Amid a recent spate of high-profile layoffs and a recognition many companies rushed to hire to fill pandemic-driven business needs, organizations are now refocusing on quality of hiring — and the use of artificial intelligence (AI) to aid in those efforts.
From 35% to 45% of companies are expected to use AI-based talent acquisition software and services to help select and interview job prospects in the coming year, according to two recent studies.
Nearly three in four organizations boosted their purchases of talent acquisition technology in 2022 and 70% plan to continue investing this year — even if a recession arrives — according to a survey by online enterprise hiring platform Modern Hire.
More recently, AI has been applied to the task of creating job requisitions and similar materials shared by the employer that are gender and ethnicity neutral; the goal is to eliminate as much human bias as possible in hiring and increase diversity, equity and inclusion (DEI).
The shift comes as the US unemployment rate dropped to 3.5% last month — and just 1.8% in the tech sector — making it hard for organizations to recruit top talent even as many companies lay off workers hired in haste during the COVID-19 pandemic. Many organizations rushed to bring in employees to address business goals such as digitization projects, distributed work models, and the rollout of data analytics and business intelligence platforms. In some cases, companies lowered hiring standards to find anyone who could meet the minimum job qualifications.
Now there is an increased need to identify high-quality job candidates and make hiring decisions quickly, and that has upped AI adoption, according to Bret Greenstein, a PricewaterhouseCoopers (PwC) partner and Data Analytics and AI researcher.
“There were a lot of factors that drove this need, from the Great Resignation, to the rapid hiring and recovery in 2021, to the recession period now causing a large influx of tech workers into the market,” Greenstein said. “In all cases, recruiters need better tools to be efficient in matching candidates and ensuring interviews are used efficiently by ensuring candidates are well-matched up front. Additionally, they needed ways to do this in highly remote settings, due to the initial lack of travel and the later trend towards roles which are inherently remote.”
A reversal of reactionary hiring
In 2023, the reactionary hiring of recent years is expected to be replaced by a focus on quality, which can include hiring employees without college degrees but with passion and drive to learn on the job.
However, as many as 49% of candidates turn down a job offer because of poor recruiting experiences, according to PwC's Future of Recruiting survey. Along with improving the candidate interview experience, organizations need higher quality candidates who are also more likely to remain, and they're turning to AI to find, cull, and woo job candidates.
AI use in hiring is well entrenched for data manipulation and resume analysis, according to Lisa Rowan, a vice president of human capital management research at IDC.
“If you think about it, recruiting is a data-centric function with a lot of unstructured data found in people's resumes and CVs (curriculum vitae),” Rowan said. “The sophistication in this process of matching has evolved from matching up skills with requirements to include analysis that helps determine candidate fitness for the role.”
According to Modern Hire’s fifth annual Hiring Report, 45% of companies worldwide are using AI to improve recruiting and human resource functions. The survey of 300 senior level talent acquisition and HR professionals also found for the first time in two years that quality of hires (QoH) was considered a top technology investment priority. (A PwC survey conducted last year found 35% of companies plan to use AI to hire and train employees this year.)
"Quality of hires" is a metric used to determine how well a new hire performs, their engagement and promotability, as well as how likely new employees are likely to stay at the company over time.
Hiring right is better for retention
Hiring right the first time is vital to retention and creating value in a well-run organization, Modern Hire said in its report. Additionally, the skills and competencies needed for most jobs are more complex and more urgent than they were even a few years ago, as digital 21st-century skills become table stakes.
Resume matching to job descriptions is the most common use of AI, but Greenstein has also seen a lot of work enabling AI to analyze patterns, including factors affecting retention and segmentation of candidates based on experience, education, and skills to aid in recruiting.
“Chatbots have also become more popular as an aid for candidates to help answer questions about everything from benefits to how the company is organized and operates,” Greenstein said.
In 2023, AI hiring technology will also include intelligent interviewing, according to Modern Hire. Talent acquisition professionals can get a further assist from automated AI-based scoring.
"Now, AI techniques allow us to attach a valid and fair numerical score to the words a candidate speaks during an interview, yielding job-relevant, competency-based scores and rankings that can be used in decision making," Modern Hire reported.
Beyond AI scoring, hiring intelligence is increasingly allowing companies to match candidates to jobs they're likely to fit — before they become formal applicants. Early matching is an indication that organizations recognize the need for a two-way fit — it is no longer enough for companies to “gift” candidates with a job only when they deem them worthy. Candidates also pick the company, and especially the job.
