A New High-Cost Center: Hiring

Hiring has always been expensive: There’s the recruiting, the screening, the candidate care, the onboarding, the training and development, and the management of all those tasks, plus the lost productivity of an empty seat. Wasn’t AI supposed to make it cheaper? Or faster? Or easier?

It may someday, but for now, the much-hyped technology appears to be sending costs in the wrong direction. The average cost of employee turnover has jumped 20% to $45,236 per person, up from $36,723 last year, according to new figures from The Harris Poll. AI, of course, was supposed to help firms filter through thousands of candidates faster, but in practice, its own biases sometimes miss strong candidates and force firms to do more interviews. Meanwhile, candidates are turning to the technology in a big way—to prepare résumés, to fill out applications, to help with the interview process—and once again inundating employers with false impressions or simply too many options. “It’s gumming up the candidate funnel,” says Bryan Ackermann, head of AI strategy and transformation at Korn Ferry. “The funnel is not funneling. It’s a wide pipe.”

But AI isn’t the only problem here, as it turns out. Experts say that human indecisiveness is also slowing the process and raising its costs. Unsure about which roles they may need in the near future, many managers end up delaying their hiring decisions, in the process losing prized candidates and forcing the job-hunting process to begin all over again. Company leaders, meanwhile, are retreating on head count late in the game, which adds to costs as well. “The process is dragging on a bit more these days,” says Dennis Deans, global human resources business partner at Korn Ferry. “Firms are being very selective in what they’re looking for.”

At the root of the problem is a major conceptual shift in hiring. Twenty years ago, a hiring manager’s chosen candidate likely did not have every skill and qualification the job description called for. Development and training ensued, which made sense at a time when average tenure at a company, according to data from the Bureau of Labor and Statistics, was four to five years. (The figure is now 3.9 years, but lower among young people, who tend to need more training.) “There was always the expectation that the person would not be perfect upon walking through the door,” says David Vied, global sector leader for medical devices and diagnostics at Korn Ferry.

These days, recruiters expect candidates to hit the ground running. Firms are hiring not just for a full suite of skills, but also for culture and personality—which means four to six interviews instead of one or two, plus a pile of assessments. In turn, hiring times have grown longer, hovering at an average of 30 to 45 days. “They’re looking for a perfect long-term fit,” says Dan Zautis, director of marketing and sales operations at Korn Ferry’s Professional Search and Interim business.

But it’s AI that’s at the center of the cost issue. By helping candidates look stronger than they are, or filtering out the ones who really are strong, it can double the amount of time recruiters spend on hiring. “They find out that they don’t have the right person, and restart,” says leadership expert Flo Falayi, senior client partner at Korn Ferry. With this in mind, experts suggest not letting perfect AI ratings be the enemy of the good in hiring. “It’s easier to default to AI,” says Kim Waller, senior client partner at Korn Ferry. But the result is a hiring process that prioritizes risk avoidance over actually finding talent. “Sooner or later, a human needs to make a judgment call,” says Vied.

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