The First Job of AI Enablement Isn't Education

I had one of those little AI moments this weekend that reminded me why I care so much about AI enablement. It did not happen in a workshop, or a steering committee, or anywhere near an enterprise. It happened at a cabin in the woods in Minnesota.

My friends are not AI people. They aren't following the latest models, talking about agents, or thinking about what AI is going to do to the workforce. If I started a sentence with the phrase “workflow transformation” at that kitchen table, I would deserve the silence that followed.

They are, however, always thinking about projects for this cabin. That is the thing they will talk about for hours.

So we started playing with ChatGPT and asked it to show us what the cabin could look like with a few changes. One photo of how it looks today. Then a second image of what we were able to imagine.

And they were hooked.

The part that stayed with me

My friend's husband is about as Minnesota as it gets — hunter, fisherman, outdoorsman, always working on something around the property. His world is much more about being outside than being online.

He doesn't need AI because someone tells him it's going to transform the world. Frankly, I'm not sure that argument would interest him at all. And he would be within his rights — it is an abstraction, delivered by a stranger, about a future he did not ask about.

But give him a tool that helps him visualize what his cabin could look like before he starts the next project?

Now we have his attention.

Not because anyone convinced him of anything. Because for about ninety seconds, the technology stopped being a topic and became useful to him, specifically, for something he already wanted to do.

What I keep getting wrong at work

We spend an enormous amount of time thinking about how to educate people about AI. Training. Prompting. Agents. Productivity. Workflow transformation. Our program has built curricula for all of it, at real scale, and I would defend every one of them.

All of that matters.

But I'm becoming more convinced that the first job of AI enablement isn't education at all.

The first job of AI enablement is helping someone find their reason to care.

Education assumes the person already wants the thing you're teaching. That assumption holds for maybe the first fifteen percent of any workforce — and those are the people who show up to the optional session, who were going to find it anyway.

For everyone else, education without motivation is just noise arriving on a Tuesday. Well-designed noise. Beautifully produced noise. Still noise.

Meet people where they are

The alternative isn't complicated, it's just less scalable-looking, which is why programs skip it.

Find something they already want to do, and show them how AI can make it easier, better, faster — or maybe just more fun. That last one gets dismissed and shouldn't. Delight is a legitimate on-ramp. Nobody at that kitchen table was optimizing anything.

That's where curiosity starts. And once someone has that first “wait… it can do that?” moment, a sequence begins that I have now watched play out dozens of times inside the enterprise and once, this weekend, in a cabin:

• They start experimenting.
• Then they start asking better questions.
• And eventually: what else could I do with this?

That last question is the shift we are really trying to create. Everything else in an enablement program is scaffolding around getting more people to ask it.

Where the real work is

This is the part I would push hardest with anyone running one of these programs, because it determines where you spend your scarcest resource.

Your enthusiasts will find the tool with or without you. They will build things, evangelize, show up to office hours, and make your dashboards look excellent. It is genuinely tempting to optimize for them, because they respond, and responsive people feel like progress.

The harder — and more important — work is reaching the person who doesn't think AI has anything to do with them yet.

Not because they're resistant. Usually they're not resistant at all. They just have a full job, a reasonable amount of skepticism, and no particular reason to believe this is for someone like them. Every message they have received about AI has been aimed at somebody else.

Reaching that person means three things, and none of them are a curriculum:

• Helping them find value — in their actual work, not in a generic use case from a vendor deck.
• Helping them build confidence — enough to try something in front of a colleague without feeling foolish.
• Helping them imagine what might be possible in their own work — which is the cabin, exactly. Show them the second photo.

One person at a time

That is how you bring a workforce along.

Not one technology deployment at a time. One person at a time — which sounds hopelessly unscalable until you notice that it's how every real adoption curve has actually worked. Someone has the moment. They tell the person next to them. That person has their own version of it. The enablement function's job is to manufacture more of those moments deliberately instead of waiting for them to happen by luck.

I think about this constantly now when I look at a rollout plan. Where in this plan does someone who doesn't care yet get a reason to? If the answer is “the training,” the answer is probably nowhere.

And sometimes, it starts with a cabin in the woods.

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If you're running enablement and wrestling with the same thing — how to reach past the enthusiasts — I'd like to compare notes. Find me on LinkedIn or send me a note.