By Matt Chambers, Founder and CEO, Loxo
Executive search firms are handling more searches with fewer recruiters than at any point in the industry’s recent history. AI now handles much of the sourcing, outreach, scheduling, and administrative work that once filled recruiters’ days, allowing firms to run more searches with more efficient and lean teams.
Efficiency may outpace expertise, unless firms can retrain their teams to better utilize their time.
The Uber wake-up call
The gains of AI use are easy to measure: faster searches, lower administrative burden, more candidate introductions, and higher recruiter throughput. But Uber’s recent decision to eliminate nearly a quarter of its HR and recruiting organization offers an early glimpse of what that efficiency means for search firms.
It’s not that AI directly triggered the cuts; the company attributed the restructuring to overlapping responsibilities and a fragmented people organization rather than AI itself. But the sheer number of HR employees Uber once needed is no longer necessary.
The issue for firms is that instead of using these efficiency gains to fundamentally rethink how recruiters create value, firms instead seem content to fill the reclaimed time with more of the same — more searches and more busywork activity that categorizes AI primarily as a productivity tool instead of something bigger.
Take for example a recent study by Gartner, which found that although AI adoption across HR has accelerated rapidly, 88% of HR leaders say their organizations have yet to realize meaningful business value from those investments. Organizations that redesign workflows around AI consistently outperform those that simply add technology to existing processes.
The pipeline problem
But there are long-term risks for firms that choose efficiency over effectiveness as well: they lose their own talent pipeline, as the “grunt work” of recruiting is turned over to machines, and junior team members lose out on critical learnings.
While an experienced recruiter may rely on pattern recognition built over years of reviewing candidate profiles, participating in intake meetings, listening to executives describe what they want and (just as importantly) recognizing what’s been left unsaid, a recruiter who spends five years merely supervising automated workflows instead of building pattern recognition through experience may become highly proficient with the tools without acquiring the judgment clients ultimately expect from a trusted advisor. Faster execution cannot compensate for expertise that never had an opportunity to develop.
Those instincts rarely come from formal training. They develop through repetition, exposure and accumulated experience, much of it during the junior stages of a recruiter’s career.
As AI assumes more of those foundational responsibilities, firms need to decide how the next generation develops those same capabilities.
A lesson from Wall Street
Other industries are already confronting that reality. Investment banks and private equity firms embraced AI to automate financial modeling, presentations, and research traditionally performed by junior analysts, then discovered they had disrupted the apprenticeship model that produced future managing directors. Many have begun redesigning entry-level roles to focus on work that still requires human judgment because they recognized that the pipeline producing future leaders had begun to narrow. Executive search firms face the same structural challenge, with the advantage of learning from someone else’s course correction rather than repeating it.
What reclaimed time should buy
The ideal workflow looks different from what most firms currently run. When AI handles intake, sourcing, first-pass candidate matching, and outreach, recruiters are freed to do the work that has always driven placement quality but rarely received the time it deserved. More conversations with candidates. Deeper advisory relationships with clients. Genuine judgment applied to a shortlist rather than a quick read before the next administrative task pulls attention away.
There is also a business development argument that tends to get lost in discussions about AI efficiency. Recruiters who are not spending most of their day on administrative work have time to build lateral relationships that generate future searches. The highest-value placements in retained search frequently trace back to a relationship maintained for no transactional reason — a follow-up that was not required, a former candidate kept warm across roles, a conversation that started because someone had a free hour rather than a deadline. Those moments do not appear in throughput metrics. They show up in client retention and referral volume, often years later.
The measurement trap
The measurement problem is part of what makes this transition difficult. Efficiency gains from AI are visible immediately: time saved, screens completed, searches closed faster. The value of a recruiter who has spent three years building genuine advisory relationships with clients, staying close to candidates who were not placed, and developing the judgment to know when a technically qualified candidate is the wrong cultural fit. That value does not appear in a dashboard. Firms that optimize for what is easy to measure risk underinvesting in what actually drives long-term client retention.
The question executive search leadership needs to answer is not how much AI can reduce operating costs. It is the cost of deferred investment in human judgment in client relationships. Recruiting organizations that treat reclaimed time as an opportunity to run more searches at the same depth are making a different bet than those that use it to build sharper advisors. Both approaches will produce results in the short term. Only one of them compounds into the kind of judgment and client loyalty that competitors cannot easily copy.
Matt Chambers is the founder and CEO of Loxo, an AI-powered talent intelligence platform used by more than 13,000 recruiting firms worldwide. AI is transforming executive search, but the biggest challenge isn’t automation, it’s what comes next. In this timely op-ed, Matt argues that while AI is eliminating much of recruiters’ administrative work, firms risk weakening the very expertise that drives successful placements if they fail to redefine the recruiter’s role. Rather than using AI solely to increase productivity, search firms should invest in developing stronger advisors, deeper client relationships, and the human judgement that technology cannot replace.
