“There are really powerful ways that AI can augment, support, and accelerate human decisioning around who to hire and who to move forward, as opposed to AI tools that make decisions for us,” said Andy Nelesen, market director, talent acquisition solutions at SHL. “I would encourage you to explore some of those solutions, systems, and opportunities that really design in the human judgment piece from the start.”

With rapidly increasing applicant volumes and AI-driven transformation across the hiring process, talent acquisition teams are now faced with identifying how to effectively balance technology adoption and high-quality decision-making at scale while maintaining applicant trust. This was the topic of a thought leadership spotlight at From Day One’s March virtual conference.

Both candidates and TA teams are using AI to streamline the job search and hiring process, says Nelesen, but he thinks the current benefits may be one-sided. “It feels like AI has been a real dream for candidates and a bit of a nightmare for talent acquisition teams, in terms of getting these new technologies fully enabled and delivering value.”

As candidates use AI to contextualize, polish, and submit their resumes, shrinking TA teams can be left with candidates who aren’t aware they’ve applied for a specific job. Similar career documents generated by AI make it more difficult for hiring teams to screen and differentiate applicants. “When AI is polishing up all of these resumes, they sure look the same.” Nelesen said. 

Additionally, there are increasing concerns that what recruiters are learning from AI-generated documents may not be real. He suggests that employers require candidates to demonstrate their skills during the interview process, not just claim them. “All of this is making things much more difficult, obviously, for the talent acquisition function, especially at the selection portion of the hiring funnel.”

That said, TA teams are also using AI in the hiring process, and candidates “want reassurance that those tools are capturing their skills and capabilities accurately and fairly.” SHL research shows that 59% of workers believe AI is increasing bias and 66% believe employers should reveal when AI is used in the hiring process. So how can organizations leverage these emerging tools while simultaneously ensuring a positive candidate experience?

Nelesen cautions against relying too heavily on AI without also incorporating governance, transparency, change management practices, and human oversight. “It’s really easy to get overly focused on the automation capability,” he said, acknowledging that poor implementation of AI can inadvertently scale risks by amplifying existing bias and causing inconsistency.

Successfully integrating technology into the hiring process requires companies to understand how candidates will engage with the tools, along with their expectations and fears, which he expects to result in intentional strategies for technology selection.

“I think we should over-index on the human side of the equation,” Nelesen said, “rather than just being wowed by the promise that AI can deliver in terms of driving scale and efficiency.”

As organizations continue to embrace AI, they will need to prioritize AI readiness among their candidates. SHL research shows that only 48% of employees believe their workplace is AI ready, but this is a metric best measured through behavior—not just employee perception.

Based on data collected from millions of employees around the world, SHL developed a behavioral framework that predicts high performance in an AI-enabled environment. Factors like AI literacy, analytical ability, continuous learning, and AI promotion break down into competencies such as AI output evaluation, value creation, critical thinking, and decision-making amid uncertainty. 

Rather than getting too caught up in tool-specific, rapidly changing skillsets, he says that hiring for these foundational, lasting skills like critical thinking, adaptability, and embracing new technology can be more meaningful. Even better? Combine the two. “I’m not saying that we should walk away from hiring profiles that are steeped in job-specific skills. There are ways to layer in these AI-readiness skills on top of those skills.”

The research also shows that new graduates and tenured professional pools bring different, complementary sets of AI-readiness skills to the table. Nelesen encourages leaders not to dismiss either population outright based on perceived limitations—instead look for ways to integrate these teams for maximum impact.

Editor’s note: From Day One thanks our partner, SHL, for sponsoring this thought leadership spotlight. 

Jessica Swenson is a freelance writer and proofreader based in the Midwest. Learn more about her at jmswensonllc.com.

(Photo by Thai Liang Lim/iStock)