What Are We Really Hiring For?

The Skills Behind the Skills

Given the market and the volatility in tech, I find myself reviewing job descriptions for leadership roles quite often. Everything from Chief of Staff positions and Operations leaders to Sales executives and Strategy roles.

There is a pattern emerging.

Nearly every one of these roles is looking for some version of the same thing:

• AI experience preferred
• AI fluency required
• Experience leading AI transformation
• Ability to leverage AI to improve business outcomes
• AI-first mindset

The wording varies, but the message is clear: organizations want leaders with AI experience...or at least, that's what the job descriptions say.

But the more I read, the more I find myself wondering whether we're repeating a pattern we've seen before. Those of us who entered the workforce in the late 1990s and early 2000s might remember when job descriptions routinely listed requirements like:

• Microsoft Word proficiency
• Advanced Excel skills
• PowerPoint experience
• Internet research capabilities

At the time, these were meaningful differentiators. Not everyone had those skills (I know, crazy). Organizations were trying to identify candidates who could effectively use emerging workplace technology so they could keep pace with the changing nature of work.

Today, those requirements feel almost silly.

Not because the skills aren't important, but because they've become expected, they're table stakes. We assume professionals know how to use a computer, communicate digitally, and navigate common productivity tools. The technology didn't disappear. It became embedded in the way work gets done.

I suspect AI is following a similar path...the challenge is that we're in the awkward middle.

Organizations know AI matters. They know it will change how work gets done. What they're less clear on is what capability they're actually looking for in the leaders expected to navigate that change. I think part of the confusion is that we're talking about two very different things.

On one hand, organizations absolutely need leaders who own AI strategy, governance, risk, infrastructure, and implementation. We're seeing the rise of Chief AI Officers and expanded AI responsibilities within CIO and CTO organizations for exactly this reason. AI requires leadership, accountability, and governance at the enterprise level.

On the other hand, we're also seeing AI requirements appear in leadership roles that have little to do with owning the technology itself. Operations leaders, Chiefs of Staff, Sales leaders, HR leaders, Communications leaders, and many others are increasingly being asked to demonstrate AI fluency as part of the job.

Those are two very different expectations, and even seasoned executives and recruiters are struggling to make sense of it.

Research is increasingly drawing a distinction between AI expertise and AI fluency. The former is about building, governing, and implementing technology. The latter is about understanding its implications, asking better questions, evaluating risk, and helping people adapt. The distinction matters because most leaders won't be responsible for building AI, but many will be responsible for leading through its impact.

All that said, I don't believe every company needs dozens of AI leaders. I do believe every leader needs a level of AI fluency if AI is part of their organization's strategy (which it should be).

Not because they need to become technologists. Because they need to understand how technology changes work. The technology matters, but it isn't the point. The point is what a leader does when the technology changes and how they lead through it.

The leaders succeeding today aren't necessarily the ones with the deepest technical expertise. They're the ones who are willing to learn, experiment, adapt, and help others do the same.

They ask different questions:

What problem are we trying to solve? What assumptions are we making? How might this change the way work gets done? What risks should we account for? How do we help people build confidence while maintaining accountability?

These aren't AI skills. They're foundational leadership skills.

The same capabilities that helped organizations navigate cloud computing, mobile technology, remote work, digital transformation, and countless other shifts are relevant still.

The tools may be different, but the underlying challenge is not. And this is where hiring conversations become particularly interesting.

Too many interview processes focus heavily on AI exposure:

• What AI tools have you used?
• Tell me about your AI strategy.
• Describe your AI implementation experience.
• How have you leveraged AI to drive business transformation?

These questions aren't inherently bad, but they often measure proximity and assume that access to AI initiatives is the same thing as the ability to lead through change. I'm not convinced those are the same capability.

A candidate may have extensive AI experience simply because they happened to be assigned to a high-profile initiative. Another may have spent an entire career navigating ambiguity, learning new domains, and leading through change but lack the specific AI examples recruiters are looking for.

Which one is better equipped for the next wave of change? I'm not sure we always ask.

Personally, I'd be more interested in questions like:

Tell me about a time you had to solve a problem in an area where you had little expertise. How did you learn? Who did you involve? What assumptions did you challenge? What was your approach when there wasn't a clear roadmap?

These aren't new questions (or at least they shouldn't be). But the answers tell us something much more valuable than whether someone knows how to write a prompt. They reveal how a person thinks.

I tell leaders this all the time: today's AI won't be tomorrow's AI.

The tools will evolve. The platforms will change. Entire categories of technology will emerge that we can't yet predict. The most valuable capabilities you can build your organization around are the ability to learn, adapt, evaluate, experiment, and lead responsibly through uncertainty.

Perhaps that's what organizations are really trying to describe when they add AI requirements to every job description - not expertise in a specific technology.

The ability to adapt and effectively lead when the technology inevitably changes.

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Sources & Further Reading

• What Is a Chief AI Officer? (IBM), on the scope and responsibilities of the emerging CAIO role
• IBM Study: CEOs Are Reshaping C-suite Roles for the AI Era (IBM Institute for Business Value), on how AI is reshaping leadership structures

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• Boston University, on the distinction between AI fluency and AI tool proficiency
• Workday, on building an AI-fluent culture