systems.

That’s more for developers who want to maintain high ethical standards in their AI work. However, it’s a powerful example of a leading brand that values ethical development of groundbreaking technology such as artificial intelligence.

2. Accenture: Responsible AI Framework

Like IBM, leading professional services company Accenture developed a Responsible AI Framework to address the ethical challenges that AI presents.

This framework outlines six core principles, including transparency, accountability and fairness, to guide the development and deployment of AI systems.

Accenture also established a dedicated AI Ethics Committee, pulling together experts from various disciplines to ensure that their AI solutions adhere to these principles and promote responsible AI use across the organization.

3. Dr. Timnit Gebru: Black in AI

Widely regarded AI researcher and ethicist Dr. Timnit Gebru has led the charge of advocating for responsible AI use for years. Her focus is on mitigating bias and ensuring fairness in AI systems – a growing concern with the surge of ChatGPT usage across all disciplines.

As part of her focus on AI bias mitigation, Timnit co-founded Black in AI, which aims to increase the representation of people of color in AI research and development. She continues to play a leading role through her research and advocacy.

Actionable tips for HR pros in ethical AI

Now, how about yourself? If you’re working in human resources, you’re likely already incorporating ChatGPT and other AI tools into your workflow through the automated creation of job descriptions, interview questions and other things.

But there is a risk of relying too much on AI to steer processes as Amazon learned the hard way in late 2018.

Also, diversity, equity, inclusion and belonging is likely a major priority in your work. So how do you combine the undeniable benefits of AI-driven optimization with maintaining fairness, decency and ethics in your work?

You can start right now with these seven focal areas:

1. Prioritize fairness and transparency

It’s likely you have already emphasized the importance of fairness and transparency throughout your organization in terms of communication, opportunity and collaboration. You’ll need to apply that same thinking to your AI systems. Here’s how:

Establish clear evaluation criteria

Develop a well-defined set of criteria for assessing the fairness and transparency of AI systems. This should include considerations such as data quality, explainability and the impact of the AI system on different employee groups.

Vet AI vendors thoroughly

When selecting AI solutions, carefully evaluate vendors based on their commitment to ethical AI principles. Inquire about their efforts to minimize bias, promote transparency and ensure data privacy.

Implement explainable AI

Choose AI systems that provide explanations for their recommendations, allowing you and your team to understand the reasoning behind AI-generated decisions.

Communicate AI usage with employees

Inform employees about the use of AI within the organization and the specific areas where it is being applied. Clearly communicate the goals and benefits of AI, addressing any concerns or misconceptions they may have.

Conduct bias and fairness assessments

Regularly assess your AI systems for potential biases and fairness issues. This can involve analyzing the training data, validating AI-generated decisions, and monitoring AI system performance across different employee groups.

Establish an AI ethics committee

Create a cross-functional team of stakeholders responsible for overseeing the ethical use of AI in your business. This committee should monitor AI implementation, enforce ethical guidelines, and address any ethical concerns that may arise. This team can consist of representatives from different teams including HR, IT, legal, and other relevant departments. That diverse approach is crucial here.

Provide training on AI ethics

Offer training and resources for HR professionals and other employees involved in AI implementation. This can help ensure that your team understands the importance of ethical AI use and is equipped to make informed decisions.

There’s no reason fairness and transparency should exist solely within human-driven processes. Your AI tools can absolutely be fair and transparent as well, but as the manager of those tools, it’s your job to ensure that your technologies don’t fail in this area.

2. Diversify AI development teams

The infamous ‘racist soap dispenser’ is a perfect example of the risks of non-diverse teams when designing products – since they are the brains behind the design and are the first testers of the product.

That thinking applies to AI development teams too. If you’re in the software development field, you want your teams to be diverse so as to avoid design faux pas like the one above. Here’s how you can ensure that diversity thrives where you are:

Expand talent sourcing

Broaden your search for AI talent by exploring diverse channels, such as niche job boards, online communities and professional networks that cater to or specialize in underrepresented groups. Or, if you represent one of those networks or communities, consider building your own branded job board.

Review job descriptions

Ensure that your job postings are inclusive and free of gendered language or other biases that might discourage diverse candidates from applying.

Implement blind recruitment

Utilize blind recruitment techniques, such as anonymizing resumes, to reduce unconscious bias in the hiring process.

Foster an inclusive work environment

Create a workplace culture that values and promotes diversity, equity, and inclusion. This will not only attract diverse talent but also support their retention and career development.

Offer training and development opportunities

Provide training, mentorship and career advancement opportunities to underrepresented employees, helping them grow professionally and contribute to AI development.

Set diversity goals

Establish clear DEI objectives for AI development teams, and track their progress over time. This can help ensure that your organization remains committed to fostering diverse AI development teams and continues to focus on this area going forward.

Diversity may feel like a richly covered topic for many teams, but there’s a reason for that – it’s not just about the teams. It’s about the results of their work – a diverse team means an inclusive software, because unique experiences and perspectives are pulled together into a single production.

3. Regularly audit AI systems

We touched on the importance of setting goals in the last section. You want to be sure those goals are met regularly – to do that, you need a system in place that properly tracks and audits your AI systems so you can jump on any potential biases or unethical processes that your tools may churn out.

Regular audits not only ensure that you’re on top of anything that may happen – they also give you an opportunity to refine your AI implementation strategy to make sure your tools align with your business’ mission, vision and especially values.

Follow these guidelines for a failsafe audit process:

Establish a schedule

Create a regular schedule for auditing your AI systems, based on factors such as system complexity, usage frequency and potential impact on employees.

Define performance metrics

Identify relevant metrics to assess AI system performance, such as accuracy, fairness and explainability. This will help you tangibly evaluate and measure AI systems during audits.

Monitor AI system outputs

Keep a close eye on AI-generated decisions and recommendations, looking for any signs of bias, discrimination or other unintended consequences.

Review training data

Periodically examine the data used to train your AI systems. AI learns from real-life human experience and therefore skews AI-generated decisions – so it’s crucial to ensure that the sourced material itself is diverse, accurate and free of bias.

Engage external auditors

Consider working with external auditors or third-party organizations to conduct unbiased evaluations of your AI systems. The additional layer of scrutiny that this expertise provides can be invaluable.

Implement a feedback loop

Encourage employees to share their experiences and concerns about AI system usage. This feedback is indispensible in identifying potential issues and areas for improvement.

Update and refine AI systems

Based on your audit findings, make necessary adjustments to your AI systems, addressing any biases or performance issues uncovered during the audit process.

Nothing necessarily happens without proper oversight. To ensure that your AI tools and processes run free of bias, implement the above tips so that your company can reap the full benefits of AI in its workflows while mitigating and even eliminating potential risks coming from bias and prejudice.

4. Develop ethical AI policies

Now, you need clear ethical guidelines and policies for your colleagues to follow when they use artificial intelligence in their day-to-day work. Rulebooks mean structure, and structure is crucial to success. Not only do you need to establish these – you also must enforce them, with clear information on potential risks, ethical considerations and especially compliance requirements to ensure that AI is implemented responsibly.

Related: Our AI tool policy template can come in handy here.

Get started with these action items:

Conduct a risk assessment

Evaluate the potential ethical, legal and social risks associated with AI implementation in your organization. Consider factors such as data privacy, algorithmic fairness, and employee impact.

Consult relevant guidelines and frameworks

Refer to industry-specific guidelines, frameworks and best practices for ethical AI. You can check with professional organizations and even government agencies for examples of such guidelines.

Involve stakeholders

In line with the AI ethics committee recommendation above, you can collaborate with multiple stakeholders and leaders from various departments, including HR, IT, legal and executive teams, to develop comprehensive AI policies that address diverse perspectives and concerns. This can include policies unique to specific teams and functions.

Define AI usage boundaries

Clearly outline the permissible and prohibited uses of AI within your organization. Take into account different ethical considerations and regulatory requirements as you do so.

Incorporate transparency and accountability

Ensure that your AI policies highlight the importance of transparency in AI processes and decision-making – and establish clear lines of accountability for AI system performance and outcomes.

Communicate policies organization-wide

Be uniform and thorough in your communications. Share your ethical AI policies with all employees. Provide training or resources to ensure that everyone understands that they have a role in upholding these guidelines – and that they know what they must do to maintain standards.

Regularly review and update policies

Again, tracking and auditing is a must. Review your AI policies consistently to ensure that they remain up-to-date. Adjust accordingly to stay in line with evolving ethical considerations, industry standards and technological advancements.

Ensuring ethical use of AI – and also that the AI you use is in itself ethical and fair – will not happen in a vacuum, nor can it happen simply because you’ve advised your employees and colleagues to do so. You need to prescribe ethical AI throughout your organization and that can only happen with a clear prescription. That’s the value of building guides and policies – not just for AI, but for anywhere.

5. Foster collaboration

The workplace is by nature a collaborative environment. You can work this to your advantage when ensuring that ethical AI practices are consistently implemented and maintained throughout your teams.

Some tips to get you started:

Promote knowledge sharing

Encourage employees to share their expertise, experiences and insights when using AI in their workflows. This can be done via anonymous surveys and in-person workshops to foster a culture of continuous learning and improvement in the area.

Create internal communication channels

Another aspect of sharing knowledge is providing a space for employees to actively discuss AI-related topics in your organization. This can be a new chat channel, an intra-company forum, or even emails and regular meetings, giving employees multiple avenues to voice concerns, share ideas and collaborate on further AI initiatives.

Partner with AI vendors

Since you’re already auditing the AI systems being used in your company, you can also build strong relationships with AI vendors to address any ethical concerns that may arise, You can then optimize and fine-tune your systems to ensure fairness and inclusivity.

