AI accelerates executive search by 2-3x, but closing C-suite deals still requires human touch

AI is transforming how companies find their next CEO, but not how they close the deal

AI is speeding up the sourcing half of executive search, but the trust and persuasion needed to close a C-suite hire remain human work AI is accelerating roughly half the work involved in filling a chief executive or C-suite vacancy, according to recruiters at several major search firms. The technology can map talent markets, surface candidates from unexpected industries, and mine years of interview notes in hours rather than weeks. But the parts of executive hiring that depend on trust, persuasion, and reading a room remain as slow and human as ever. Marty Parker, CEO of Waterstone Human Capital, said the identification stage of candidate searches is becoming commoditised. His firm saw the shift first-hand during an ongoing search for an executive to run a jewellery company's high-tech manufacturing operation. The company's proprietary AI tool suggested looking at the dental technology industry, where similar precision machinery produces veneers, crowns, and other intricate products. "Who would consider dental manufacturing with jewellers?" Parker said. "You just wouldn't" Search firms are also using AI to retrieve forgotten impressions from old notes. Matthew Siegel, a principal at Korn Ferry, said a consultant might recall being impressed by someone at a particular company but forget the name or what stood out. AI can retrieve the likely match and the earlier observations, turning years of accumulated institutional knowledge into a searchable asset rather than a fading memory. The productivity gains are substantial. Nathan Clauss, CEO and managing partner of tech-focused search firm Talent SDK, said AI has allowed his sourcing team to accomplish two to three times as much in a day as they could several years ago. The tools integrate with internal messaging and applicant-tracking systems, organise information across platforms, and eliminate manual steps like reading candidate emails to note why someone declined a role. "I haven't fired any of my sourcers," Clauss said. "They've just gotten way more productive." Waterstone's AI was trained on 23 years of data about organisational culture and executive hiring, and can suggest interview questions, presentations, and exercises designed to reveal how finalists think. The technology does not evaluate their performance, though. Parker said it provides the experience while his team applies the judgment. But for all the time AI saves on research and administration, recruiters said it has not altered the stages that require interpretation and persuasion. Jeff Markham, a partner at Parker Remick, said that as more executives claim AI expertise on their profiles, his team still has to verify who actually "gets their hands on the keyboard" by contacting references and backchannel industry sources. Umesh Ramakrishnan, chief strategy officer at Kingsley Gate, said assessing a C-suite candidate can require observing the person outside a formal interview. A recruiter may notice nonverbal behaviour that would never surface in a prepared response. AI, he said, "takes care of everything else," but only a human being can sit with a CEO candidate at dinner and watch for the things that matter most. The courtship stage remains untouched as well. Mike Doud, executive vice president for North America at The Barton Partnership, said winning over a candidate still requires understanding the company, the opportunity, and what might motivate someone to leave their current post. Recruiters need a nuanced understanding of both sides, the client's culture and politics and the candidate's career arc, to determine whether the match will hold. An executive move is "a life-changing event," Doud said, "not simply another job." No model can close that sale. The pattern mirrors what is happening across the broader executive search industry, where firms are racing to build or acquire AI-powered sourcing tools while doubling down on the relationship-driven work that technology cannot replicate. The firms that survive will likely be those that use AI to compress the research phase and redeploy the time saved into the human-intensive stages where deals are actually won or lost.

Why AI Is Forcing Companies to Rethink Executive Hiring

For decades, quality executive hiring has relied on a simple premise: the best predictor of future success is experience. It's an understandable approach. A CFO who has successfully led a public company through an acquisition is more likely to navigate the next one well. A CEO who has scaled a business from $50 million to $500 million has learned lessons that can't be found in a textbook. Experience matters, but it has never been the end of the story. Experience has always been a proxy for something more valuable: the ability to perform in the future. As artificial intelligence reshapes industries, organizations, and the nature of work itself, that proxy is becoming less reliable. The question today is whether experience alone can tell us who will succeed in an environment that looks fundamentally different from the one that produced career experiences. Increasingly, the answer is no. Not by itself and not at the level of analysis most people use. It's time to move past check boxes Historically, hiring teams have understandably focused on what candidates have done. What industries have they worked in? How many years have they held a similar role? Hiring teams thought about experience as a series of checkboxes: Managed a similar scope. Check. Worked in same industry. Check. Had successively larger roles. Check and done. Those questions remain important. What now must change is how we think about experience. The previous way was using blunt assessments of high-level experience. Now, we need to think about subcomponents of experience that built capability for future, different scenarios. Subcomponents such as implementing a large-scale change, grew and led a team, and demonstrated ability to learn new technologies and teach others quickly become important. At an even more granular level: shows multiple signs of adaptation under stress; provides guidance to others and removes barriers, while not jumping in to do the task; and casts vision for why embracing AI is exciting versus frightening, while acknowledging fears appropriately. The pace of technological change means executives are making decisions they have never had to make before. They're redesigning workflows around AI, redefining jobs, navigating ethical questions, managing employees who are experimenting with tools at vastly different rates, and competing against organizations that may be reinventing entire business models overnight. The hiring questions you need to ask No executive has 20 years of experience leading organizations through widespread AI transformation. The best we can do in selecting the right leaders for those situations is to find examples of them implementing other rapid changes and learning quickly while moving with incomplete information. Increasingly, we must distinguish between evidence that someone has done something before and evidence that they possess the capability to do something new. Simply put, organizations should look for different signals when selecting leaders. Organizations should be asking questions such as: These subcomponent characteristics have always factored into hiring decisions. The difference now is that they are becoming more predictive of future success. And the way to go about assessing whether a person possesses these characteristics and capabilities must also shift for many organizations. Organizations that rely on resumes, references, the words of a good executive search firm, and/or a series of conversational interviews will not have a good measurement of what matters for success today. Organizations relying on these outdated approaches: take heed. You must change your approach now. Some organizations have been at the forefront, utilizing psychometric assessments, business simulations, and structured interviews that have always systematically measured essential characteristics. Don't stop growing and changing your approach. While you started with a leg up in this race for talent, you must ensure you are consistently using this approach and not allowing, "but I enjoyed having a beer with him at dinner," or "the reference checks were glowing," to override scientific data. Final thoughts The leaders most likely to thrive over the next decade won't necessarily be those with the longest resumes. They'll be those with the strongest capacity to learn, evolve, and lead through challenges that have no established playbook. Artificial intelligence has reminded us of what experience was always supposed to do: help us predict future performance. As the future becomes less like the past, companies must become more sophisticated in how they evaluate leadership potential. Those organizations that continue hiring primarily for where someone has been will increasingly find themselves disappointed by where that person can take them. Get 1 Smart Business Story delivered straight to your inbox when you subscribe to Inc.'s free daily newsletter.

