AI is transforming executive search but not by replacing recruiters.
In a recent conversation, Fahad Jalal spoke with Ken Dickie, CITO at Leathwaite, to explore what truly needs to change for AI to deliver value. They go beyond automation, discussing data quality, adoption, behavior change, candidate experience, trust, compliance, and what distinguishes a retained search firm from one that simply builds lists.
Executive search firms are paid for advisory, not data processing. Yet much of their time is consumed by repetitive tasks. When AI handles this low-value work, firms gain speed, deeper market insight, stronger client relationships, better candidate care, and more time for work that truly wins mandates. But without careful adoption, governance, and bias control, AI can backfire. The firms that succeed will rethink their workflows, not just add tools.
Key takeaways
- The main challenge isn’t AI itself it’s getting people to use it and redesign workflows.
- Firms are hired for solving leadership problems, guiding decisions, and delivering results not for long lists.
- AI works best when it removes repetitive tasks, giving people time for judgment, trust-building, and client advisory.
- Knowledge trapped in heads, notes, or spreadsheets limits AI’s usefulness.
- Candidate experience is crucial; today’s candidates can become future clients.
- Face-to-face meetings still matter in trust-based work.
- Firms that succeed with AI are not just faster they have better compliance, bias controls, and data handling.
- Lower barriers to entry help agile small firms but challenge traditional firms relying on legacy processes.
Technology has been shaping executive search for years, and AI is just the next step.
Ken Dickie explains that AI is not the first major change in the industry. Executive search has evolved from relying on “black-book” relationships to using connected, data-driven workflows. At firms like Spencer Stuart, this wasn’t just about buying software it meant building unified systems, improving communication across offices, and making information easy to access and use.
Search is global, but it always depends on local context. A system only works if it helps people understand markets, families, relocation challenges, culture, and fit not just resumes.
Why Executive Search Firms Are Betting Big on AI
Ken Dickie points out that when firms are personally invested in results, the benefits of better technology become clear. In partnership-driven firms, improvements in data, process, and execution quickly translate into better outcomes, stronger client delivery, and higher revenue. That’s why leading search firms continue to invest in advanced systems, even if the path isn’t always straightforward.
Today, AI is more than a productivity tool. It is reshaping how quickly firms can move from understanding a brief to analyzing the market, building a candidate pool, and providing meaningful advisory work. This goes far beyond saving a few minutes of administrative work.
Firms are looking for more than just tools. They want firm-level leverage: greater capacity, faster cycles, broader market insight, better candidate coverage, and more consistent execution across the organization.
Adoption, Not Technology, Is the Real Challenge
Ken is blunt that transformation is usually not blocked by the technology itself. It gets blocked by behavior. People resist new systems, keep side spreadsheets, rely on notebooks, store context in their heads, and default back to the workflows they already trust. That is why adoption is harder than implementation. A firm can buy a tool in a quarter. It can take much longer to actually change how people work.
Fahad Jalal adds that even when a search demo looks easy, users often fail to reproduce the results and blame the tool. The real work isn’t just building strong models it’s creating a user experience that makes the system intuitive for non-technical users. In executive search, this is more important than many AI vendors realize.
When workflows aren’t intuitive, users create workarounds. As soon as that happens, the system loses value.
Fear of Automation Is Real But Misunderstood
It’s natural for people to worry that AI will replace them. Leaders often avoid discussing it, fearing they might trigger anxiety among research teams or associates. Ken Dickie acknowledges this concern, noting that some firms might misuse AI as a shortcut and that can create real stress.
But the better way to think about AI is as a tool to expand the team’s capabilities, not reduce headcount. One researcher can work as if they have ten capable assistants behind them, allowing for more searches, pitches, market coverage, and growth.
AI doesn’t just compress work it amplifies the impact of the people already in the firm. The goal is not less human involvement, but more leverage per person.
Executive Search Is Advisory, Not List-Building
Executive search is more than producing candidate lists it is retained advisory work. Ken Dickie highlights the difference between contingent recruitment and retained executive search. The distinction isn’t just about fees. Retained search involves deep diagnosis and advisory: understanding why a business needs a CFO, why previous CFOs failed or left, whether structural issues exist, and if the role is properly defined.
At the top end of the market, clients don’t pay for admin work. They pay for insight: understanding leadership challenges, shaping the brief, analyzing the market, building confidence, and guiding decisions.
This also explains why AI won’t replace executive search. Clients value judgment, challenge, trust, interpretation, and process control far more than a simple list of names.