Engage with external experts

You can consult with external experts such as Dr. Timnit Gebru and other AI ethicists and industry leaders to gain insights and advice on ensuring ethical AI use and overcoming challenges.

Participate in industry events and forums

Likewise, you can learn from others in the ethical AI space (such as IBM, Accenture and more). Go to industry events, conferences and forums and actively engage in discussions. Learn from other organizations’ experiences and contribute to the shaping of best practices all around.

Again, ethical AI does not happen in a vacuum. Use the existing knowledge that’s out there to your advantage, and also contribute your own experiences. We can’t progress in isolation from one another – a culture of continuous learning through collaboration has tremendous value here.

6. Engage in industry-wide conversations

Following on the above, your peers are likely as engaged in the overall conversation around ethical AI as you are. For example, this LinkedIn post from Caroline Fairchild explicitly expresses concerns around the greater threat of AI on marginalized groups:

When you get involved in these conversations, be it in LinkedIn or at industry events, you can stay informed about best practices and experiences that will shape the future of AI in HR.

Follow these tips to advocate for responsible use of artificial intelligence and contribute to shaping AI policy and regulations as an HR professional:

Raise awareness

Educate employees, management, stakeholders and peers about the importance of responsible AI use. Shed light on the potential risks, ethical considerations and best practices as part of those interactions.

Promote ethical AI champions

Encourage and support employees who demonstrate a strong commitment to ethical AI practices. You may even incentivize them with public recognition and rewards. Empower them to lead the charge as advocates and role models throughout your company.

Collaborate with industry peers

Again, collaboration is huge here. You can network with other HR professionals to share insights, experiences and actionables related to responsible AI use. Your commitment is stronger as a collective than as an individual.

Share success stories

Everyone likes a success story. Those stories are inspirational and informative and deserve celebration. Put a spotlight on moments where your company has successfully implemented AI in an ethical and responsible manner – and more so, show the results and benefits.

When people share knowledge and success stories about those triumphs and accomplishments, that’s powerful information. Equally powerful is sharing challenges with your industry peers and seeking out best practices in overcoming those challenges. That dialogue is crucial to ensuring ethical AI across the board. The reasoning behind a moratorium on AI is understandable, but deeper within that is the call for conversation and understanding. That’s the value of industry-wide conversation.

You can be part of the ethical AI conversation

The primary takeaway from all of this for you as an HR professional is this: establish a culture of continuous learning. AI is growing exponentially and will continue to do so – it’s understandable if you’re struggling to keep pace with all the new developments and information around AI.

When that technology grows and evolves, the orbiting opportunities and challenges will grow with it – and that includes the ethical use of artificial intelligence.

It is crucial for you, as an HR professional, to embrace the opportunities that AI presents while ensuring smart and equitable use of the evolving tech. You don’t want to shy away from it altogether because it does have a place in your work – but you also don’t want it to get away from you either. Striking a careful balance between harnessing the benefits of AI and mitigating potential risks is what you’re aiming to do here.

Be proactive, driven and optimistic as you do so. Look at the real-life examples above – IBM, Accenture, Dr. Gebru, Caroline Fairchild, Olivia Gambelin – they’re all directly contributing to the conversation around ethical use of AI at work and at play. You can be part of that conversation too.

The post Ethical AI: guidelines and best practices for HR pros appeared first on Recruiting Resources: How to Recruit and Hire Better.

That’s, of course, the emergence of ChatGPT, generative AI and LLM AI (large language model AI) and all their many offshoots.

How this will change our landscape is really a huge amount of fodder for another large-scale discussion, but let’s keep it in mind as we dive into the latest data because it will change how we hire.

Let’s get started!

How we’re looking at data

We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.

For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.

As always, we look at the worldwide trends for three common SMB hiring metrics:

• Time to Fill (TTF)
• Total Job Openings (JO) 
• Candidates per Hire (CPH)

Let’s start analyzing!

Main highlights

The three main highlights for this month’s Hiring Pulse are:

• Job activity continues to be high for small businesses
• TTF is continuing to decline sharply – but at what cost?
• CPH is finally ‘stabilizing’ – sort of

1. Time to Fill

For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of March are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.

Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.

Got that? Good. Let’s have a look at the monthly TTF trend throughout 2022 against the average of 2019, based on jobs that have been filled:

Again, we see a decrease in the TTF trend. This is the third consecutive month of decline – and it now stands at 81 for March 2023, down from 87.1 in February and 90.6 in January.

This shortening TTF may initially seem a good thing for both employers and jobseekers. For hiring teams, of course it means you’re finding candidates to fill your much-needed positions quicker than before. For jobseekers, it means you’re getting jobs quicker than before.

There are downsides, too. It may be a sign of a need to fill urgent roles ahead of a looming recession, either for that hire to provide the stopgap that’s needed to carry a company through the downturn. It could also signal a rush to get ahead of potential budget cuts and hiring freezes before they happen. Not inherently a problem, but rather, signals of problems.

But we’re already in April and we’ve been talking about that downturn for a long time now (and in multiple Hiring Pulses). It’s highly likely that the shorter TTF is due to a larger candidate pool – when a job is opened, applications start flooding in and it’s easier to lock in on someone who fits the bill.

All the same, there are caveats to this shorter TTF. Companies may not be taking the opportunity to properly evaluate candidates which means a higher risk of bad hires. That can be expensive down the line and you don’t want that.

So, consider slowing down, even in the face of increased urgency to fill roles.

Or – more apropos – consider better, more optimized ways to evaluate candidates so you can vet them more thoroughly, and quickly too. Like, for instance, incorporating (ahem) AI tech in your hiring process.

Now, let’s move on to job openings.

2. Total Job Openings

Total job openings represent the total number of job openings activated across the entire Workable network.

As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of March.

Well, look at that. Steady growth across the board. Those lines at the bottom of the chart look like a group of airplanes taking off together from November 2022 at different speeds and cadences, and then ultimately falling into line with one another into March.

We’ll get into the specific details in a second, but first, the main takeaway is that the overall average jobs opened per company in March in our dataset is 7.6, up from 6.7 in February and 6.6 in January. At this time last year, we didn’t see such a consistent increase in job openings.

We’ve talked about this in previous Hiring Pulses: a downturn doesn’t necessarily mean hiring freezes for new jobs. It can also mean a recalibration – for instance, let’s look at the restructuring of teams with the objective of producing with 10 FTEs where 15 were able to do so previously.

In such a reworking, job requirements change as a result and new skill sets are discovered to be needed. Some team members can learn and grow, some get promoted, some are disgruntled and leave for other opportunities, some are let go, and finally, entire new jobs are created to fill important gaps in these new team structures.

In times of affluence, these things do happen and they are an opportunity to scale. But in times of fiscal stress, they come up as necessities as businesses clamor to find more efficient ways to carry out processes.

Anyway, interesting discussion and we’ll come back to it. Now let’s look at the company size buckets.

Larger companies still anomalous

Job activity for companies of 200 or more employees saw a roughly 10% increase from February to March. This is interesting compared with previous years, where larger companies saw averages of 15.2/15.9/19.5 for the first three months of 2021 and 21.3/21.3/23.8 for the first three months of 2022.

Yet, this year, instead of a spike in March after a roughly stable Jan-Feb trend, we’re seeing a dip from January to February and then an almost identical recovery from February to March.

Perhaps we’re splitting hairs by looking at the data like this, and perhaps it’s just one of those anomalies, but it’s still interesting to look at.

Medium is steady as she goes

For companies with 51-200 employees, we see a jump in the average job postings for March to 6.2 after a relatively stable January (5.7) and February (5.6).

We noted it last month and the insight remains the same – this is not wholly anomalous. Job activity trends for the first three months of the year is again pretty normal this year for medium-sized businesses.

Small and vibrant

Now, here’s where the interesting stuff is. Small-sized businesses with 50 or fewer employees are continuing to rise in terms of job activity. Last month, we saw a jump from 4.1 to 4.7 jobs per company from January to February, and that growth has accelerated to 5.5 in March.

We’ve talked extensively about agility in small businesses rapidly adapting to evolving economies and shifts in market trends. We’re definitely keeping an eye on this one.

Now, on to the candidates.

3. Candidates per Hire

Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.

Now that Let’s look at what’s going on here through March:

We’ve talked for months about a prominent spike in the number of applicants per job dating back to July 2022. Ultimately, a 56% increase in CPH from July 2022 to February 2023.

But now, apart from a moderate slowdown from November to December (understandable given that December is slow all around), we finally see the CPH trend coming in lower than the previous month.

Not really by a lot, but it’s there: March’s 136.6 is a drop from February’s 141.5.

We discussed the Great Resurgence in last month’s Hiring Pulse – that’s still happening, of course, but the candidate pool is not a bottomless one. Are we finally reaching the crux of this data point? Or is this just a hiccup and more are on the way? We shall see.

What’s going on here?

As the hiring landscape continues to shift and adapt to the ever-changing job market, one thing we know for sure: the use of AI in the hiring process is growing exponentially. While generative AI tools like ChatGPT can provide significant benefits to hiring teams in terms of time and efficiency, they also come with potential risks and drawbacks.

OK, full disclosure: ChatGPT was used to help write that paragraph above with some minor tweaks. However, it’s on point. We’re in a time where we’re now dealing with yet another earth-shattering development on the heels of previous ones – that being the rise of artificial intelligence in the everyday zeitgeist and lexicon. Sure, we’ve been talking about AI for years but until ChatGPT, we hadn’t really thought collectively about how AI fits into our everyday lives at work and at play.

