When the Bartender Talks About Claude

My day began with polite distance and puzzled looks. It ended at a neighborhood bar, talking about film and AI with four people I'd only just met. AI was the thread tying those conversations together.

I work in transformation. Change management is the practice that holds it together. Right now, AI is the biggest transformation every organization faces outside of M&A. So when I describe what I do, implementing AI, building tools for change leaders, embedding AI into a methodology built since 1989, I expect people to lean in. Yesterday, many leaned back. Polite pauses. Slight retreats, the tiny gestures people make when they don't want to follow your enthusiasm into a conversation.

When I travel, I make a habit of finding a local bar or restaurant and talking to whoever's there. It's one of the clearest ways I learn. The bar is where the day untangles.

Three industries, four strangers, one thread

At the next stool, a group working in biomed were bright-eyed and unabashedly enthusiastic about AI: the tools they use, the decisions AI is accelerating, the pace of change in their work. They weren't hedging. They were solving problems and moving fast.

The bartender, who grew up in California, didn't ask what AI is. He described what his small business had already done: specific steps, clear lessons, measurable results. No formal change program. No consultant on retainer. They'd run their own implementation and learned quickly.

Then the conversation shifted, through a reference to friends in film, and within a minute biomed gave way to movies. The same thread, AI, carried us across industries without anyone having to translate.

Earlier that day, in meetings about my professional work, people who are responsible for leading change had quietly stepped away from the topic.

The curve has stopped sorting the way we expected

The adoption curve we teach (early adopters, fast majority, slow majority, laggards) is not sorting the way we expect. Job title, seniority, or org chart no longer reliably predict who will adopt or apply AI first.

What AIM says about it

The Accelerating Implementation Methodology (AIM) frames readiness with five elements: Information, Willingness, Ability, Confidence, and Control. The bar test showed me those elements are no longer moving in lockstep across populations the way they used to.

Willingness is appearing where we didn't plant it. A bartender is past willing and into doing. A researcher is operating with confidence. A film conversation springs up between strangers. Meanwhile, many people whose role it is to lead organizational adoption are still working on willingness, despite having access to information.

Three things I'm sitting with

First: Resistance is landing in unexpected places. Pockets have flipped, and my job now includes diagnosing where willingness really sits before I design a change sequence.

Second: Application-ready voices are already inside most organizations. They're often outside the obvious functions, not waiting for permission, and they become powerful change agents when sponsors notice and back them.

Third: The quiet back-aways are data. When the people tasked with guiding change sidestep AI conversations, the gap is upstream of the workforce, not downstream.

Those small social signals matter in transformation work. The bar test isn't a formal study. It's a signal, and signals matter. This week's signal is that public conversation about AI is already past some of the people whose job it is to lead that conversation.