AI and Senior Recruitment: Efficiency, Equity, and the Human Edge
Walk into any recruitment meeting today and AI will dominate the conversation. The statistics are compelling: 81% of UK HR professionals are open to AI in recruitment (WorkBuzz / HRReview (2025). State of Employee Engagement), with many genuinely excited about its potential. Nearly 70% of employers now use AI to review CVs (ResumeBuilder.com / Forbes (2024). AI in Hiring Survey), and automation is set to expand even further in 2025.
The appeal is obvious: faster CV screening, automated scheduling, predictive insights, just to name a few. For overwhelmed talent teams juggling hundreds of applications, AI feels like salvation.
But here's where it gets interesting, and where we've seen the biggest disconnect between promise and reality.
When Automation Gets It Wrong
We recently worked with a client whose ATS had ranked a seasoned Operations Director so low in their candidate pool that he wasn't being considered. Twenty-plus years of delivery excellence, a track record of transforming underperforming teams, genuinely impressive commercial results. The issue? No degree. The algorithm couldn't see past that single data point.
We flagged him for human review. He's now in the position and performing in the top quartile of their leadership team.
This isn't an isolated incident. Harvard research reveals that 88% of employers admit their own filtering systems screen out people who could actually do the job (Harvard Business School (2021). Hidden Workers: Untapped Talent). When you're hiring at executive level, that's not just inefficient, it's business-critical talent walking out the door.
"AI should be your co-pilot, not your autopilot."
The Unintended Consequences at Senior Level
AI doesn't start with a clean slate, it learns from historical hiring data. If your past appointments skewed male or white, for example, your algorithm will perpetuate exactly those patterns. Amazon's scrapped recruiting tool famously downgraded CVs containing the word "women's" (as in "women's football captain"). The UK Equality & Human Rights Commission has been clear: employers remain liable for discriminatory outcomes, regardless of whether "the computer did it."
The Experience Expectation Gap
At £50k+, candidates expect white-glove treatment. They want to feel valued, understood, and personally engaged with your organisation. One £120k candidate recently told us: "After three bot reschedules, it felt like the company wasn't serious about me, so why should I be serious about them?" He withdrew from the process entirely.
LinkedIn's 2025 research confirms this sentiment: AI is welcomed by candidates only when it frees up recruiters to spend more quality time with them, not when it replaces human interaction altogether.
The Leadership Story Problem
Executive careers rarely follow neat, linear paths. The most transformational leaders often have the most interesting (and unconventional) journeys. AI struggles with nuance. It can't read between the lines of a career pivot, understand the context behind a two-year gap, or recognise that someone's sideways move into consulting actually demonstrates their strategic thinking.
Real leadership stories are complex. Algorithms prefer simple.
The Emerging Best Practice: Augmentation, Not Automation
The most successful organisations aren't abandoning AI, they're reframing how they use it. The winning approach combines technological efficiency with human insight at critical decision points.
AI as Radar, Humans as Relationship-Builders
Use AI to expand your search horizon. Let it map industry adjacencies, spot hidden talent pools, and identify patterns you might miss. But switch to human recruiters for outreach, assessment, and relationship-building. C-suite candidates won't be impressed by chatbot engagement.
Human Checkpoints on Every "No"
Every AI-driven rejection at senior level should trigger a quick human review. Two minutes of recruiter time can prevent a six-figure hiring mistake (and keeps you aligned with regulatory expectations around meaningful human oversight).
Outcome-First Job Specifications
Stop hiring by proxy. Instead of "10+ years experience, degree in X," focus on outcomes: "Led multi-site transformation, reduced attrition by 5 percentage points, delivered £10M+ P&L responsibility." Train your AI to screen for achievements and impact, not just pedigree and keywords.
The Candidate Concierge Approach
For finalist candidates, assign a single human point of contact. Let AI handle scheduling coordination and process updates behind the scenes, but make sure candidates feel genuinely supported by people who understand their calibre and expectations.
"High-tech gets you speed; high-touch gets you leaders."
What This Means for Your Business
If you're serious about attracting top-tier leadership talent whilst leveraging AI's benefits, here's what we recommend:
Audit Your Funnel: Map exactly where automation makes its first irreversible decision. Insert human review at that point for all £50k+ roles. Document this process (regulators are increasingly asking for evidence of meaningful oversight).
Rewrite Your Requirements: Challenge every "essential" criterion. Is that MBA requirement actually essential, or just traditional? Frame briefs around competencies and outcomes. Expect richer, more diverse candidate pools.
Instrument for Bias: Track who's being surfaced, progressed, and rejected. If patterns emerge that don't reflect your target diversity goals, pause and retune. Don't outsource your ethical responsibilities to your technology vendor.
Measure the Executive Experience: Treat candidate journey quality as a core KPI. Track touchpoints, Net Promoter Scores, and offer acceptance rates. AI should improve these metrics by eliminating administrative friction, not conversational depth.
Upskill Your Hiring Managers: Train them to assess ambiguity tolerance, cultural add (not just fit), and leadership presence. These are uniquely human evaluation skills that no algorithm can replicate.
The We Are Adam Approach
At We Are Adam, we've found the sweet spot between technological capability and human expertise:
AI-Assisted Market Mapping: We use technology to widen our search net and identify hidden leadership talent that others miss, particularly in adjacent industries and non-traditional backgrounds.
Human-Led Assessment: Our structured interviews, outcome-focused scorecards, and nuanced judgement calls ensure we're evaluating the whole person, not just their CV data points.
Candidate Concierge: Every senior hire receives dedicated human support throughout their journey with us, making sure they feel valued and informed at every stage.
This hybrid model consistently delivers what our clients need most: faster shortlists, fewer false negatives, and leaders who not only join but stay and thrive.
The Bottom Line
AI in recruitment isn't going anywhere (nor should it). The technology genuinely excels at expanding search parameters, managing administrative complexity, and identifying patterns at scale. But when you're appointing leaders who will shape your organisation's future, human insight remains irreplaceable.
The businesses getting this balance right are seeing faster, smarter hires who stick around. Those over-automating are losing credibility, diversity, and competitive advantage.
Your mission isn't to choose between human and artificial intelligence, it's to orchestrate them together.
Ready to find that balance in your own executive hiring? Let's talk about how We Are Adam can help you attract transformational leadership talent whilst leveraging the best of both human expertise and AI capability.