Now, we’re exploring all the ways in which ChatGPT can be used in human resources, and all the ways in which technology can boost hiring processes. At the core of these conversations is optimization of workflow.

So, let’s go back to this month’s data analysis. We’re seeing a shorter time to fill. We’re seeing more job activity. And we’re (still) seeing a lot of candidates for each of those jobs. Combine all three, and understaffed and underfunded hiring teams are just scrambling to get it all done.

ChatGPT is a real boon for those teams, obviously. You no longer have to write those job descriptions (not from scratch, at least). You no longer need to craft lists of interview questions designed to get what you need to know from the candidate. Yes, we have templates for both and more, but that can only go so far. In these rapidly evolving times, we need something that can keep with the times and meet our current needs immediately. Generative AI tech can do that for us.

But (and of course there’s always a but) as teams grapple with these surging trends and developments in the hiring process, it’s crucial to strike that balance between speed and quality. You know the saying, “He/she who hesitates is lost”? And the other, pretty much opposite saying: “Slow and steady wins the race.”

It’s about finding a balance between both. Speed serves a purpose, and so does quality.

Now, we asked ChatGPT what actionable tips it has based on all of the above. It presented the following (without any edits):

Focus on targeted outreach: Instead of simply casting a wide net with job postings, consider a more targeted approach that identifies and reaches out to qualified candidates directly. This can help ensure a higher quality of candidates and reduce the need for rushed hiring decisions.

Implement AI tools thoughtfully: While AI tools like ChatGPT can provide significant benefits, it is important to implement them thoughtfully and carefully, with an eye toward potential risks and biases. Consider involving human oversight in the AI hiring process to ensure that the best possible candidates are being selected.

Prioritize candidate experience: In a competitive hiring landscape, it is important to prioritize the candidate experience, from the application process to the interview and beyond. By providing a positive experience, you can attract and retain top talent, even in uncertain times.

Good work, bot. And ChatGPT even has the insight to recommend caution on using itself. Ultimately, it’s a great tool to help you in your work, but only if you steer it properly and that you maintain that all-important human touch at the end.

As for how AI will change the working world – it will, in absolute, countless spades. It’s not a coincidence or an accident that everyone is talking about it right now. Jobs will change. Workflows will change. The overall interaction of society will probably change.

And will it impact the economy and in turn our three trends of time to fill, job openings and candidates per hire? Yes, it probably will. Let’s watch and find out.

Until next month…

Thoughts, comments, disagreements? Send them to content@workable.com, with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in February!

The Hiring Pulse: Methodology

Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.

To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.

For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.

And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.

The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.

The post Your Hiring Pulse report for April 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

• Tech buy-in and adoption in hiring teams is a challenge for 22.8% of businesses
• The percentage of businesses citing insufficient in-house capacity to hire as one of their major challenges has increased 84.5% since 2020
• And finally – nearly one in five employers (17.5%) say their existing tech stack isn’t enough to meet their hiring needs

This was all before ChatGPT hopped into the ring with great aplomb. Surely, if we carried out the same survey today, all the above numbers would be higher. And as businesses increasingly incorporate more AI tools into their fold, many will find their existing tech stack is no longer enough to meet their needs. Likewise, employees worry that they’ll become redundant.

Plus, many businesses are exercising financial restraint. Technologies that don’t have a clear tie-back to revenue are being dropped like hot potatoes. Employees are being let go. That double-whammy means teams are limited in their capacity to stay on top of work – including in hiring.

That’s not supposed to bring you down, however. Stay with us here, and let’s go a little deeper:

Gartner’s Senior Director Analyst, Sandy Shen, said this about surviving the pandemic as a business:

“Businesses that can shift technology capacity and investments to digital platforms will mitigate the impact of the outbreak and keep their companies running smoothly now, and over the long term.”

“Businesses that can shift technology capacity and investments to digital platforms will … keep their companies running smoothly now, and over the long term.”

In other words, Jack be nimble, Jack be quick. That same sentiment rings even more true now – businesses that move quickly to AI-driven tech capabilities will stay ahead of the curve especially during these recession-prone times.

We’re seeing rapid adoption already, with a ResumeBuilder survey finding half of all companies are already using ChatGPT and 93% of current users say they plan to expand their use of this savvy AI tool.

Take on that optimistic spirit of early adoption of the tech – not just ChatGPT, but all the AI and digital developments happening in the hiring space – and you’ll see a vastly improved hiring process at a time when your business most needs it.

The evolution of AI in hiring

But what exactly is changing in hiring? A lot, as it happens. ChatGPT is already being used extensively to auto-write job descriptions, interview questions, and many other elements of the hiring process that at one time required a human to create. You’re still the driver, however, and there are many elements of hiring that you can drive with the support of AI.

With that in mind, let’s look at some fundamental aspects of recruitment and the ways in which they’re being digitally transformed.

1. Sourcing and outreach

The rise of advanced search tools, AI-driven algorithms, and automation has expanded the ability to identify and target top candidates. To stay ahead, learn to leverage these technologies effectively, engage with emerging niche platforms, and build meaningful connections with candidates through online communities.

Some of the tech advances in sourcing include:

AI-based candidate matching

Platforms are utilizing artificial intelligence to analyze job descriptions and match them with the most suitable candidates from a large database. Workable’s AI Recruiter, for example, can build a list of top passive candidates for your job openings utilizing our data intelligence gathered from hosting 160 million candidates in 1.5 million jobs.

Programmatic job advertising

AI-powered programmatic job advertising platforms help you target and attract the right candidates by distributing job ads across various online channels. These platforms analyze real-time data to make intelligent decisions on where and when to post job ads, optimizing budget and reach.

Recruitment chatbots

Chatbots help automate initial candidate interactions, answering questions, and pre-screening candidates. These chatbots can engage candidates 24/7, collect necessary information, and schedule interviews, freeing up time for more high-touch interactions.

Talent pooling and candidate rediscovery

AI-powered platforms allow you to tap into existing talent pools by rediscovering candidates who have applied for previous positions. By analyzing candidates’ profiles, these platforms can identify potential matches for new job openings, reducing the time and resources spent on sourcing. A good example is Workable’s Resurface Candidates tool, which does exactly this.

2. Screening and assessments

Technology can revolutionize the way you assess candidates’ skills, experiences, and cultural fit. AI-powered tools and gamified assessments offer more efficient and engaging methods of evaluation. Hiring team members must stay up to date with these tools and ensure they comply with privacy regulations to maintain candidate trust.

Some of those tech advances include:

Pre-employment assessments

Hiring teams are increasingly utilizing pre-employment assessment tools, such as Criteria Corp and Workable Assessments, to measure candidates’ cognitive abilities, personality traits, and job-specific skills.

These assessments help to streamline the screening process and identify candidates who are more likely to be a good fit for the role and company culture.

Gamified assessments

Gamification has been incorporated into the assessment process to create a more engaging experience for candidates. Tools like Pymetrics and Arctic Shores utilize game-based assessments to evaluate cognitive abilities, problem-solving skills, and personality traits.

These provide a fun and interactive way to measure candidates’ fit for a role, while also collecting valuable data to support hiring decisions.

Skill tests and coding challenges

Companies use platforms such as HackerRank and Codility to administer skill tests and coding challenges, allowing candidates to demonstrate their technical abilities in real-world scenarios. These tools enable you to objectively assess candidates’ skills and compare them against established benchmarks.

Virtual reality assessments

Virtual reality (VR) technology is being utilized in the hiring process to assess candidates’ skills and aptitudes in immersive, simulated environments. Talespin and Immerse, among others, are VR-based assessment tools that test candidates’ decision-making, teamwork and communication abilities in realistic scenarios.

Automated reference checking

Automated reference checking platforms such as SkillSurvey and Checkster streamline the reference checking process by collecting feedback from a candidate’s professional contacts. These tools use AI algorithms to analyze the feedback and generate detailed reports, supporting hiring decisions.

3. Virtual Interviewing

Virtual interviewing tools have become increasingly popular, providing valuable insights through AI-powered analysis. Through these technologies, whether carried out synchronously or asynchronously, hiring team members can make more informed decisions about candidates.

Asynchronous video interviews

Asynchronous video interviews enable candidates to record their responses to pre-set interview questions at their convenience. Platforms like Workable’s Video Interviews allow you to review and assess these recorded responses on their own time, streamlining the interview process and eliminating scheduling challenges.

Then, AI-driven analysis of these interviews can help you identify key soft skills and communication abilities – more on that below.

Synchronous video interviews

Real-time video interviews conducted through platforms like Google Meet, Zoom, and Microsoft Teams became increasingly standard during the pandemic. These virtual meetings provide a cost- and time-effective alternative to in-person interviews while still allowing for real-time interaction between the interviewer and the candidate.

AI-driven video interview analysis

AI-based platforms can analyze recorded video interviews to assess candidates’ soft skills, communication abilities, and other attributes. These platforms use natural language processing and machine learning algorithms to evaluate candidates’ responses, providing you with valuable insights and data-driven recommendations.

Likewise, AI-powered transcription services such as Supernormal can then be used to transcribe, analyze and summarize these interviews, providing you with valuable insights and data points for further evaluation.

AI-based sentiment analysis

AI-driven sentiment analysis tools can evaluate the tone, emotions, and sentiment expressed by candidates during video interviews. These insights help you to better understand candidates’ communication styles, emotional intelligence, and cultural fit.

Platforms like RingCentral and IBM Watson can integrate with video interviewing tools to provide real-time sentiment analysis during virtual interviews.

Facial and voice recognition

Advanced facial and voice recognition technologies are being utilized to analyze non-verbal cues and vocal characteristics during video interviews. Realeyes and VoiceVibes are two such tools that can help you identify key traits and behaviors that may not be evident through traditional interviewing methods, offering a more comprehensive assessment of the candidate.

