AI in Recruiting: What it Means for Talent Acquisition in 2022

At this point in the 4th industrial revolution, we’re all familiar with just how commonplace the use of AI is. Whether it’s your Spotify Wrapped summary at the end of the year, Alexa reminding you to order Tide Pods, or a chatbot conversation to change a dinner reservation – artificial intelligence is a part of our daily lives. 

But beneath the convenience and hype of consumer AI, the world’s largest employers have been finding ways to use this transformative technology to create faster, fairer hiring processes for their businesses.  

Consider these examples of AI in the enterprise:

• One HireVue customer was able to save 68,124 recruiter hours in one year and reach 300% more candidates 
• Black Angus Steakhouses leveraged conversational AI and text messaging during the beginning of COVID to achieve a 96% response rate 

 

HireVue's Chief Data Scientist, Dr. Lindsey Zuloaga explains the science behind HireVue’s AI Assessments. 

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Science-Backed Hiring: Enhance quality & fairness with structured interviews

 

AI in recruiting: It’s about more fair prediction

The potential for AI to make an impact in all domains is huge, and recruiting is no exception. Talent acquisition succeeds when it predicts the best candidates for a job, and builds the relationships that convert those candidates to employees.

AI has the potential to scale and manage a large portion of this prediction work. At its best, artificial intelligence offers up great talent (whether internal or external) for recruiters and hiring managers, surfacing the best candidates regardless of work history, educational background, and demographic.

This is important to keep in mind when starting a conversation with any AI vendor. It might be tempting - and interesting - to discuss the technical nuances of a vendor’s AI solution, but this shouldn’t be the focus. Instead, you should focus on the impact a solution could have on your recruiting.

Properly implemented, AI can deliver dramatic improvements in quality of hire, time to fill, new hire diversity, and other critical recruiting metrics.

The artificial intelligence landscape

Some of the most common applications of AI in recruiting include::

• AI-driven assessments. AI-driven assessments are pre-hire assessments which leverage AI to evaluate candidates faster, more effectively, and in a candidate-friendly way. These most commonly take the form of game-based assessments and video-based assessments.
• Candidate rediscovery. Candidate rediscovery tools analyze your existing database of candidates to “rediscover” those who might be a good fit for your open requisitions.
• Job description optimization. Job description optimizers are similar to Grammarly, but for job descriptions. They provide wording and phrasing recommendations that make a description more informative and inclusive.
• Ad automation. Ad automation AI places and tests your job ads on a variety of different platforms, optimizing your ad spend.
• Job market forecasting. Job market forecasting software gives insight into available pools of talent for different job types, experience levels, or location.
• Candidate relationship management. Candidate relationship management software can leverage AI to deliver a higher level of personalization to candidates, and re-engage candidates who applied previously.
• Chatbots. Chatbots and conversational AI provide a convenient interface for candidates to find and apply for jobs.
• Resume filtering. Resume filtering tools evaluate candidates’ resumes and applications to make broad-stroke screening decisions.
• Social candidate discovery. Social candidate discovery software scrapes social and other online platforms to surface passive candidates that may be a good fit for open requisitions.

Within each bucket are a large variety of solutions that promise similar results. While the majority of these have at least one unique use case where they excel, a select few excel in many domains.

This puts recruiting leaders in a dilemma. How do you select vendors when they all promise the same improvements in time to fill and quality of hire? Like we mentioned previously, it comes down to impact. Which technologies are most likely to fundamentally change your recruiting strategy, and deliver transformative - rather than iterative - successes?

The question that cuts through the hype

It’s difficult to find a technology vendor in 2022 who doesn’t claim to use some form of artificial intelligence in their tools, but a peek behind the curtain shows that many offerings are just previous generations of automation with a well-designed and updated interface. 

This isn’t to say they can’t be useful – a beautifully designed spreadsheet is better because the information is easier to digest. That being said, the highest potential for impact lies with today’s best-of-breed technology, not rebranded tech.

While not 100% precise, you can use this question to test whether a vendor is leveraging 

best-of-breed, and delivering the highest potential for impact:

“Could a team of interns, armed with calculators and flowcharts, do what this AI claims to accomplish?”

If the answer is “no,” chances are the vendor you’re talking to is making the most of today’s available tech. The reason this works is because today’s AI offers the ability to embed expertise - not just rote tasks - into an algorithm.

5 table stakes criteria to evaluate AI vendors

While potential for impact is the most important metric when evaluating AI vendors, it’s not the only criteria. Some might promise the moon, and ultimately be unable to deliver. Use these 5 table stakes criteria to ensure you don’t end up in a disappointing partnership.

1) Experience with the recruiting space.

Recruiting is a highly regulated discipline. Inexperienced vendors run the risk of putting their customers in jeopardy.

Vendors who have experience in the recruiting space typically have a lengthy history of success, use widely accepted and validated standards when building AI (like the EEOC’s adverse impact guidelines), and understand and have demonstrated the legal implications of their technology on hiring.

2) History of success with organizations like yours.

While the number of documented AI success stories grows by the day, many applications of AI remain theoretical. When a vendor has a library of documented, referenceable success stories from organizations like yours, it indicates that you’ll be a partner (not a beta tester), and have a built-in playbook for success.

3) Data used to identify and evaluate candidates.

With a few exceptions, most applications of AI in recruiting are designed to uncover great candidates. Sourcing tools, whether through social media scraping or candidate rediscovery, evaluate passive job seekers who have yet to apply. Chatbots and resume-filtering tools evaluate applicants at or during the application phase. AI-driven assessments evaluate applicants post-application. The data that feeds these tools plays a large role in their predictive accuracy and potential for bias.

You can evaluate a vendors’ ability to predict what they say they can predict by the data they use to make the prediction. Things like demographics, GPA, and the school someone attended offer very little predictive power, while, unsurprisingly, job-related data offers the highest level of predictive power. 

4) Commitment to ethical AI.

This is also the time to look inward and decide if AI ethics are important to you and your organization. If they are, you should take the opportunity to evaluate if vendors have the same commitment. Vendors that are serious about ethical AI have documented ethical principles, can explain how they test their algorithms for bias (and remove it if necessary), and have an external technical advisory board.

5) How a vendor audits AI for adverse impact.

One of the biggest promises of AI is its ability to make hiring more objective and fair. That said, AI is like any powerful technology: improperly built and tested, there is the potential for harm. Vendors should be able to provide full documentation around their process for mitigating bias, and it should include internal procedures, third-party audits and an AI explainability statement.

Any algorithm in the recruiting space should be vetted to prevent adverse impact against protected classes.

The incredible potential of AI in recruiting

The potential of artificial intelligence in recruiting is tremendous. But the potential is accompanied by hype, misinformation, and market noise that makes it difficult to discern the applications of AI which are truly transformative. So while some early adopters are seeing incredible advances in their recruiting processes, platforms, and metrics, most TA teams remain on the sidelines.

If you’re looking for more information around how to enhance the quality and fairness of your hiring, get the science-backed whitepaper on structured interviews.