You Need Someone to Talk To

The fastest way to build AI capability isn’t more tools. It’s more conversation.

I had a one-on-one with Adriana McLean last week.

There was no agenda item labeled “AI strategy.” We were just talking. She’s sharp, she’s been paying close attention to what’s happening in this space, and somewhere in that conversation, two ideas surfaced that I hadn’t been thinking about before. Both ended up affecting the whole team.

I’ve been doing this long enough to know that’s not a coincidence. That’s a pattern.

The people making the most progress with AI right now aren’t necessarily the ones with the time, the biggest budget, or the most advanced tools. They’re the ones who have someone to talk to about it.

Most operators are doing this alone.

Why Most People Are Stuck

They try something. It works or it doesn’t. They move on. No debrief. No second perspective. No one to push back or say, “that’s interesting, have you tried it this way?”

The result is slow, uneven progress. You get good at the specific use cases you stumble into and miss everything else. You don’t know what you don’t know, and there’s no one to tell you.

This is one of the reasons AI adoptions inside distribution companies looks the way it does right now. There are pockets of real capability and large stretches of nothing. The capability tends to cluster around the people who are talking to each other.

The isolation isn’t laziness. It’s structure. Most organizations haven’t built any infrastructure for informal AI learning. There’s no regular meeting where people compare notes, share what worked, admit what didn’t, and push each other to try harder things.

So, people do it alone. And most of them slow down without realizing it.

Here’s what I’ve found: having a thinking partner isn’t about the ideas. It’s about accountability.

Why Accountability Changes Everything

When you know you’re going to talk to someone about what you’ve been experimenting with, you experiment. You push a little further. You try the thing you’ve been putting off. You don’t let three weeks go by without opening the tool.

This is not a new insight. It applies to any skill you’re trying to build. Fitness, languages, writing. The research on skill development is consistent: people who have a partner, a coach, or even just a regular check-in outperforms people who go it alone. Not because the partner has better information. Because the relationship creates a reason to show up.

AI is no different.

The conversation with Adriana worked the way it did not just because she’s smart. It worked because I knew I was going to have a conversation with someone who was also paying attention. That created a kind of forward pressure. I was more intentional about what I was noticing. I was more willing to follow a thread because I knew I’d have a chance to talk about it.

That’s the hidden value of the thinking partner relationship. It’s not just the ideas that surface in the conversation. It’s the quality of thinking that happens in between conversations because you know the conversation is coming.

What This Actually Looks Like

I’m not talking about a formal mentorship program or a structured AI committee. Those have their place, but they’re not what I mean here.

I mean finding one person in your orbit who is genuinely engaged with this, someone who’s experimenting, paying attention to what’s happening, willing to say what they think, and interested enough to push back.

It might be a peer inside your company. It might be someone in your industry network. It might be a counterpart to a supplier or customer you trust. The organizational relationship matters less than the quality of the engagement.

What you’re looking for is someone who will ask you, “so what have you been working on?” and mean it. Someone who will share something they tried that didn’t work. Someone whose learning is moving fast enough that a conversation with them changes how you think.

Set up a regular call. Not to report out. To think out loud. Thirty minutes every couple of weeks is enough to keep the momentum going and the accountability real.

What Leaders Should Build

If you’re running an organization right now, this is worth thinking about structurally.

Informal AI learning networks are already forming inside your company whether you’ve designed them or not. The question is whether they’re forming in useful ways or whether the people with real capability are staying quiet because there’s no safe place to share what they’re learning.

The simplest version of this is creating a regular space where people can compare notes. Not a training session. Not a vendor demo. A working conversation where people share what they’ve tried, what worked, what didn’t, and what they’re going to try next.

The companies that will pull ahead in AI adoption aren’t going to be the ones with the best roadmaps. They’re going to be the ones where learning compounds across people instead of staying trapped in individual heads.

That starts with conversation. It gets sustained through accountability. And it scales when leadership creates the conditions for both.

Find Your Adriana

You don’t need a perfect AI strategy to make meaningful progress right now. You need someone to talk to about it on a regular basis.

Find the person in your network who is paying attention and moving fast. Set up a recurring call. Go in without a fixed agenda. See what surfaces.

The ideas will come. Accountability will keep you moving between conversations. And over time, you’ll look back and realize that the conversations were where most of the real learning happened.

I had that experience last week with Adriana. One conversation. Two ideas. Impact on the whole team.

That’s the return on a thirty-minute call. Hard to find a better investment.

If you’re looking for a room full of peers who are working on the same problems, the Applied AI for Distributors Conference is in Chicago, June 23-25. It’s built for exactly this kind of conversation.

Register and learn more at appliedaifordistributors.com.