Virtual interview coaching and feedback

AI-driven coaching tools provide candidates with feedback on their interview performance, identifying areas for improvement and offering personalized guidance. This helps candidates to refine their skills and better prepare for future interviews, while also providing you with a slicker pool of applicants. InterviewStream and MyInterview are two such examples of this technology.

4. Onboarding and beyond

The onboarding process is also evolving rapidly, with virtual onboarding tools and personalized experiences driven by data analytics and AI.

Digital onboarding platforms

Cloud-based platforms like BambooHR and Talmundo enable companies to centralize and streamline the onboarding process. New hires can access essential documents, complete paperwork, watch training videos, and connect with team members—all from a single platform.

These tools allow HR and managers to track progress, ensuring that new employees complete required tasks and receive necessary support during their initial weeks.

Virtual onboarding events

As remote work and distributed teams continue to gain traction as a standard in the workplace, companies are increasingly hosting virtual onboarding events to welcome new hires. Organizations use video conferencing tools to conduct virtual meet-and-greets, team-building exercises, and training sessions to help new employees feel connected and engaged from the start.

Personalized learning paths

AI-driven learning management systems (LMS) like Docebo and Cornerstone can create personalized learning paths for new hires based on their roles, responsibilities and skill sets.

By leveraging AI and data analytics, these systems can track progress and adapt training content to suit individual needs, ensuring that new employees are equipped with the necessary knowledge and skills for their roles.

Employee onboarding chatbots

AI-powered chatbots like Talla can assist new hires during the onboarding process by answering common questions, providing relevant information, and guiding them through required tasks.

These chatbots can be integrated into workplace communication platforms like Slack or Microsoft Teams, offering real-time support and minimizing the need for new employees to contact HR or managers for help.

Social and collaborative learning

Digital tools like 360Learning and Degreed foster social and collaborative learning experiences for new hires. These platforms allow employees to share knowledge, ask questions, and collaborate on projects, enabling new team members to learn from their peers and build relationships within the organization.

The future of hiring tech

That’s a lot of tech already. But there’s more on the horizon – and ChatGPT and its cousins are really only at the cusp of it. Let’s look at the various other ways in which digital transformation of recruitment is continuing to grow:

Advanced AI-driven candidate matching

AI algorithms are growing to the point where they can predict the success of a candidate within a company based on data analysis of past employees’ performances. This could significantly improve the quality of hires and streamline the recruitment process, allowing you to focus on the human aspects of your role.

Virtual reality interviewing and onboarding

Virtual reality (VR) technology is already revolutionizing the hiring process. Candidates can be immersed in a virtual work environment, interacting with potential colleagues, and participating in real-life work scenarios before they even get the job. This provides you with valuable insights into a candidate’s ability to adapt and perform in their new role.

Augmented reality (AR) enhanced job previews

Likewise, augmented reality can be utilized to give candidates a more immersive preview of their potential work environment, from their desks to the company’s facilities. Candidates can use their smartphones or AR devices to explore their future workplace, interacting with digital information about company culture, benefits, and team structures.

This would allow candidates to make more informed decisions about accepting job offers and help you identify candidates who are genuinely excited about joining the company.

Blockchain-based credential verification

Blockchain technology can play a significant role in recruitment by streamlining the verification of candidates’ credentials, such as education, certifications and work experience. By using a decentralized, secure and tamper-proof system, you can quickly and accurately validate the qualifications of candidates.

This reduces hours spent on background checks and minimizes the risk of fraudulent claims.

Remote workforce management through IoT

The Internet of Things (IoT) could play a vital role in managing remote workforces, as companies increasingly adopt flexible and remote work models. IoT devices and wearables could be used to monitor employee health, productivity, and engagement in real-time, providing valuable insights. This data could be used to create personalized support plans for employees, addressing their unique needs and preferences.

There’s plenty more, of course, but that’s just a taste of what’s happening now and in the near future.

Lessons from Michelangelo, Borg and Ford

Let’s step out of that tech rabbit hole for a moment, and consider some real-life lessons to help assuage fears that jobs will be taken over by artificial intelligence including in hiring teams. The reality is, AI can be your friend if you embrace it.

Michelangelo and the Sistine Chapel

First, let’s look at one of history’s great painters and one of history’s equally great paintworks. While Michelangelo is famous for his work on the Sistine Chapel, he did not complete the masterpiece alone. He had a team of assistants to help him bring his vision to life. He consulted with them, worked with them to prepare the “canvas”, and so on. He still led the project and directed his teams to set the foundation for what ultimately became his masterpiece.

Likewise, for you, AI can be your assistant. It’ll take care of the other work and help you focus on the human aspects of your role, including fostering a positive candidate experience and ensuring that your teams are highly engaged.

Bjorn Borg and the wooden racket

When tennis legend Bjorn Borg made a comeback in 1991 after years in retirement, he chose to stick with his wooden racket rather than adopting the modern graphite rackets that had become the standard in the sport. His insistence on staying with outdated technology led to disappointing (and even embarrassing) results.

This is a reminder to stay up-to-date with – and ahead of – the latest technologies and trends in your area of work. If you don’t stay on top of your game, you’ll fall behind and miss out on top talent.

Henry Ford and the assembly line

Car titan Henry Ford revolutionized the manufacturing industry with his innovative assembly line, which dramatically increased efficiency and reduced production costs. Ford took inspiration from meat-packing plants and a grain mill conveyor belt to divide the labor into clear steps and to bring the work to the workers, thereby reducing time wasted in moving around and leading to mass production and cheaper cars.

Likewise, you can explore and adopt new technologies that can optimize your workflow and save you an incredible amount of time and hassle – and money.

AI isn’t a threat – it’s your ally

SWOT analysis is a common element of business strategy. Strengths, Weaknesses, Opportunities, Threats – hence, SWOT. Think about what you’re doing at work, and what your company’s doing. What are your strengths right now? What are your weaknesses? And what are the opportunities you can capitalize on to overcome those weaknesses?

The fourth one – the threat – is probably overplayed when it comes to AI. The infusion of AI in hiring need not be seen as a threat to the profession, but rather as an opportunity for growth and enhancement.

Don’t forget that the human touch continues to be a vital aspect of the hiring process, and AI technology is the tool to support and streamline your efforts.

It’s an exciting time. Embrace this age of digital transformation, including in hiring. Learn from the successes of Michelangelo and Henry Ford, and the failure of Bjorn Borg, and navigate this new road. The future of hiring sits squarely in the harmonious blend of technology and human skill. Master that balance, and you’ll do very well.

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1. Write job descriptions

This may seem ridiculous to use a bot for – after all, you want to describe the job you need to be done, not just a generic job! But the reality is most job descriptions are terrible at describing the actual job.

Why? The people who write them (managers and recruiters) don’t actually do that actual job!

ChatGPT shouldn’t be copied as is, but it can give you a starting point. It may include some important things that you wouldn’t normally think to include. For instance, I asked ChatGPT to write a job description for an entry-level accounts receivable clerk and got this:

Job Title: Entry Level Accounts Payable Clerk

Job Summary: We are seeking an entry level accounts payable clerk to join our accounting department. The ideal candidate will be responsible for the timely and accurate processing of invoices and payments, ensuring compliance with company policies and procedures. This position will report directly to the Accounts Payable Supervisor and will work closely with other members of the accounting team.

Key Responsibilities:

• Receive and process invoices from vendors, ensuring accuracy and completeness of information
• Code and enter invoices into the accounting system
• Ensure timely and accurate processing of payments to vendors
• Resolve any invoice discrepancies or issues with vendors in a timely manner
• Reconcile vendor statements and resolve any outstanding balances or discrepancies
• Communicate with other departments to ensure accurate recording of expenses and proper authorization for payments
• Assist with month-end close activities, including preparing accruals and reconciling accounts
• Maintain accurate and complete records of all accounts payable transactions

Requirements:

• High school diploma or equivalent; some college coursework in accounting preferred
• Prior experience in accounts payable preferred but not required
• Strong attention to detail and accuracy
• Excellent organizational and time management skills
• Strong written and verbal communication skills
• Proficiency in Microsoft Excel and other accounting software
• Ability to work independently and as part of a team in a fast-paced environment
• Willingness to learn and take on new responsibilities as needed

This is an entry level position with opportunities for growth and advancement within the accounting department. If you are a highly motivated individual with a passion for accounting and a desire to learn, we encourage you to apply.

Takeaway: ChatGPT is a starting point, not an ending point. It will not write everything perfectly for you, and you still must edit.

2. Help to summarize complex documents.

When you are trying to understand a document from the EEOC or a court case, ChatGPT can give you a good summary. For instance, I asked for an overview of the EEOC’s Draft Strategic Enforcement Plan as it relates to talent acquisition. It gave an excellent summary:

The Equal Employment Opportunity Commission (EEOC) proposed new guidelines, outlined in the Draft Strategic Enforcement Plan, could impact talent acquisition in several ways.

First, the plan prioritizes addressing issues such as systemic barriers to equal employment opportunities and discriminatory practices in the hiring process. This could lead to increased scrutiny of hiring practices and a focus on ensuring that they are non-discriminatory and fair.

Second, the plan emphasizes the protection of workers in industries that are rapidly changing or expanding, such as technology. Talent acquisition practices in these industries may need to be re-evaluated to ensure they are not discriminatory.

Finally, the plan also highlights the need to address emerging and developing issues in equal employment, such as discrimination based on sexual orientation and gender identity. Talent acquisition practices may need to be adapted to comply with these new protections and avoid potential legal action.

