Imagine you’re going away for a month and trying to figure out who can watch your house. Not just someone who knows where the spare key is, but someone who’ll water your plants, make sure you didn’t leave any rotting food in the fridge, and call if something goes wrong. You’d turn to someone you’ve known for years, not to the neighbor down the street who claims to have a green thumb.
That’s how the best retained-search professionals operate in an era of agentic AI, when the depth of relationships matters more than ever before.
For years, experienced recruiters have weathered one disruption after another—internal-talent team dynamics, the onslaught of LinkedIn, company HR teams using keywords to treat talent like a search result, and now AI. Each wave has prompted the same question: Do recruiters still matter? And each time, the answer has been yes—but the reasoning has evolved. Today, the value of recruiters comes down to something simple but high stakes: Organizations can’t afford to hire the wrong person.
AI has greatly improved many aspects of recruiting, with algorithms that can scan and surface qualified candidates at speeds no human can match. These tools help HR to accelerate preparation and to cull long lists of potential candidates and skill sets. But they can’t predict who’ll actually succeed.
"AI has greatly improved many aspects of recruiting."
Résumés disproportionately reflect opportunity, storytelling ability, and historical context—not future suitability. Korn Ferry research consistently shows that past performance, without an additional assessment of potential and learning agility, is a poor predictor of success in larger or more complex roles. These capabilities—operating under pressure, leading through ambiguity, fitting within a company’s culture—are harder to see, even by the most skilled internal HR teams. That gap is where mismatched hires happen. I’m fond of saying, “You get hired for what you know, and fired for who you are.”
Consider a controller who arrives at a financial firm with stellar credentials, excellent references, and a history of transforming the function. Yet the culture, team dynamics, and pace of business at the firm don’t fit how she works. Within a year she’s gone, and the organization is back at square one.
We see this all the time. Culture fit and potential are the two most important predictors of whether someone sticks around, earns promotions, and grows with a business. They’re also the two things AI is least equipped to evaluate. A machine can identify who looks like the person who held the role before, but it can’t tell you who will excel in the role as it’s evolving. But retained search thrives in such cases. Recruiters have trusted networks cultivated through repeated interactions and candid conversations, allowing them to really understand who will watch your home and who’ll just say they will.
The most effective retained search today uses data to validate what experience already suspects, and human judgement to interpret what the data can’t fully explain. Korn Ferry has analyzed more than 100 million assessments to understand what greatness looks like across four dimensions: competencies, experiences, traits, and drivers. Of those dimensions, our data shows that agility captures the traits most relevant to a world in constant flux. Organizations that hire for agility dramatically outperform their competition. But that data, and the ability to gauge a candidate’s agility, still requires interpretation by humans. That’s why we’re not surprised that as AI has become more embedded in search, we’ve seen retained search grow instead of shrink.
As agentic AI’s role continues to expand, the best outcomes won’t come from choosing between data and instinct. They’ll come from combining both. It’s a case of recruiters and agents being copilots, not competitors. AI can accelerate some parts of search.
Reprinted with permission from the May 14, 2026 issue of HR Executive. Further duplication without permission is prohibited. All rights reserved.