From intuition to intelligence: How AI is redefining the art of executive search

For most of its history, executive search has been a craft practised in the shadows -- driven by Rolodexes, relationships, and the accumulated instinct of seasoned practitioners. It worked, more or less, because leadership talent moved slowly and markets changed on decade-long cycles. That world no longer exists. Today, organisations are navigating digital transformation, geopolitical disruption, and a structural scarcity of specialised skills,all simultaneously. The leaders they need must be capable of operating across cultures, managing AI-augmented workforces, and driving growth in markets that did not exist five years ago. Filling a C-suite vacancy with the same tools and thinking that worked in 2010 is not merely inefficient, but a strategic liability. This is the gap that artificial intelligence, deployed thoughtfully, is beginning to close. The Science of Talent at ScaleMy doctoral research at ESGCI Paris examined the ways AI is reshaping talent acquisition,not just in speed and reach, but also in the quality and accuracy of the decisions it supports. What I found was both encouraging and cautionary. Encouraging, because AI tools genuinely extend what is humanly possible: they can scan thousands of leadership profiles across geographies, identify non-obvious patterns in career mobility and performance, and surface candidates that a purely network-dependent search would miss entirely. Cautionary, because over-reliance on algorithmic filtering produces its own blind spots, including optimising for the past rather than anticipating the future. At NicheHR Global, we built our SmArt Recruitment™ model precisely to hold these two realities in tension. The Science half uses AI-powered sourcing, behavioural analytics, structured assessments, and global market intelligence to create a rigorous, data-backed universe of leadership candidates. This is not about replacing human judgement,it is about giving human judgement better raw material to work with. The "art" that cannot be automatedBut here is what four years of running SmArt Recruitment across the US and 30+ countries has taught me,and what I explore in depth in my book, The Human Algorithm: the final decision must always be a human one. The art of executive search:reading a leader's motivations, their resilience under pressure, their ability to hold a team together through ambiguity, their genuine alignment with an organisation's values and long-term mission-these are not things an algorithm can determine from a LinkedIn profile and a psychometric score. Cultural nuance alone renders pure algorithmic matching unreliable. A CFO who thrives in a Nairobi-headquartered pan-African business requires a fundamentally different profile to one leading finance transformation for a European SaaS company. Both roles might generate the same keyword matches. Neither would be well served by the same candidate. The art lies in understanding these distinctions at depth and that understanding is built through years of cross-border operating experience, thousands of leadership conversations, and a genuine commitment to knowing both the client's culture and the candidate's true motivations. What boards and founders must rethinkThe organisations that will win the leadership talent race in the coming decade are those that treat executive search as a strategic discipline,and not as a transactional service triggered by a resignation. This means engaging search partners earlier in the strategic cycle, investing in leadership mapping as a continuous process rather than a crisis response, and demanding that search methodologies evolve as fast as the markets they serve. It also means being honest about the limits of efficiency. AI compresses timelines and expands reach but the organisations that consistently attract transformational leaders are those with compelling missions, psychologically safe cultures, and authentic investment in leadership development. Technology can find the right people faster. It cannot make an organisation worth joining. The next frontierWe are entering an era where the most decisive competitive advantage for any organisation is not its product, its capital, or even its technology:it is the quality of its leadership. The firms that understand this and that approach leadership acquisition with the same intellectual rigour they apply to capital allocation or product strategy will define their industries. AI is not the future of executive search. The intelligent, disciplined, human-centred use of AI in service of finding and placing leaders who build organisations that outlast the trends-that is the future. And that future, for those willing to embrace both the science and the art, is already here. (This article is generated and published by ET Spotlight team. You can get in touch with them on [email protected])