In summary, the EEOC’s proposed guidelines could impact talent acquisition by promoting non-discriminatory practices, protecting workers in rapidly changing industries, and addressing emerging issues in equal employment.

Great, right? But be careful. ChatGPT just makes stuff up if it doesn’t know.

For example, I asked it to give me a summary of this recent court case on employees’ reproductive rights. Here’s the response:

Certainly! Here is a brief summary of the court decision in question:

The court upheld a lower court ruling that the New York State law prohibiting the possession and sale of stun guns violates the Second Amendment of the United States Constitution. The court found that stun guns are “bearable arms” that are commonly used for self-defense, and therefore are entitled to Second Amendment protection. The court also rejected the argument that stun guns are “unusual” weapons that fall outside the scope of the Second Amendment.

The decision has implications for New York State, as it may require the state to change its laws related to stun guns. However, the decision may also have broader implications for other states that have similar laws prohibiting the possession or sale of stun guns, as they too

You’ll notice it ends without a complete sentence. That’s because I stopped it because this has absolutely nothing to do with the case at hand. The case actually involves an employer who argued they could take adverse actions against an employee for their reproductive rights decisions. Not a thing to do with guns.

So, while it can be good to summarize things, much like a high school senior, it will just make stuff up if it doesn’t know. An AI bot needs to learn things, and a brand new court case hasn’t been around long enough for it to learn.

Takeaway: You can use ChatGPT to summarize things, but be careful and double-check! If it’s something you know nothing about, this is probably not the best place to start.

3. Helps neurodivergent people

Brenda Neckvatal, Human Resource Professional and e-Commerce Entrepreneur, has dyslexia. That hasn’t stopped her career one bit, and she’s even become a bestselling author. She’s found ChatGPT to be super helpful.

“As a dyslexic person, I find it difficult to accurately compose written text. AI can help me write more effectively by providing me with tools that can check my grammar, spelling, and syntax,” Brenda says.

“AI can also suggest words, phrases, and sentence structures that I may not have thought of, which can help me create clearer, more concise writing. Additionally, AI can help me find more appropriate resources for research, allowing for more accurate and informed writing. With AI, I can write more effectively and efficiently and with much more confidence.”

That’s not the only way someone who is neurodivergent can use this AI tool.

Members of Reddit’s /r/autism group discussed the benefits of ChatGPT for people with autism.

Here are some excerpts from that discussion:

“Being a learning language model, the software can help with just about anything, and I know many people have found it great with assignments for high school/college, myself included.”

“But I have been using it more recently like it is a small neurotypical brain in my phone. Not only can I run social scenarios through ChatGPT, but it’ll talk with [me] about my special interests for hours without getting bored.”

“The software has continually provided great advice on tricky social situations, reminders, and positive reinforcement in my day-to-day activities. It can even give you encouragement/motivational messages.”

“Maybe it’s the technology nerd in me, but I love ChatGPT, it’s free and I don’t think it’s being discussed how helpful this software is for people on the spectrum.”

That’s a massive benefit for HR and employees alike.

Takeaway: Think of it as a translator. ChatGPT can help you write out things you’re uncomfortable with.

4. Personal assistants

Every HR person would love a personal assistant, but what company has the budget for that?

Director of People Support Robert Jumalon said he uses ChatGPT as a personal assistant. The tool figured out how to set up e-signatures and gave instructions for his existing systems, gave step-by-step instructions for filing a legal complaint, and other things. Jumalon is just starting to use it and is excited about it.

But could there be more? Combining ChatGPT with a bit of Python programming can take over a wide variety of tasks that a personal assistant would originally be able to do.

According to Artificial Intelligence in Plain English contributor “Ordinary Programmer”, here are a few of things it could do for you.

• Scheduling appointments and setting reminders
• Answering questions and providing information on a wide range of topics
• Finding and booking travel arrangements
• Making recommendations on books, movies, and other forms of entertainment
• Helping manage finances, such as tracking expenses and budgeting

You say that’s all fine and good, but you don’t know Python, and again, there’s no budget. Well, he also gives the instructions.

Think of the benefits of a recruiter using AI to schedule appointments! That alone could save hours of tedious work, putting the recruiter’s skills to better uses.

Takeaway: Don’t limit yourself. See what ChatGPT can do for you!

5. Helps you be more creative

Creativity is hard work. Anybody who tells you otherwise is probably not very creative, and HR people are often called on to find creative solutions to problems. Brainstorming, list making, and figuring out how to handle a problem employee are all things ChatGPT can help you with. I asked it about icebreakers for HR people and got this response:

Sure, here are a few icebreakers that HR professionals might find useful:

• Two Truths and a Lie: Have each person share two true statements about themselves and one false statement. The others in the group must guess which statement is false.
• Name Game: Have everyone introduce themselves and share one interesting fact about themselves that begins with the same letter as their first name.
• Group Juggle: Have everyone stand in a circle and toss a ball or object to each other. Each time someone catches the object, they must say the name of the person they are throwing it to. After everyone has caught the object once, add a second object and repeat the process.
• Personal Scavenger Hunt: Create a list of characteristics or experiences, such as “Has traveled to more than five countries” or “Has a pet.” Have everyone circulate and try to find someone who matches each characteristic.
• Speed Networking: Set up a series of two-minute conversations where each person has the opportunity to introduce themselves and share their professional interests.

Remember, the goal of an icebreaker is to help people get to know each other and feel more comfortable, so be sure to choose activities that are appropriate for the group and the setting.

If you’re stuck and out of ideas, ask it a question:

What are five ways to help a new employee who doesn’t seem to fit in?

It can be challenging for a new employee who doesn’t seem to fit in, but here are five ways to help them feel more comfortable and welcome:

• Assign a Buddy or Mentor: Pair the new employee with a buddy or mentor who can show them the ropes, answer questions, and introduce them to other colleagues. This can help the new employee feel less isolated and more connected to the team.
• Set Clear Expectations: Make sure the new employee knows what is expected of them in terms of their job duties, goals, and company culture. This can help them feel more confident and less uncertain about their role.
• Provide Feedback: Regularly check in with the new employee to provide feedback on their performance, progress, and any areas for improvement. This can help them feel supported and motivated to succeed.
• Encourage Social Interaction: Create opportunities for the new employee to interact with other team members, such as group lunches or team-building activities. This can help them form relationships and feel more included.
• Be Patient and Understanding: Recognize that it can take time for a new employee to adjust to a new job and workplace. Be patient and understanding, and offer support and encouragement as they navigate the transition.

Overall, the key is to be proactive in helping the new employee feel welcome and supported, and to create a positive and inclusive work environment for all team members.

This type of brainstorming can help you get started when you’re stuck. And it can make things fun as well.

Obviously, this is far more exciting than a regular company picnic invitation. (Note to Workable employees – I just made this up. It’s not an actual event!).

I entered this as a prompt: “Please write a poem in the style of Dr. Seuss inviting the employees at Workable to a summer picnic. It will be held at 12 p.m. on June 7, 2023 at Boston Common. Partners and children are invited. No pets, though.”

This was the result:

Oh, Workable team, listen up, do!

We have a picnic planned just for you!

On June 7th, at noon on the dot,

We’ll gather at Boston Commons, a perfect spot!

Bring your partners and bring your kids,

We want everyone to come and have some fun, we insist!

But leave your pets at home, oh please,

For safety’s sake and everyone’s ease.

We’ll have food and games galore,

And plenty of chances to chat and explore.

So mark your calendars, don’t delay,

And let us know if you’ll be joining us that day!

We can’t wait to see you there,

With your picnic blankets and your flair!

We’ll make some memories that’ll last,

And have a blast, blast, blast!

So come one, come all, and let’s unite,

For a Workable picnic that’ll be just right!

Takeaway: Let ChatGPT help you get those creative juices flowing! It can make a huge difference.

There are a million other things that it can do, and we’re just learning the beginnings. Just remember, ChatGPT is not perfect, and it is biased. (You are too, but it has a problem recognizing its own bias.) It’s a tool, not the solution to everything. It definitely doesn’t replace humans, and it sometimes lacks good sense. But give it a try!

The post What can ChatGPT do for HR? appeared first on Recruiting Resources: How to Recruit and Hire Better.

Taking advantage of a larger talent pool

The COVID-19 pandemic ushered in a new era in terms of workplace norms. The pandemic proved, for the most part, that geography is irrelevant when it comes to hiring. The technology developed and deployed to allow employees to work from home during COVID now allows tech professionals to do their work from any location.

In short: Thanks to COVID and the changes it inspired, it doesn’t matter if your programmer lives in California, Cambodia, Chicago, the Cayman Islands, or Cameroon.

In addition to having more options available when it comes to prospective employees, the new landscape also allows employers to use labor arbitrage to build a more cost-efficient workforce. Hiring an engineer in the US may cost a company $200,000 a year, whereas an equally skilled engineer based in India can do the same work for $56,000 a year.

When adjusted for the cost of living in each engineer’s location, the compensation is equivalent and the company receives the same volume and quality of work. This represents an opportunity for significant savings for tech companies.

Salary based on location vs. salary based on value is a topic of debate. Read the Evil HR Lady’s take on this.

Identifying top talent released in layoffs

Layoffs are another development adding opportunities to the talent pool. Typically, big technology companies stack rank their employees on an annual basis, which involves rating employees based on their performance. When layoffs happen, it is most often those perceived to be the lowest performers or contributors who are let go. In recent years, however, tech companies have both overhired and held on to weaker talent due to labor shortages and lower employee productivity.

