How to figure out if an executive is AI fluent

AI fluency is quickly becoming the new leadership divide: Some executives are already embedding it into strategy, while others are still asking what it means. The gap is widening—and it’s shaping who gets hired to lead.

That’s why AI fluency is becoming a top priority in leadership searches. Not deep technical mastery, but a practical understanding of how these tools work and where they apply. Companies want leaders who aren’t just talking about transformation but are actively engaged in it. People who’ve run pilots, evaluated risks, collaborated with product and tech, or led adoption efforts in their function.

They don’t need to be engineers. But they do need to know what these tools can (and can’t) do—and how to help others use them responsibly.

How executives are actually using AI

Executives at the forefront are already putting AI to work in meaningful, strategic ways. According to Salesforce, top-tier leaders are leveraging AI for critical tasks: running high-stakes market analysis, stress testing new business ideas before launch, and anticipating market shifts before they happen.

A recent TechRadar piece reports that 74% of executives now trust AI’s input more than that of colleagues, with 44% “willing to let it override their own decisions.” AI has become more than a dashboard—it’s a boardroom copilot.

Behind the scenes, back-office leaders are increasing AI spending: 92% of executives surveyed plan to ramp up investments in AI over the next three years, and 55% expect a boost of at least 10%. Yet execution is uneven. A recent IBM study found that while CEOs expect AI investment growth to more than double in the next two years, only 25% of AI initiatives have delivered expected ROI—and just 16% have scaled enterprise-wide. Similarly, PwC found that while 79% of senior executives are adopting AI agents, many see success only when implementations are tied directly to measurable productivity gains in targeted areas.

But high adoption doesn’t always mean high impact. MIT researchers recently found that 95% of generative AI pilots fail to deliver measurable ROI, often because they’re launched without clear objectives or integration into core workflows. Meanwhile, another study warns of “workslop”—a proliferation of low-quality output from poorly managed AI usage.

These findings underscore a growing reality: AI fluency among leaders isn’t just a nice-to-have—it’s the difference between pilots that fizzle and initiatives that scale. Leaders who understand both the capabilities and constraints of these tools are far better equipped to unlock value while avoiding the hidden costs of misuse.

What leaders who use AI well do differently

Here’s what separates AI-fluent executives from the rest:

• Hands-on experimentation—These leaders gain firsthand experience with generative AI—understanding not just the tech’s capabilities, but its limitations.
• Visible, scalable fluency—Harvard Business Publishing’s new study shows that employees with fluency aren’t just dabbling—they integrate AI into daily workflows. In “best-in-class” organizations, 98% of AI-fluent users are confident in using tools and report significant team performance gains.
• Strategic, not siloed, use—AI isn’t just owned by the CTO. Leaders from across the organization—from chief human resources officers (CHROs) to CFOs—are embedding AI literacy into their domains, turning it from a technical specialty into leadership capability.
• Intentional oversight—Even when AI is applied, responsible use is rare: Infosys found that 95% of executives experienced AI mishaps, and only 2% of firms meet responsible-use standards.

Don’t just hire faster—hire toward the future

Most companies today aren’t ignoring AI—they’re trying to figure out how to keep up. They know they can’t afford to fall behind, especially when competitors are investing aggressively in AI across operations. The challenge is finding people who can lead that shift—not just within their function, but across the business.

That’s the conversation I’m having with clients right now. Not “how do we hire someone fast?” but “how do we hire someone who can take us where we want to go?”

Takeaways for talent teams and leaders

• Screen for real fluency. Ask candidates to share where they’ve deployed tools, navigated roadblocks, coled adoption, and managed both opportunity and risk.
• Favor hands‑on experience, not academic abstraction. AI fluency is demonstrated, not talked about—from pilot artifacts to team processes.
• Insist on governance and oversight. Pair fluency with accountability. Use AI, yes—but responsibly.
• Prioritize curiosity and adaptability. Leaders don’t need to master every tool, but they do need to stay agile, ask questions, and foster a culture of experimentation. AI will keep evolving, and so must the people leading its adoption.

Leaders aren’t expected to be coders. But they must know how to marshal AI, translate insight, and guide adoption—balanced with judgment. The future of leadership is not running from change. It’s defining it.

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