Bill Campsey AI Adoption & Experiential Learning
The problem no one is naming

Your teams have the AI tools.
They're not changing how they work.

I design learning experiences that change how people work — not what they know. My proof of concept is a high-resistance military environment where I built AI adoption interventions that produced measurable behavioral change in real time, with peer leaders and their teams, on live systems, under operational conditions.

Case Study April 8, 2026
Grafenwoehr, Germany

A working group of military training professionals — peer site leads and exercise planners — gathered to explore AI-assisted exercise design. These were not early adopters. They were skeptical practitioners with real work to do and no patience for theory.

"AI derives. AI verifies. Human decides."

The session was designed as an experiential intervention, not a training event. Participants worked live AI workflows on government systems, derived real training objectives from actual transcripts, and verified outputs using a second model. The governing principle emerged from the room — not from the facilitator.

By the end, participants had surfaced insights the design hadn't scripted: gaps in multinational training task alignment, obsolescence in legacy reference numbers, new questions about human-AI authority in operational planning. The experience changed how they thought. That's the difference between training and design.

Is this the problem
you're trying to solve?

If your organization has deployed AI tools and is now asking why adoption isn't following — that's a design problem, not a training problem. I'd like to hear about it.

billcampsey@gmail.com