The Best Use of AI: Remove Process Drag, Keep Humans at the Core
Fahad Jalal highlights a key point: search firms are not hired for data processing, yet much of their time is spent on building lists, reconciling information, validating data, moving records, and creating outputs clients often see as “proof of work".
Ken Dickie agrees: if AI handles these repetitive, low-value tasks, firms can focus on what really drives value building relationships, advising clients, converting candidates, and supporting decisions. That’s where margins, client value, and outcomes improve.
Many conversations about AI miss this point. Firms often chase small productivity gains at the edges, but the real opportunity is workflow redesign. Coordinating the full process from brief to research, outreach, and follow-up creates structural gains, not just incremental improvements.
Candidate Experience Is Pipeline, Not Branding
Ken Dickie makes a key point: every candidate is a potential future client. This isn’t just sentiment it’s commercial logic. The people you engage with today may hold bigger roles tomorrow, influence hiring decisions, control mandates, or shape your firm’s reputation long after the current search ends.
Fahad Jalal adds that top-performing billers generate a significant portion of future business from past candidates, while lower performers do much less. This shows how elite operators view the market as a long-term game.
AI can support this process quietly but effectively. By reminding teams to follow up, flagging stalled communications, maintaining relationships, and reducing missed opportunities, AI doesn’t make search less personal it helps firms behave like their most effective partners.
In-Person Meetings Still Matter
Despite all the talk about automation, dashboards, and AI workflows, Fahad Jalal found that partner performance still correlates strongly with the number of meetings, especially in-person. Ken Dickie agrees that trust builds fastest in direct, face-to-face interactions.
Executive search involves sensitive, high-stakes decisions. Clients need to trust the adviser, and candidates need to trust the person representing the opportunity. AI or better workflows do not replace this trust; they should free people to spend more time in the room, not less.
Compliance Separates Serious Firms
Ken emphasizes that AI carries risks such as bias, black-box logic, explainability, data handling, and legal obligations. He is not against AI; he is against sloppy AI. In regulated industries and high-stakes searches, firms cannot rely on “the model said so".
Properly governed AI can improve fairness and reduce legal risk by detecting gaps, testing assumptions, and highlighting imbalances. But this only works if governance is built into the workflow from the start. The next competitive advantage is not just speed; it is trustworthy speed.
AI Changes the Market
AI lowers the cost of market mapping, research, and structured information. This reduces some historic advantages of large incumbents. Agile boutiques can scale faster, and new entrants can appear credible sooner. Legacy firms that rely on structure or assume data access is a durable moat face challenges.
The market may grow, but it will also become more competitive and less forgiving.
Closing Advice
AI should be seen as a threat to waste, not to the industry itself. The human core of executive search defining the brief, building trust, reading nuance, selling opportunity, managing stakeholders, and guiding decisions remains essential.
Firms that succeed will focus on three things. First, they will redesign workflows instead of layering AI onto broken processes. Second, they will treat data discipline as a strategic advantage, not just an admin task. Third, they will use AI to create more space for human judgment, not less
Key Quotes from Ken Dickie
- "The biggest problem right now is the adoption."
- "It's not just a 'we want a CFO,' right?"
- "You don't build trust over Zoom"
- "A candidate is a future client."
- "We're not talking about co-pilot here. We're talking about changing the ways you do business."
Practical Next Steps
- Audit your workflow and separate process drag from actual value creation.
Be honest about how much time still goes into long-list production, record cleanup, and internal admin. - Fix your data capture habits before expecting AI to perform well.
If key context still lives in heads, notes, and spreadsheets, the system will always underperform. - Redesign candidate experience as a growth lever. Put clear ownership around follow-up, interview feedback, and relationship continuity.
- Treat adoption as a product problem, not a training problem alone.
If the workflow is not intuitive, people will create shortcuts and shadow systems. - Build governance into the system from the start.
Bias checks, compliance layers, explainability, and audibility cannot be afterthoughts. - Protect more time for in-person relationship-building.
AI should reduce admin so your best people can spend more time with clients and candidates. - Pressure-test your moat.
Ask what still differentiates your firm if better mapping, synthesis, and market research become easier for everyone.
About the guest
Ken Dickie is CITO at Leathwaite and has worked across financial services, executive search, retail, sports wagering, insurance, and compliance. In this conversation, he shares a practical operator's view on where AI creates real value inside executive search, where firms still get stuck, and why trust, data quality, and adoption matter more than hype.
Want early access?
QLU is building AI-native workflows for executive search teams that want to move faster without losing the human edge. If you want to see what that looks in practice from search execution and market mapping to relationship intelligence and faster candidate workflows book a demo and see it live.
Ready to see how? Book a demo