As 2022 came to a close, shifts in the US economy created an environment with high levels of inflation, high levels of interest rates, and a softening housing market. There has also been an inverted yield curve in the 10 year-3 month Treasury Yield Spread, which has historically signaled an impending recession. These developments have triggered major tech players like Microsoft, Amazon, and Google to launch layoffs.

While some of the technology professionals now available for hire were let go due to low performance in their past roles, others are out of work as a result of overhiring in the tech field in recent years. In some cases, tech companies closed entire divisions to trim their staff size, sending many seasons and highly capable professionals into the talent pool. This means companies have a phenomenal opportunity to hire top performers in 2023, provided they choose carefully.

Boosting productivity with new technology

Artificial intelligence (AI) is causing a huge stir in the tech space as we move into 2023. Microsoft, which laid off 10,000 workers to start the year, also invested $10 million in the ChatGPT AI platform in early 2023.

Why? Because the AI-based language model chatbot, which is still in its infancy in terms of development, can code, automate, configure tech, and find problems with software, among other things.

In some cases, AI-driven tools like ChatGPT can take the place of hands-on tech workers. In others, technology professionals equipped with AI-driven tools can deliver as much as 10 times the output of those working without AI. Employers who commit to leveraging AI tools stand to gain considerably in terms of increased productivity.

Targeting talent with business savvy

There was a time when those who could support technology were in high demand. That time has passed. Not only is today’s tech more reliable, but AI-driven solutions promise to provide the support that tech workers once delivered. As a result, the most valuable tech workers will be those like cloud architects and enterprise architects who understand how technology can be used to solve business problems.

Tech companies hiring in 2023 should be looking for employees who can provide more than technical expertise. Professionals who bring business acumen, leadership skills, sales skills, executive presence, and emotional intelligence will prove to be those who can thrive in their positions and add value to the company.

They have what it takes to go beyond working with technology to design solutions that can improve business performance and transform organizations.

The post Tech hiring: how it’s different now for employers in 2023 appeared first on Recruiting Resources: How to Recruit and Hire Better.

These tasks were things that most of humanity (except computer programming) had to do to keep fed and clothed. But we automated and outsourced so many tedious tasks, we now have time for fun things.

It’s highly possible that you can eliminate many of your hated job tasks as well.

For some of you, that would reduce you to strictly payday, but for most people, there are a lot of things you like about your job, and if you could just get rid of the few annoying things, life – and working life, especially – would be better.

What tasks serve little to no value?

How often do we do things because they have always been done that way? Do you generate reports that get sent to people who rarely, if ever, open them? Do you have a weekly staff meeting that could be an email?

To find out, survey your employees. Ask them to name three tasks or meetings that can be eliminated or reduced in frequency. Using a number is crucial because it sets a boundary. Without a limit, you’ll end up with a list of 153 things, most of which can’t be eliminated, or nothing because people can’t think of anything. By specifically requiring three things, you’re more likely to get your employees thinking and receive reasonable responses.

Then take the time to look at these tasks and determine if you can eliminate them. Some of them may be useless to the business’ success but are still required for legal reasons. Some of them are needed, but perhaps differently.

But, you will find things that can go away. And you can remove them from the workplace.

What tasks can you automate?

We’ve automated everything! Have we, though?

If you asked your ancestors, they would never have dreamed of a magical machine that washed their clothes for them or kept their house at a constant temperature. That same thinking applies to today’s world.

Look at ChatGPT. A few weeks ago, this didn’t exist. But have you figured out what it can do for you?

For instance, I asked it this simple question and got a helpful list:

What are ten office tasks that people think they have to do but can be automated?

1. 1. Email management (filtering, sorting, responding)
   2. Scheduling and calendar management
   3. Data entry and processing
   4. Document creation and formatting
   5. Invoicing and billing
   6. Financial reporting and analysis
   7. Customer relationship management
   8. Human resources management
   9. Marketing and sales reporting
   10. Supply chain management and order tracking

Can any of this stuff be automated? Maybe. New systems do appear all the time. There could be something cost-effective that can automate some of your work. In fact, what it can do for you is enough for a whole separate article.

So let’s focus on the overall topic: eliminating tasks from the workplace. Here are some options for you:

1. Hire a robot

What? Who needs a robot? You do.

Maybe. After all, I have a robot that vacuums my floor, and Boston Dynamics now has a robot that does this:

Boston Dynamics’ humanoid robot Atlas demonstrates its ability to move objects of different sizes, materials, and weights as it shows off its new skills pic.twitter.com/Av8sSdo2ID

— Reuters (@Reuters) January 19, 2023

Surely, that’s not going to be a cheap option for anyone, but when you think of automation, don’t forget about machines that can and will do things for you. We use machines so often that we don’t remember that many of them can be called robots.

Remember: “A robot is a machine – especially one programmable by a computer – capable of carrying out a complex series of actions automatically. A robot can be guided by an external control device, or the control may be embedded within.”

Your Alexa that you can ask politely to “Add grapes to the shopping list” can also “Schedule a meeting with Bob at 2 p.m. Tuesday,” and “Set a reminder at 3 to review invoices.” It’s a robot, even if it doesn’t resemble Rosie from the Jetsons.

I’m a fast typer, so typing makes sense for me, but if you’re not, a voice-to-text function edited by Grammarly and translated by Deepl may be just what you need.

2. Outsource tasks you don’t like

Have you checked Upwork lately? You can hire people to do just about anything. Why are you cleaning your own toilets when hiring a cleaning company may be cost and time effective? If you hate writing blog posts, stop it, and hire an expert who likes doing that.

What about marketing plans? If you’re not good at that, outsource it. Yes, outsourcing costs money, but you need to look at opportunity cost as well – what could you be doing if someone else was doing the thing you hate?

3. Watch out for task creep

When you eliminate, automate, or outsource a task, it can be tempting to bring more work in to replace it. But that can be work you don’t need.

For instance, think of all the reports you do that no one would have ever attempted before Excel appeared on the scene. Some of that is helpful, but some are simply because nature abhors a vacuum, and something fills it when you have more time.

Be careful about adding new systems to the overall workflow. Make sure they add to the success of the business and actually solve the problem at hand (such as reducing task burdens). Focus on the good parts and things you’re good at and see things improve.

Don’t worry about running out of things to do

When I was straight out of school, I got a temp job at a real estate management company. My job was to put together this report that involved a lot of calculations. I had never really used Excel before (this was – gulp – 25 years ago), but I knew it existed and I knew it could do basic calculations.

Within a week, I learned enough Excel to fully automate the report, and, well, I worked my way out of a job.

But that’s OK because it allowed me to land an HR career, which I was much better suited for.

And while automation does eliminate some jobs, this isn’t something you should be worried about. Chances are your skills can be put to better use elsewhere, and it’s unlikely that you were hired to do one repetitive task.

Freeing up time means you can now use your brain for the things only a human can do. If you can let a robot edit your grammar and outsource your PowerPoint slides to an expert who can do them in a quarter of the time it would take you. That allows you to work on things that really matter.

And that’s what’s important and the reason you want to eliminate tasks. There’s always more to do in a day than you have time for. Getting rid of the things you hate (or even just the things you aren’t good at) opens you up to so many more opportunities for success.

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Engineers who build AIs need data to train the machines, and they also need more information to determine what works or not. And this is where organizations can contribute because they have access to data and they’re in a position to actually test technology in the field.

This topic was part of my conversation with Matt Alder, the reputable British HR thought leader and host of the Recruiting Future podcast. During an hour-long phone conversation, we discussed possible actions on how businesses can play their part in shaping a world using powerful recruiting AI tools.

See also our discussion on the state and future of AI in recruiting and whether machines can really take recruiters’ jobs.

Technology in our own image

The data we use to train our machines is essential to a successful AI-driven recruitment strategy. If the data is inaccurate, incomplete, skewed or one-dimensional, the machine’s “intelligence” will suffer.

So, we need to choose our data carefully. This is tougher than it sounds because sometimes we don’t even realize we’re looking at biased or incomplete data samples. Because we’re only human, we have inherent difficulties to identify our own shortcomings and the wrong data causes machines to replicate our biases, opinions or behaviors. The old adage of “garbage in, garbage out” applies readily here.

One example is the apparent apathy, evasion, or occasional positive response of virtual assistants Siri and Alexa when faced with verbal sexual abuse from users. They were programmed to respond in certain ways to various forms of harassment that human creators might have thought were “OK” (they’re not). This is something companies that make these AIs are trying to tackle, as Quartz reported.

In the recruiting world, automated tools don’t make final hiring decisions, so how much does bias matter? There’s an interesting caveat here. Matt discussed this in a recent Recruiting Future podcast when he interviewed Miranda Bogen from Upturn, a non-profit think tank promoting equity and justice in the design and use of digital technology.

Upturn recently published a report on the bias of hiring algorithms. Based on that report, Miranda explained that, while AI in recruiting doesn’t decide who gets hired, it can decide who won’t get hired – and that may often be people with certain characteristics. An example of this is Google’s algorithm which showed ads for higher-paying jobs to men only because it thought men were the most likely to click on these jobs. This way, it effectively precluded women from learning about these job opportunities. Upturn’s report also mentions that this bias persists even if you obscure attributes like gender and race when training machines. That’s partly because the datasets we have available are inherently correlated with systemic biases.

So there’s a legitimate philosophical question: could we really create technology that doesn’t replicate our limitations and biases? Well, we have done so in other branches of tech: for example, our naked eye can’t see details far away in space, but our telescopes can. Intelligent machines could work the same way – complementing and enhancing our abilities.

How we can do that is less clear. Matt reflects on this:

“I think this is perhaps the biggest dilemma over the next few years; how do we actually make technology be better than humans?”

When humans are the designers, therein lies the challenge.

