It was only a matter of time, of course. AI has ‘arrived’ in executive search.
For decades, one of the most labour-intensive parts of a search assignment has been research: mapping the relevant company landscape and building a comprehensive longlist of potential candidates. Over the past six months, we’ve examined a number of AI tools that claim to be able to do this in a fraction of the time.
I was delighted to find that most are embarrassingly bad, but at least one seems seriously impressive (I say ‘seems’ because we’ve had a demonstration, not a trial). Give it the right prompts and it can scan multiple data sources and produce a list of hundreds of potentially relevant executives in minutes.
The question is: if AI can now find candidates, what exactly are headhunters for?
Finding ≠ Assessing
I think the answer starts with an important distinction: AI is becoming very good at finding people, but the greatest value we provide at JMA is assessing people.
AI’s ability to identify hundreds of executives whose profiles potentially fit the brief certainly has value. But a list of hundreds of potential targets isn’t executive search. In some ways, it’s simply a new problem.
Who should we discount? Who deserves serious investigation? Who is genuinely exceptional? And which candidates who aren’t on the list should be?
Quality Over Quantity
Before we start looking for candidates, we spend time deciding where (and where not) to look, and why. The best candidate might sit in an adjacent industry, a different geography or a different function entirely. What matters is whether they have solved a similar problem, led through a comparable stage of growth, or transformed an equally complex organisation.
Two executives can have near-identical CVs but in reality be remarkably different: one may have transformed the business they led; the other may simply have been a passenger while somebody else did the heavy lifting. You often can’t tell the difference on paper.
That’s why, at JMA, no candidate makes it onto a longlist simply because an algorithm says they match the spec. A Partner has to allow them on.
It may sound old-fashioned, but it’s fundamental to the quality we aim to bring clients. We consider who has succeeded in comparable circumstances and what the client needs; not only immediately, but in three to five years, in the context of its strategy, culture and leadership.
This creates a paradox: the easier candidates become to identify, the more commoditised and less valuable identification alone becomes. The value lies in distilling hundreds of potential targets into a shortlist of exceptional people who are culturally right, genuinely motivated and able to make an impact. That takes real-world context, pattern recognition built over decades, and judgement that AI can’t yet replicate.
Looking Beyond the CV
Moreover, sometimes there’s a ‘unicorn’ working in an industry or company the client has not asked us to consider: an executive whose particular experience makes them an exceptional fit. Good search involves knowing how to interpret a brief, and when to challenge it.
The same applies to candidates. What somebody can become isn’t necessarily obvious from what they’ve already done. A future GM, for example, may not yet have been a GM. Their CV might never make an algorithm’s list, yet a headhunter who knows them can recognise the breadth, judgement, commercial instinct and leadership capability indicating they could excel in the right GM role.
That’s why interviewing matters: we’re not simply validating what’s on a CV; we’re looking for what isn’t.
Uncomfortable Questions for Search Firms
The advent of AI in executive search poses some uncomfortable questions. For many years, research was expensive and time-consuming. Knowing who worked where, and being able to find people, represented a meaningful part of a search firm’s intellectual property. Increasingly, it doesn’t.
And if AI now allows headhunters to examine a vastly larger universe of companies and executives more quickly, clients should naturally expect not just a quicker process, but more imaginative candidate pools, broader market coverage and fewer blind spots. That expectation may prove uncomfortable for firms constrained by extensive off-limits agreements.
AI Will Make Executive Search Better and More Human
So, will we harness the power of AI at JMA? Absolutely. If AI can help us scan the market more comprehensively and identify potential candidates more quickly, we’d be fools not to.
Interestingly, I don’t think AI’s greatest impact will be to replace research teams. It will make knowing ‘what great looks like’ even more valuable, while allowing us to spend more time on the things that matter: understanding the client, refining and when necessary challenging the brief, surfacing exceptional profiles through multiple routes, persuading candidates to engage, interviewing for what isn’t obvious, assessing talent, and giving strategic, honest advice.
AI shouldn’t simply make executive search faster. It should make it better.
Ultimately, AI won’t make executive search any less human. It will allow us to concentrate even more on why clients come to us in the first place.