What leaders need to know before delegating executive hiring to AI
Artificial intelligence is no longer a distant or theoretical concept in recruitment – and AI is already now used by recruiters and employers identify, evaluate and appoint new colleagues. But according to Jim Green, head of executive search and selection at Campbell Tickell, while the temptation to automate and even delegate some aspects to AI is understandable, it is not without problems.
Jim Green is an experienced recruitment and talent acquisition expert, having spent more than 15 years in senior recruitment roles across the professional services sector. Joining Campbell Tickell in 2019, he has since come to lead its executive search function – something which, in recent years, has also given him key insight into the ways other organisations have tried to incorporate AI into their recruitment processes.
In particular, Green has seen how the recruitment market for roles at senior and executive level continues to rapidly alter – sometimes without a clear overview of the long-term impacts. In Campbell Tickell’s work across executive and non-executive recruitment, the firm increasingly sees the same questions arise. How is AI being used? What impact does it have? What does it actually mean for those involved?
Top concerns
For candidates and clients alike, the most immediate fear is of ‘invisibility’. In a market where career narratives at senior level are often nuanced and non-linear, there is a legitimate concern that experience can be reduced to overly simplistic signals.
“Candidates may rightly worry that their profile will never reach a human decision-maker if algorithms filter them out at an early stage,” Green explains. “That concern reflects a real shift in the process as concerningly, AI tools are now widely used by some to organise and prioritise candidates before any direct engagement takes place.”
Sometimes, this may be supported by built-in features within recruitment software. According to Green, Campbell Tickell has even heard of “AI interviews being conducted”, as organisations look to expedite the first filtering stage of a recruitment process.
Linked to this, another major concern is around fairness and equalities. As AI is ultimately drawing on a huge catalogue of human data to approximate similar ‘correct’ decisions, research has consistently shown that AI systems can replicate historical hiring patterns, potentially disadvantaging candidates whose careers do not follow traditional trajectories.
Green warns, “Where candidates have moved across sectors, taken career breaks, or built portfolios of experience, AI may flag this as a material risk. In other spheres of life, it has become very clear that AI may discriminate by gender, ethnicity, and others with protected characteristics.”
Alongside this is a broader concern about misrepresentation: the idea that algorithms lack the ability to understand context, scale and impact in the way a human conversation can. Employers may also have a further set of concerns relating the quality of documents produced for them by their executive recruiters.
“Anecdotally from conversation with clients,” Green continues, “we have heard more than one story of poor practice in this area, such as recruiters presenting reports containing ‘AI hallucinations’ within candidate write-ups. Conversely, we have become aware of job applicants using AI to refine their CVs, or to produce gushing supporting statements. All we would say here is that use of AI in this way is not necessarily to the benefit of the candidate!”
The value and limitations of AI in recruitment
There are still applications where AI can add value during a recruitment process, though. The important thing is to be aware of these risks – using the technology “carefully and sparingly” to ensure it is a “positive force”.
“It tends to be most effective in supporting the research and mapping phases of a search, as a supplement to the recruiter’s own headhunting,” Green notes. “Advanced tools can analyse vast datasets to identify potential candidates, including individuals who are not known to be actively seeking new roles, but whose experience aligns with the requirements of a position. This expands the reach of search activity far beyond traditional networks and, in theory, allows for a more systematic exploration of the talent market.”
This kind of use comes with the firm guardrail that human search is “only being supplemented, not supplanted”. In this way, there is even a case to be made that “use of AI may broaden the diversity of candidate pools”, usefully extending and deepening headhunting reach.
Green expands, “Executive recruitment is inherently complex. It involves assessing not just capability, but judgement, cultural alignment, and the ability to navigate ambiguity. These are dimensions that remain difficult to quantify. Current AI tools are simply not designed to replace the nuanced evaluation required. Even the most advanced systems struggle to interpret context, interpersonal dynamics, or the subtle indicators of leadership potential that experienced search professionals identify. Conversation, interaction, and informed judgement, are areas where human expertise remains essential.”
So, when it comes to evaluating candidates for roles at the most senior levels, AI must play “a much more limited role, if any role at all”. No evaluation or ranking of candidates “is ever conducted using AI” at Campbell Tickell, Green confirms, while the human judgement of the firm’s consultants remains front and centre of the firm’s executive hiring support.
He concludes, “From our perspective, the role of AI in executive search is clear, and limited. It can be a useful tool for expanding reach and enhancing insight. But its value lies in supporting, not replacing, the core human disciplines of search: deep market knowledge, rigorous assessment and trusted relationships.”
