The hard truth about rolling out AI

Everyone wants AI right now.
But most have no clue what it actually takes to make it work.

I met a founder recently who said:
"Can’t we just roll it out across the whole business this quarter?"

Sure.
If you’re also cool with team resistance, failed pilots, and a blown-up budget.

The biggest myth in AI right now is that it’s plug-and-play.
Drop in a model. Add some prompts. Watch the magic happen.

In reality, most fast AI rollouts end in frustration.
Not because the tech doesn’t work — but because the approach is wrong.

If you want real ROI, you need structure.
And patience.

I’ve seen two types of companies trying to implement AI:

Type 1: The rushers.
They roll out five use cases at once.
They skip training.
They launch before testing.

Three months later?
They’ve spent $200k.
The team doesn’t use it.
Nobody knows what worked.
And they quietly shut it all down.

Type 2: The builders.
They start with one high-impact workflow.
They test it with a small team.
They collect feedback early.
They measure every week.
They improve before scaling.

Twelve months later, they’ve got 90% adoption.
They’ve automated entire processes.
They’re building internal agent teams that scale with confidence.

It’s not glamorous.
It’s not fast.
But it works.

AI is not a magic switch.
It’s a process.

Build. Test. Refine. Repeat.

Start small.
Focus on what matters.
Let the wins compound.

It’ll feel slow at first.
But in a year, you’ll have a business that runs differently — and better.

And if you want to see what that looks like in practice, I share one real-world AI build every Friday.

Stick around. I’ll show you the difference between hype and results.

— Robin