your AI champion is already there.

In almost every team I’ve worked with, there’s that one person.

You know the one.

They tried Cursor before anyone asked them to.

They’re testing new models over the weekend.

They show up to stand-up saying:

“By the way, I automated that thing we spend half a day doing every week.”

And the rest of the team looks at them with a mix of admiration, curiosity… and slight exhaustion.

Because yes, they are that person.

But here’s the interesting part.

A lot of companies don’t really know what to do with people like this.

Sometimes they’re treated as a curiosity.

“Oh yeah, ask Mark. He’s the AI guy.”

Sometimes their experiments are seen as nice little side projects.

And sometimes — especially in more traditional organizations — they’re almost treated as a problem.

Because they’re not following the established process.

They’re trying tools that aren’t part of the official workflow.

They’re asking uncomfortable questions like:

“Why are we still doing this manually?”

And:

“Why does this take three days if I can do the first version in twenty minutes?”

But if you actually want your company to become AI-native, this person might be one of the most valuable people you have.

Not because they know every AI tool.

They don’t.

Not because every experiment they run works.

It won’t.

But because they’ve already crossed the biggest barrier:

They’ve changed the way they think about work.

They don’t start with:

“How do I do this task?”

They start with:

“Do I still need to do this task this way?”

That mindset is much harder to create than access to Claude, Cursor, Copilot or ChatGPT.

You can buy licenses in an afternoon.

Changing how a team works takes much longer.

And that’s why your internal early adopters matter so much.

They can show people real examples from their actual work.

Not a generic AI demo.

Not another presentation about “the future of productivity.”

Something much simpler:

“Here’s what I did yesterday.”

“Here’s how I did it.”

“Here’s the prompt.”

“Here’s the workflow.”

“And here are the two hours it saved me.”

That’s how adoption starts to spread.

The problem?

These people often operate completely on their own.

They experiment after hours.

They share a few tricks in Slack.

Maybe they show something during a call.

But there’s no real space for them to teach others.

No time allocated for experiments.

No place to document what works.

No way to turn one person’s workflow into something the rest of the team can actually use.

So eventually one of two things happens.

They stop experimenting because nobody really cares.

Or they move somewhere that does.

And then, six months later, the company hires an external consultant to explain how to become “AI-native.”

There’s nothing wrong with external help.

But before you go looking for it, look around your own team.

Who is already doing this?

Who keeps experimenting?

Who keeps showing up with small automations, better workflows and slightly annoying questions about why things are done the way they are?

Find that person.

Give them space.

Give them time.

Let them share what works — and what doesn’t.

Because your first AI champion might already be sitting in your next stand-up.