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By Carson Kolb
When Every Executive Needs to Speak AI, Not Just the CIO The finance chief who could once leave technology strategy to the technology team is now sittin...
The finance chief who could once leave technology strategy to the technology team is now sitting in budget meetings where half the questions turn on whether an AI-driven tool will actually deliver what the vendor promised. The operations leader who used to evaluate a new workflow on staffing and throughput is now expected to weigh in on whether an algorithm should touch that workflow at all. This shift is happening across the entire senior team, and it is happening fast.
AI has stopped being a specialist concern. For healthcare leaders whose titles have nothing to do with information systems, that is a real change in what the job demands.
For most of the last decade, an organization could concentrate its AI fluency in a few roles and get by. The people who understood the models sat in one part of the building, and everyone else deferred to them. That arrangement is quietly ending.
Boards now ask clinical, financial, and operational leaders how AI is changing their function, and "that is a question for our technology team" is no longer a satisfying answer. The expectation is that a senior leader can speak to what the technology means for their part of the enterprise, what it costs, what it risks, and where it genuinely helps.
None of this requires an executive to become an engineer. It does require the ability to ask good questions, challenge a confident vendor, and understand enough to know when an answer does not hold up.
Consider a service-line leader deciding whether to adopt a documentation tool that promises to cut administrative burden. Two years ago that was largely a technology evaluation. Now the leader is expected to reason through the clinical implications, the effect on staff, the accuracy claims, and whether the promised savings are real or theoretical.
The same pattern shows up in how leaders allocate capital, contract with partners, and think about workforce planning. A decision that once had a clear owner now pulls in several executives who each need enough fluency to hold their piece of it. Strategy, growth, operations, and performance all run through this now, which means the fluency has to be shared across the leadership table rather than parked in one office.
That is a different kind of leader than the market was hiring for a few years ago. The strongest candidates today combine deep functional expertise with genuine comfort in these conversations, and organizations are beginning to screen for exactly that blend.
Some leaders have leaned into this. They can articulate where AI creates value in their domain and where it introduces exposure, and they can do it without hiding behind jargon or waving it away. Others are more hesitant, not because they lack ability, but because the expectation arrived faster than the opportunity to build the skill.
That gap matters most when an organization is making a senior hire. A leadership team that already has this fluency needs a new executive who can match it. A team still building the capability may need someone who can help raise it.
Getting that read right is part of what a serious search actually evaluates.
This is one reason the definition of a strong candidate keeps shifting. The functional resume still matters enormously, but the ability to lead through technological change now sits alongside it as something organizations weigh directly.
Start with the questions you already know how to ask in your own domain, then apply them to any AI tool put in front of you. What problem does this solve, who does it affect, what happens when it is wrong, and how will we know if it is working. Those are leadership questions, and they do not require a technical background to ask well.
Spend time with the people in your organization who do understand the technology, and treat those conversations as a two-way exchange rather than a briefing. You bring the operational and clinical judgment they may lack, and they bring the technical grounding you are building. The leaders who close their own fluency gap fastest tend to be the ones who make those conversations routine.
Be honest about what you do not yet understand. A senior leader who asks a direct question about how a model actually works signals confidence, not weakness. The executives who struggle are usually the ones performing certainty they do not have.
When an organization opens a senior search now, the specification quietly includes this capability whether or not anyone writes it down. A candidate who checks every functional box but cannot engage with how technology is reshaping the function is a harder sell to a board than they were even a short while ago.
This is where a thoughtful search process earns its keep. Understanding an organization's current level of AI fluency, and finding a leader who fits or improves it, is exactly the kind of nuance that separates a real fit from a resume match. The team at Carson Kolb spends a great deal of time on that gap between what a title implies and what an organization actually needs, and this is one more dimension where that distinction shows up.
The leaders who thrive over the next several years will be the ones who treated AI fluency as part of the job rather than someone else's department. The organizations that hire well will be the ones that looked for it on purpose.