"Because metrics such as on-the-job performance is not consistently tracked, quality of hire is often the hardest metric to measure accurately,” Modern Hire CEO Karin Borchert said in a statement. “By leveraging trusted science-based interview and assessment tools based on job relevancy and fair candidate experiences, hiring teams are relieved of these stressors, and can rely on the technology to deliver data-driven insights and quality outcomes."
The traditional interview process — long fraught with inefficiency, inconsistency, bias, and poor experience — is on the chopping block in 2023, as science and next-gen technology address the urgency felt by companies, and frustration felt by candidates, to move the interview experience to the next level, according to Modern Hire's study. “The next-level intelligent interview is one that uses data and candidate feedback to continuously learn, improve, and evolve," it stated.
Specifically, Modern Hire said an intelligent interview should embrace:
- The use of science, analytics, and AI for greater automation and insight and reduced bias;
- Clarity, accessibility, transparency, and humanity in the candidate experience;
- Global candidate reach through multilingual capabilities and support for international talent markets;
- Seamless workflows and extreme ease of use.
In 2023, hiring technology will include built-in structured interviews across job families and roles with questions designed to be job-relevant and focused on factors related to job success. Adding in automated AI-based scoring allows companies to more objectively evaluate candidate responses, yielding job-relevant, competency-based scores and rankings that can be used in hiring, according to Modern Hire.
What about built-in bias?
Problems still exist, however. While AI was supposed to eliminate subjectivity in terms of gender and race, experts say self-selection is still sometimes baked into AI software.
“It is often said that technology can only be as unbiased as the humans programming it,” Rowan said. “It is a challenge to eliminate bias from every angle. We are getting there, but it is an iterative and evolutionary process.”
Greenstein was more blunt: “The risk of bias in AI recruiting systems is still very relevant and has not been eliminated.”
Greenstein suggests HR reps and hiring executives be the ones to ensure the people deciding on policy and tools represent corporate diversity goals. And, they should ensure the data used to train AI systems reflects diversity, too.
“There are techniques for de-biasing that can be used to correct for bias in data, but it requires leaders who understand it to ensure this is addressed well,” Greenstein said. “AI systems are able to assist in talent acquisition today. However, it is important to leverage AI to augment the recruiting process and not automate it."
While AI can help scan resumes — and review, edit, and generate job descriptions — it is important to ensure that people validate the effectiveness of AI systems rather than blindly accepting the results, Greenstein said.
AI-powered virtual reality simulations can also bolster virtual recruitment, open access to talent in far-flung geographies, help monitor remote workers and upskill employees, Greenstein said.
"Companies are increasingly using AI/ML, including simulations, to model and predict retention - including simulating different policy decisions, understanding how candidates' skills and experience match to job descriptions, and predicting acceptance rates on offers," Greenstein said. "It also includes using analytics to understand where your company is positioned in your market and your city when it comes to hiring and promotions."
Data driven approaches are so much more important now that candidates and workers are more remote now than ever. Additionally, the introduction of VR technologies has enabled virtual reality based onboarding and virtual exploration of the workplace.
"This is still in early stages, but there is a generation of new hires who expect more immersive experiences as part of their recruiting and onboarding, and as remote workers, this has the potential to bring the workplace to them," Greenstein added.
AI-based talent acquisition software runs the gamut across different areas of the recruiting landscape, said IDC’s Rowan. For example, Beamery offers job recruit marketing software. For applicant tracking, there are software and services providers such as iCIMS, Jobvite, Smartrecruiters, SAP SuccessFactors, Oracle, and Workday. And for data analysis, firms such as Modern Hire, Seekout, Eightfold, and Phenom are among the leaders.
When choosing an AI-based talent acquisition application or service, Greenstein said organizations need to be transparent, “so people are not surprised or put off by it. Assure people that you properly manage AI systems to be fair and to assist the work of HR,."
Don't discount the effect AI can have on talent acquisition, he said, and don't fear bias.
“Instead, put in business leaders who help define and select AI systems who understand the issue of bias, and who understand the HR and skills strategy of your business,” he added. “AI is not a technology to just build and deploy. It is a tool that needs to be managed by people who understand the strengths and risks, and who also understand your business.”