For most of my career, "keeping up" meant learning new tools. AI is the first shift that's made me question something deeper: not how to do the work, but who gets to decide when the work is good.

I started using AI in production work before most people were talking about it — generating web, social, and application imagery for clients like Siemens, Chipotle, and Clarivate. At the time, it was simple: it saved time. I didn't think of it as a strategic shift. I think that was a mistake, in hindsight — not because the work suffered, but because I wasn't yet asking the harder questions I ask now.

Here's what I've come to believe since: AI is very good at producing options. It is not good at knowing which option is right for this brand, this audience, this moment — and it never will be, because that judgment isn't a pattern in a dataset. It's built from every project that didn't work, every client who couldn't articulate what was wrong until you showed them the fix, every younger designer you've watched find their own eye. That's not sentimentality about experience. It's the actual mechanism by which good taste gets formed, and it's the thing AI has no substitute for.

So the question I'd put to any design leader right now isn't "how do we use AI" — that part is increasingly obvious. It's: who on your team still knows what "right" looks like when the tool hands you ten plausible answers? If the answer is "no one, yet," that's not a tooling gap. That's a leadership gap, and it's the one I actually care about closing.

I don't have this fully figured out. I'm earlier in this than the confident takes on LinkedIn would suggest anyone should be. But I'd rather be honestly early than falsely fluent — and I think that's true for most of us right now, whether we admit it or not.