You’ll be hard pressed to find an area of corporate America where AI hasn’t found a place, and that includes the tech hiring process. A survey from MyPerfectResume found that 73% of employers say they use AI in hiring decisions, while 52% use it for decisions around restructuring and role planning.
On the other side, candidates are also increasingly relying on AI, with 52% of current job seekers reporting they use AI to help them in their job searches to refine submission materials (85%) and prepare for interviews (73%), according to data from SAP.
“Technology can help employers be more efficient, but hiring decisions still benefit from human judgment, especially when a candidate’s experience requires context that automated screening may not understand,” says Jasmine Escalera, career expert at online career and résumé builder Zety.
It’s clear AI is an integral part of the hiring process, and organizations need to prepare a strategy for what that looks like moving forward in terms of hiring bias, transparency, and striking the right balance of human effort and AI assistance.
AI has the promise of bringing efficiency in hiring for both job seekers and employees, but if organizations aren’t careful, an overreliance on AI technology can lead to unintended consequences. Further MyPerfectResume data also reveals 65% of respondents say AI often automatically rejects applicants before a person sees them, and 14% say AI rejects more than half of applicants outright.
Additionally, 47% say they feel AI has filtered out candidates who would’ve otherwise advanced in the process. And 51% say they use AI to flag risky candidates, such as people who might be viewed as job-hoppers or who have employment gaps.
Flagging risky candidates and eliminating them before a human can look at their résumé can filter out candidates with experience that tells a more complex story than an algorithm is designed to interpret, says Escalera. Candidates re-entering the workforce after time off, for example, may have valuable skills that don’t fit neatly into automated screening criteria, she adds.
Similarly, there’s concern AI will reject a professional who wants to change industries, or has qualifications that don’t perfectly reflect the language in a job description before a human has a chance to look.
Laurie Cure, CEO of consulting firm Innovative Connections, says she’s seen instances where AI has eliminated highly qualified yet nervous candidates who take more time than what the AI allocated to answer a question, or candidates may simply use a different language than the AI is programmed to look for, causing them to not be recommended to progress in the process.
She’s also seen where AI might use historical data to determine patterns of a successful employee, identifying certain schools, work histories, tenure, or other characteristics that, while not inherently bias, perpetuates the bias that accurate correlations exist between these elements, when they often don’t. Organizations need to ensure that humans remain a part of these processes, Cure adds, where they can bring context, intuition, nuance, and an ability to identify potential in a candidate that AI can’t replicate.
“I think we’re allowing AI to become the process instead of allowing it to support the process in ways that makes hiring better,” she says.
Cure says a major problem for most companies is that the balance is off, with companies using AI for the majority, if not all, of résumé screening rather than as a complement to human efforts. Organizations that simply implement AI to speed up different parts of the hiring process, without taking time to consider if a process stands to benefit from AI, run the risk of introducing bias.
“While this allows for managing high volumes of applicants, and provides greater degrees of consistency in applying job criteria, it likely misses many good candidates,” she says. “The human element needs to be highly active in developing job requirements so they’re not too narrow. Organizations need to look at how they ask AI to do its work, so be cautious how you frame the screening or other criteria.”
Ultimately, AI isn’t a tool to be implemented and forgotten, or one that should be viewed simply as a path to efficiency since many processes still benefit from and require a human touch. It’s important to conduct audits of AI processes in hiring, and to remember that the use of AI doesn’t eliminate the legal or ethical obligations an organization has for equal employment, says Cure, making the balance between human and AI even more important.
AI has also introduced an element of mistrust into hiring on both sides, where employers can’t be sure candidates haven’t relied on AI the same way candidates aren’t always sure exactly how AI is being used in the hiring process. Candidates are aware that employers are implementing AI, but they’re often unsure of the extent it’s being used and when to expect to interact with humans.
“That lack of clarity can create skepticism and frustration, particularly in a job market that already feels highly competitive,” says Escalera. “The goal shouldn’t be to convince candidates that AI isn’t being used, but to help them understand how technology supports decisions rather than replaces the human judgment behind them.”
Cure recommends organizations start with a process map that outlines every step of an organization’s hiring process to help visualize where AI is beneficial and which processes still require human intervention. Companies can shift to relying too heavily on AI or they may become too dependent on human effort, when that effort could be put toward more important tasks.
“Humans bring an understanding of a person’s broader history, and the ability to detect when a candidate has potential to grow into the role,” she says. “People can see non-traditional career paths and motivations more distinctly than AI. Yet AI brings consistency, efficiency, criteria standardization, and a level of objectivity the process benefits from. If we effectively blend these two at the right points in the process, hiring is enhanced, not diminished.”