When generative AI was unleashed on the world, I started telling every senior leader I worked with the same thing: get AI fluent, now, before it’s optional. Not because any client was asking for it yet. Because I could see where the conversation was heading, and I didn’t want the people I placed to be caught flat footed.
For a while, that advice lived mostly behind the scenes, something I’d say quietly in a coaching conversation or a debrief, not something clients were putting in a job description.
Looking back across the executive searches we’ve run this year, what I expected is now showing up in the data. A pattern emerged that nobody wrote into a single job description. Half of our C-suite searches ended with the client choosing the candidate who had real AI fluency, even when AI wasn’t listed as a requirement, wasn’t part of the Role Alignment Profile, and in some cases wasn’t even discussed until late in the process.
These were C-Suite roles in commercial leadership (revenue/growth) and finance, in healthcare technology. And AI Fluency tipped the scales in the final analysis.
What “AI fluency” actually meant
This is the part that matters most, because it’s easy to wave at “AI experience” as a vague buzzword. In practice, across these searches, it meant something specific: candidates who could speak to how AI changed the way their function operated, and who could help the broader leadership team figure out where AI belonged in the company’s strategy and product, not just its internal workflows.
A few examples make the pattern concrete.
In one search for a classic CxO role, someone who needed to navigate a large, established organization while staying nimble, the client narrowed the field to two finalists. What ultimately decided it wasn’t the candidate’s ability to run AI tools internally. It was that this person could make real decisions not just about AI-driven workflows for the org, but about which products and services the company needed to build real AI capability into. The client wanted a strategist, not a power user.
In another search, the requirement didn’t even start as an AI requirement. At the outset, the client’s language was closer to “tech curious” than “must have AI experience.” By the end of the process, that had shifted considerably. The client wanted someone who could build AI into their business unit’s workflow for efficiency, and who could also help identify where AI belonged in the broader product and strategy conversation. The bar moved during the search itself, which tells you something about how fast expectations are shifting even within a single hiring cycle.
A third search, for a small, early-stage company still finding its footing, ended the same way. The client chose the candidate with AI fluency specifically so that AI could be part of how the company was built from the ground up, not bolted on later.
Three different companies, three different stages, and the same underlying decision.
Why this is showing up in revenue and finance roles first
It would make intuitive sense if this pattern were concentrated in technical roles. It isn’t. The searches where this showed up most were Chief Revenue, Chief Growth, Chief Commercial, and Chief Financial roles, functions where the connection to AI has historically been assumed to be indirect at best.
What’s actually happening is that AI has stopped being a technology decision and started being a business model decision. Revenue and growth leaders are being asked to figure out how AI changes what the company sells, how it prices, and how it competes. Finance leaders are being asked to model what AI actually does to margins, headcount, and forecasting, not just adopt a tool. Boards are quietly deciding that whoever runs these functions needs to be fluent enough in AI to lead that conversation, not just react to it.
The healthcare tech concentration adds another layer. It’s an industry moving fast on AI adoption while carrying real constraints around data, regulation, and trust, which makes AI fluency in commercial and financial leadership less of a nice-to-have and more of a requirement for the business to function credibly.
What this means if you’re building a leadership team
The clearest signal from this pattern is that job descriptions are lagging behind what companies are actually selecting for. That gap creates risk on both sides.
For companies: if AI fluency isn’t explicitly on your scorecard, you may still be selecting for it implicitly and inconsistently, without a clear way to compare candidates on it. That’s a hard way to make a high-stakes hire.
For candidates: the absence of AI language in a job posting doesn’t mean it won’t be the deciding factor. Several of the searches above didn’t lead with it. It became the differentiator anyway.
A few questions worth building into future scorecards, based on what actually separated finalists in these searches:
- Has this person changed how their function operates because of AI, or only used AI as a tool within an unchanged process?
- Can they speak concretely to where AI belongs in the company’s product or service offering, not just its internal operations?
- Have they had to make a real strategic call about AI, with tradeoffs, rather than just championing adoption?
The takeaway
None of the companies in these searches set out to hire for AI fluency. They set out to hire a strong CRO, a strong CFO, a strong operator. AI fluency turned out to be what separated the finalists anyway, often without anyone naming it as the deciding factor until after the fact.
That’s usually how the most important hiring shifts show up first: not in the job description, but in the decision. I was telling candidates to prepare for this moment before anyone was asking for it. Now the data backs it up.
If you’re building out a leadership team this year, it’s worth asking about this directly rather than waiting for it to become a standard line item. By the time it’s on every scorecard, it won’t be a differentiator anymore.