We need to go smarter

As Matt emphasizes, the first step in building machines for purely objective rather than subjective recruiting processes is to consciously understand our own biases. That not only involves the ‘what’, but also the ‘how.’ “If we’re going to make HR technology that doesn’t share human bias,” says Matt, “then we need to understand more about where that kind of bias comes in.”

Recruiting professionals are probably in the best position to identify these issues in the hiring process. Monitor your hiring metrics for patterns. Gender and race bias, for example, can be identified by measuring the percentages of female or non-white applicants who apply and are moved through the hiring process. Also, regularly communicate with your hiring teams about what criteria they use to make decisions, and be on the lookout for criteria that aren’t strictly job-related.

Once you have started collecting this type of data and insights, make a systematic effort to mitigate biases wherever they appear. For example, you could try out more objective hiring tools, like structured interviews, and train your interviewers to overcome their unconscious (and occasionally conscious) prejudices.

Also, it’d be useful to participate in the discussion with fellow recruiters in forums or in person to exchange information about existing biases and possible strategies to deal with them. Our collective knowledge and awareness of biases can help companies that make AI in recruiting tools design their products more effectively.

We also need variety

When it comes to AI in recruiting, one of the problems is that the data we’ve used hasn’t been very creative, as Matt points out:

“I think the problem is we still work off CVs which are hopeless in actually telling you what someone’s performance is going to be,” Matt says, “which is why we’re seeing more of other data points coming in, whether it’s facial recognition or tone of voice or various assessments. A CV isn’t going to give even the cleverest form of artificial intelligence enough information to make proper decisions.”

This relates to cases like the Amazon AI recruiting tool which reportedly rejected female candidates because it was mainly trained with resumes of men – in other words, Amazon’s attempt at AI-driven recruitment failed because of an overreliance on past datasets. If we train models using multiple data points, we might avoid those biases and inconsistencies that come with a single dataset.

So if your company makes AI in HR or you’re in close collaboration with an AI vendor, consider using various hiring methods (including assessments, video interviews, etc.) that can help you enrich the types of data used for training AI tools.

Also, you can contribute in making sure we model what’s meaningful for our purpose. “It’s modeling around what high performers look like,” says Matt. “If we’re modeling their facial expressions, is that going to give us the right match? So we’re modeling their behaviors, their attitudes, their values, but what aspect are we looking for? What aspects are actually repeatable in terms of finding someone who matches what we want?”

Trial and Error

Experimenting is how we learn. And that’s perhaps the most important aspect in which a company can contribute to the overall methods of training machines: with real-life data. Try out AI tools and measure results systematically. That way, we’ll soon have more evidence on whether something works or not.

To start experimenting with AI in recruiting, consider these four steps:

1. Understand your current process

In addition to identifying biases in your hiring process, dissect your existing hiring strategies. “I think a lot of it is about understanding current process,” Matt says. “How does it work? Where are the problems with it? What’s the experience like? In a large business, it could be really complicated. There could be [many] stakeholders and moving parts and people might not fully understand exactly what’s going on.”

Audit your recruiting process, and find the stakeholders and their roles. Use recruiting metrics to identify issues and bottlenecks. Then you might have an indication as to which aspects might benefit from a level of automation or AI tools.

“Gaining that understanding and that self-awareness of what’s going on within the organization is a good place to start,” says Matt.

2. Feel the pulse

Another aspect is to understand the environment. Matt clarifies: “Understanding what the technology can or can’t do, looking at companies that are trying [AI in recruiting] and looking at their results is equally important.

“And then it’s about matching the two together. How can this technology realistically solve our niche problems? And if it can, how do we implement it in a way that actually works?”

3. See what AI in recruiting is available

Since you’ve delved into your hiring process and follow what other companies are doing, look for available tools. “Understanding what’s available and what’s out there is important,” says Matt.

“Look into the market and see what can now be done. Someone could have created something that’s the answer to all your problems and you just don’t know it exists,” he says. “And that’s […] confusing and difficult because there’s so much noise out there. But actually having a good view of what’s available is critical.”

Of course, when vendors mention that their AI tools are completely unbiased, be sure to take their claims with a grain of salt. As Miranda Bogen said in the Recruiting Future podcast: “As predictive tools have access to more and more data, there’s more risk this data is closely associated or even a proxy for protected categories [which tools shouldn’t take into account in order to be bias-free].”

If you’re already using automated tools, work with vendors to test and validate them regularly.

4. Remember the candidate

Candidates’ reactions to AI in recruiting are just as important as the effectiveness of tools themselves. “Do the people I’m trying to hire actually like being interfaced with automatically in this way?” asks Matt. “Because if they don’t, and my competitor is taking a more human approach, then I might miss out on some great talent.”

As Matt mentions, there may be cases where implementing automation will be welcomed by candidates; for example, communication about the status of their application will improve. “The biggest complaint candidates have is the black hole that comes through recruitment, where they just don’t know what’s going on, what stage they’re in the process, what the next steps are, what people think of them. And I think technology can fill that gap.”

Sometimes though, candidates may be confused as to the role of technology in the hiring process.

“There’s maybe some fear and misunderstanding about how technology is used to screen out and select people,” says Matt. “And certainly some of the publicity that has come out recently around bias isn’t good. I tend to find that people overestimate how much AI in recruiting is actually responsible for whether they are chosen or not.”

People are wary that they’re being screened out for a job by a faceless machine, and a human isn’t having the chance to consider them.

And that can be especially true with tools like face-recognition software. “It’s very easy to get carried away and think ‘the expressions on my face is how people are going to decide whether I’m going to be a high performer in this job or not.’”

This brings us back to the importance of multiple touchpoints of data in AI in recruiting to lessen dependence on one single area, Matt reminds us. “[Face-recognition software] is just one data point amongst many other things.” Hiring can rarely be reduced to a single decision anyway, as Upturn’s report stresses.

Things are already happening

“There are some businesses where people are effectively being hired with an automated process,” says Matt, “and they might not go actually talk to someone until their first day. It’s a really interesting time. I think that we don’t really know what the answers are going to be in all of this, and a lot of it is experimentation and feedback.”

Matt mentions some companies are trying out automation for volume hiring and graduate hiring. For example, replacing multiple interviews with one video interview at the start reduces the number of candidates you’ll have to meet in person, and candidates wouldn’t have to go through as many hiring stages as before. It’s an effort to improve the efficiency and overall candidate experience.

“Now again, it’s still early days,” Matt reminds us. “Will they revisit that in three or four years time and say ‘the people we hired weren’t as good as the people we used to hire when humans did it’? But still, it certainly makes sense in terms of recruitment and selection process improvement.”

And actually having some real-life examples and data will bring a revolution in how AI in recruiting is made and applied, and this benefits organizations in many ways. Matt reminisces on another time when new technology was tested:

“I remember back in the late ’90s, early 2000s, when recruiting on the internet became a thing. There was a huge amount of mistakes, and horrible things happened, but that didn’t mean that online recruitment wasn’t going to be big. It just wasn’t perfect straight away.”

Matt adds, “Several companies experimented and stuck with it, and contributed to the debate, and gave feedback, and helped shape what the vendors were offering. They’re the companies that benefited the most in the long term.”

So, don’t be afraid to open up to new technology. If you’re an early adopter, you’ll also be the first to benefit when AI technology becomes a smoothly operating aspect of the mainstream recruitment process. Matt reminds us that automation is already widely used and you can find many tools to apply to your recruitment efforts. Experiment with them.

“Be very critical, very analytical about what the results actually are and whether they’re what you want or not.”

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This might be a future many of us have envisioned – one where artificial intelligence makes our lives easier and better. Then there’s the possibility many dread: that Joe won’t actually be your assistant, but rather, your replacement, coming straight out of an Isaac Asimov universe.

How possible are these scenarios and what can we do to ensure technology works to our benefit? And how can we embrace the future of AI?

I recently discussed AI in recruitment with Matt Alder, a reputable British HR thought leader and host of the Recruiting Future podcast. He gave intriguing insights into how businesses currently implement AI in hiring and what the future holds for recruiting professionals. We discuss these insights here.

The first eye-opening fact Matt mentioned is that, despite all the talk about AI recruiting software and their pitfalls and successes, we don’t actually have any genuine artificial intelligence in recruiting.

The term ‘artificial intelligence’ is greatly exaggerated

According to Techopedia, an accurate definition of AI is “the creation of intelligent machines that work and react like humans.” This means they might understand speech, learn and plan, and solve problems on their own. If you’ve ever watched the acclaimed show Person of Interest, you’ll be pretty hyped up about what’s probably the highest potential form of AI.

But that’s not what the HR and recruiting world seems to be calling AI most of the time.

Matt Alder addresses this confusion: “It’s kind of easy to get caught up in the definition of AI in recruitment. There are many vendors and suppliers to the recruitment marketplace that will claim they have AI and everything they make is based on AI.

“But, you can be pedantic,” quips Matt, “and say we haven’t got any genuine AI in the recruitment space as yet.”

Matt clarifies that the term “AI” usually refers to is relevant technology that’s used in the hiring process. As he mentions:

We’ve got algorithms to match the right people to the right jobs; we’ve got some aspect of machine learning and forecasting, and we’ve also got elements of smart automation creeping in.

Chatbots that increase candidate engagement, automated sourcing, algorithms that show jobs to targeted audiences and other tools are indeed progress towards a world of AI in recruitment, but they’re not quite there yet. “It’s still really early days for all of those too,” says Matt.

The triad of tech models

There are three types of analytics and AI: descriptive, predictive and prescriptive. Descriptive gives us information about what’s happening, predictive shows us an image of the future, and prescriptive technology tells us what we should do based on these findings.

