When companies think about who will thrive in an AI-enabled workplace, we tend to look for the obvious signals.
- Technical expertise.
- AI fluency.
- People who know the newest tools and can write the best prompts.
Those things matter.
But some of the people I’d bet on most aren’t technologists at all.
They’re the people:
- Who can spot patterns.
- Who have a clear vision of what they’re trying to accomplish, when the path isn’t clear.
- Who understand not just how work gets done, but why.
- And who can see how the pieces fit together.
I spent much of my career working cross-functionally, eventually in roles where understanding those connections was the work.
A process was never just a process.
It was data. Calendars. Dependencies. Decisions. Competing priorities. Team motivations. And, ultimately, people.
That experience has turned out to be surprisingly relevant to how I use AI.
Because getting AI to produce something isn’t the hard part anymore.
Knowing what you need, giving it the right context, recognizing whether the output is actually good, and shaping it from there is where the value is.
Someone can use AI all day and still use it poorly.
If you simply accept what it gives you without challenging, editing or applying judgment, you aren’t augmenting your capabilities. You’re outsourcing them.
The strongest AI users I see use it as a tool, not a replacement for thinking.
Companies have a role in this too.
- Some are adding solution after solution across departments without understanding how to optimize them together.
- Others are so restrictive that employees can’t experiment enough to learn where AI could actually make their work better.
- At the other extreme, some give employees carte blanche without enough guardrails. At scale, that can carry real consequences.
The opportunity is somewhere in between: create a support system that gives teams access to learn and experiment, clarity around where AI can improve their work, and guardrails to use it responsibly.
Then pay attention to who thrives.
My bet?
The curious operators. The pattern spotters. The people who understand the whole system. The ones who can hold the goal while questioning the process.
As AI gets better at producing answers, our ability to know what we’re trying to accomplish, ask better questions, and apply judgment to what comes back may become more valuable, not less.