Accepting AI in recruitment processes

AI in recruitment isn’t coming – it is already here. And in executive search, where the stakes are high and the margins for error are slim, it is becoming essential. But while the hype is loud, the conversation often misses the nuances that matter: how do you use AI to get the best results for everyone involved – you, your client, and your candidate?

The answer isn’t to fear it – but to understand where it can genuinely add value. Done right, AI doesn’t replace your expertise. It enhances it.

Sourcing:

The days of starting every search from scratch are gone. AI tools have transformed the sourcing process by mapping talent landscapes in seconds. While that level of speed is more commonly associated with high-volume recruitment, its relevance to executive search is growing fast.

Odgers proprietary platform, OBDynamics, is a striking example. Built on over 1.1 billion records, it offers everything from market mapping to skill distribution and analysis. In one recent search, they used it to find a data scientist with specific language skills, experience at a Silicon Valley firm, and connections to western India, completing the search in six weeks instead of the year it might have previously taken[1].

Spencer Stuart is also pushing boundaries. Their partnership with Qlu.ai helps automate the discovery of emerging companies and individuals by analysing over 10 billion data points – giving their teams a broader, faster, and more strategic view of leadership talent. Crucially, this application of AI supports, rather than replaces, the role of the consultant[2].

Looking farther afield, Mastercard have also grown its internal talent community from under 100,000 to over one million profiles in just one year using AI-enabled CRM campaigns, further highlighting the value of AI use in talent pipelining[3].

Screening:

The streamlining techniques mentioned above are significantly less effective if a firm doesn’t then have effective screening. But AI tools now offer meaningful support in helping to pre-screen talent. From scanning CVs against role criteria to analysing public profiles and digital behaviour, AI can help you generate a more targeted longlist, faster.

At Korn Ferry, consultants are already using generative AI to summarise job descriptions and candidate CVs side by side. This helps reduce admin time and generates cleaner comparisons, which is particularly useful when reviewing longlists across global markets[4].

Russell Reynolds takes this further. Their AI Quotient framework assesses whether leaders are truly ‘AI-ready’ – looking at curiosity, adaptability, and strategic vision[5]. This is a step beyond screening and capability assessment and is particularly relevant as boards now demand leaders who can navigate digital change.

For other firms, AI supports the long-list stage, helping firms to make their desired short-lists much faster. Electrolux reported that AI-powered scoring and one-way interviews helped reduce their time-to-hire by 9% and halve the number of incomplete applications[6]. While this case is from a volume recruitment setting, the principles apply: AI can help filter early-stage candidates and surface red flags, freeing you to focus your time and effort on the candidates with the most promise.

Process automation:

Where AI really shines is in task automation. Things like interview scheduling, document formatting, and pipeline updates can be tedious and time-consuming. Automating these processes gives consultants more time to focus on what matters: building relationships and managing outcomes.

For example, Mastercard used AI to schedule over 5,000 interviews – 88% of them within 24 hours. This reduced the time to schedule by over 85%, freeing up consultants to focus on the best performing candidates[7].

This doesn’t mean losing personalisation. In fact, it means creating space to deliver better personalisation. Imagine an automated follow-up that frees up time for you to tailor the final shortlist or spend more time prepping your candidate for an interview.

Candidates are using AI too

And it isn’t just recruiters using AI. Candidates increasingly use tools like ChatGPT to refine CVs, write bios for boards, or prepare for interviews. Some firms, like Arctic Shores, have trialled AI-powered assessments that analyse responses for tone, structure, and even leadership style[8].

But this approach carries risk. AI-generated content may appear polished but can mask genuine skill gaps. Several firms – including Amazon – are now adding in AI review and audit process to maintain quality control during their hiring process[9].

AI may help generate better-looking candidates on paper, but it still takes human insight to assess authenticity, potential, and cultural alignment.

The bottom line?

Use of AI in executive search isn’t about automation for automation’s sake. It is about using technology to enable better decisions, faster execution, and successful placements. The most forward-thinking firms – Odgers, Spencer Stuart, Korn Ferry, Russell Reynolds, and many more – aren’t using AI to replace consultants. They are using it to augment them.

AI offers many things, but it doesn’t offer trust. It doesn’t interpret company dynamics, predict cultural alignment, or understand when a candidate might be the right person at the wrong time. That is where executive search earns its value.

So, there is no point asking whether AI will change the way you work. It already has. The better question is: What AI tools are game changers for you, and how can you use them to deliver better outcomes?

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References:

[1] AESC (ND)

[2] Spencer Stuart (2024)

[3] Phenom (2025)

[4] Korn Ferry (2024)

[5] Russell Reynolds (2025)

[6] Phenom (2025)

[7] Phenom (2025)

[8] Indeed (2025)

[9] Institute of Student employers (2025)

Accepting AI in recruitment processes

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