It seems that AI in hiring is still in the descriptive phase with a bit of predictive flair. Matt emphasizes: “We can see development in matching algorithms, helping recruiters to find good candidates that may have been hidden to them, but how do we actually predict which of these candidates are going to perform better in the job?”

For example, Workable’s own AI-powered feature, AI Recruiter, searches thousands of public online profiles in seconds to find candidates who match the skills and requirements listed in your job descriptions. This type of AI recruiting software is certainly useful to help you build a strong talent pipeline, but it can’t actually predict job performance. You still have to shortlist and evaluate candidates yourself.

“We’re probably still at the descriptive stage in terms of trying to understand what’s actually happening before we can unleash a recruiting AI to make our decisions for us,” says Matt.

“The next stage is, obviously, technology starting to accurately predict the performance of candidates and say, ‘Here are 10 candidates that match the criteria you have in mind and these three are going to perform the best.’”

And while that sounds great, what will happen if technology becomes even smarter?

AI in recruitment will take your job (or some part of it)

The fear that AI will take over our jobs and we’ll all be unemployed is frequently mentioned, both in everyday society and in pop culture. And the possibility is very real: we’ve already seen it happen with driverless trains, robot miners and more.

In recruitment, being replaced by AI is also possible, though that possibility is usually considered unimaginable. “I think there’s a lot of denial in the space,” says Matt. “People think, ‘I couldn’t possibly be replaced by a machine so I’m just going to ignore the threat, and not do anything about it.’ And that’s a mistake.”

Fair enough; I, myself, can be accused of falling into that same bucket that Matt refers to. As a content writer, I can’t imagine a machine being able to conjure up stories or compose pieces like I do. But then again, an AI recently wrote Harry Potter fanfiction. It might have been terrible (contrary to what The Verge might think), but machines can learn to improve faster than humans (*cough*).

In the recruiting space, artificial intelligence can learn many of the tasks recruiters already do on a regular basis – and maybe better too. Matt comments:

“Certainly, a lot of the automated and repetitive tasks that recruiters do will be able to be removed. [Many] recruiters think they can’t be replaced by a machine because they have gut instinct and super powers and experience and that means they’re better. But what we’re seeing is that humans are very biased when recruiting.”

“Also, the way many companies recruit isn’t necessarily the best way,” says Matt. “Lots of them are still hiring on CVs and interviews and cover letters and assessment techniques from decades ago. There’s a huge step forward that technology can make to improve those things.”

This doesn’t have to be a dystopian future

There are several arguments against the possibility of a dystopian future brought by machines. One of those arguments begs the question: if AI takes over our current jobs, does that mean there’ll be no jobs left for us humans?

Recent research predicts that 85% of jobs that will exist in 2030 haven’t yet been invented. So even if technology takes over our current jobs, that could actually lead to other kinds of employment. Imagine a world where the most repetitive, dangerous or administrative tasks will be done by machines, leaving humans free to learn and educate themselves in more challenging, innovative, or exciting work.

While that may still be too far ahead into the future of AI for the recruiting world, it’s possible technology will replace people in certain tasks in the next few years. For example, scheduling interviews or screening resumes. And that will open the way for you to focus more at what humans truly own: relationship building. This includes employer branding, recruitment marketing, candidate experience, proactive sourcing during events or social media.

So while “AI Joe” busily exchanges routine information with candidates, predicts the performance of your shortlisted applicants or analyzes their facial expressions, you’re free to attend a popular tech conference speaking to ultra-qualified candidates.

Still, we must prepare

The ideal scenario of a harmonious relationship between humans and machines won’t come on its own. From their part, organizations must plan ahead. When strong AI comes, they may need to rebuild their recruiting process from scratch and rethink their strategies. (Friendly reminder: Workable’s People Search feature, including AI Recruiter, can help you in your recruiting efforts). They might need to render some positions or tasks as redundant or hire based on different specialties and skill sets.

“That’s a massive issue for businesses as a whole,” says Matt, “in terms of how they adjust the skill base of their employees to match the realities of the business.” Training programs that account for not current, but future skill gaps – think predictive analytics! – could be part of the solution.

From a recruiter perspective, it’s about thinking which of their skills are more likely to be needed and valuable, even if AI in recruitment becomes the norm, Matt says. That could be about relationships and about persuasion. Understanding data and being able to turn data into engaging stories from within the business.

“So how do you build relationships with the people you want to hire for your company? How do you persuade them that your company is the right place for them to work? And obviously, how does that reflect back internally?” Matt asks. “How do you work with your stakeholders within the business, and give them good advice and build relationships with them, and persuade them that a certain person might be right for them?”

So in the future, recruiters may focus on anything that involves networking with people and influencing their decisions. That makes sense. Machines are able to process information faster and more accurately than humans, but the ability to connect with others and plan strategically will, for the time being, remain primarily human. As stated in an article published in Harvard Business Review, the future might not see people competing with machines for jobs, but rather, humans will be freer to unleash their imagination, creativity and strategic abilities.

There are good reasons to be optimistic about the advent of AI in recruitment. We just need to be aware of the changes that are coming and hone our skills in areas that artificial intelligence can’t easily take over.

The post AI in recruitment: What the future holds for businesses and recruiters appeared first on Recruiting Resources: How to Recruit and Hire Better.

You are what you eat

Reuters identifies the objective of Amazon’s AI as scoring job candidates on a scale of 1 to 5 in order to assist hiring teams. But, as reported, the data the system was fed to learn how to score candidates was “successful resumes” and “unsuccessful resumes” from the past 10 years. Most of those resumes came from men, so the patterns the AI detected caused it to downgrade resumes from women. Essentially, Amazon unwittingly taught its AI to replicate the bias that already existed in the overall hiring process, according to Reuters.

Amazon isn’t alone

This isn’t the first time a company has seen its AI design break. The same has happened to other companies that experiment with machine learning. For example, when researchers tested Microsoft and IBM’s facial-recognition features in early 2018, they found that machines had trouble recognizing women with darker skin. The reason again was skewed input data; in short, if you feed the system with more pictures of white men than black women, the system will be better in recognizing white men. Both companies said they had taken steps to increase accuracy.

You can find countless other examples: from linguistic bias of algorithms to Google’s engine serving ads for high-paying jobs to mostly men, to Twitter users turning a friendly chatbot into a villain.

Hope on the horizon

Those of us fascinated with AI and its potential to improve our world may feel dejected when we realize the technology isn’t quite ready yet. But, despite our disappointment, it’s actually good news that these ‘failures’ come out. Trial and error are what helps us learn to train machines properly. The fact that machines are not 100% reliable yet shouldn’t discourage us; it should actually make us even more eager to tackle design and training problems.

As SpaceX and Tesla mogul Elon Musk affirms: “Failure is an option here. If things are not failing, you’re not innovating.” In that spirit, according to Reuters, Amazon has formed a new team in Edinburgh to give automated employment screening another try, this time taking diversity into account.

AI is not panacea

Despite growing concern that machines will take over people’s jobs, AI is unlikely to replace human critical thinking and judgment (we’ll still have the ability to create and control machines). This is especially so during the hiring process, where people’s careers are on the line; we need to be careful about how we use technology. HR thought leader Matt Buckland – who was VP of Customer Advocacy at Workable for two years – sums it up nicely: “When it comes to hiring, we need to have a human process, not process the humans.”

This means that artificial intelligence is a service tool that gives us initial information and analysis to speed up the hiring process. A good system can provide you with data you can’t find yourself (or don’t have the time to). But it shouldn’t make the final hiring decision. We humans, with our intelligence, must be the ones to select, reject or hire other humans.

We, at Workable, keep all this in mind when developing People Search and AI Recruiter, our very own AI features.

Our VP of Data Science, Vasilis Vassalos, explains: “Our efforts center on rendering our data more neutral by excluding demographics and gendered language when training our models. And, of course, to train our AI, we use a wide range of anonymized data, not only our own as Workable, but also data from the millions of candidates that have been processed in our system, so we can cancel out the bias of each individual hiring process.”

We’re also careful about how our tool will be used. “Perhaps the most important thing,” Vasilis adds, “is that we don’t allow our AI to make significant choices. The “AI Recruiter” feature is designed to make suggestions, not decisions.”

Of course, our methods and artificial intelligence itself will continue to improve. “We recognize the difficulty of algorithmically promoting diversity and training machines to be fair,” says Vasilis. “But, as the technology advances, we’ll keep improving our practices and product to make hiring even more effective.”

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Helping companies to streamline their recruiting is what we do at Workable. We like to help solve the harder recruiting tasks, wrapping them up into an affective, flexible workflow. Partnering with specialist services helps make this a reality, which is why we’re pleased to announce our latest partnership with JamieAi, a service that helps connect employers with data service professionals across the UK, France, Netherlands, and Germany.

As you’d expect from company in the data science and AI space, there’s some smart technology behind the scenes. JamieAi makes recruiting quicker and cost-effective, while ensuring a match with candidates on a range of technical, cultural and personal attributes.

Combining human and AI expertise, JamieAi ensures only qualified applicants with the right skills and interests hear about your role. Providing an unbiased and effective way to hire, the integration ensures that you and your hiring team retain full control of the hiring process.

Setting up the integration with JamieAi is simple. Once authenticated, you’ll be able to link up JamieAi postings with jobs from your Workable dashboard. Once the jobs are linked, candidates matched through JamieAi will be visible directly in your Workable hiring pipeline. From here, you can gather feedback, plan interviews and assessments, exactly as you would with candidates for any other role advertised via Workable.

Find out more about setting up the JamieAi integration.

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