I help organizations adopt AI the right way — turning investment into real, confident use instead of stalled pilots.
Thirty years leading enterprise technology adoption inside institutions that couldn't afford to get it wrong — now focused entirely on making AI usable, trusted, and adopted by the workforce that needs it most.
Most AI initiatives don't fail on the technology. They fail on the rollout — unclear governance, weak change management, and tools no one ends up using. I bring the same adoption discipline that moved trillion-dollar institutions onto new systems, so your AI investment becomes measured, durable use rather than a stalled pilot.
The people who stand to gain most from AI are often the most wary of it. I teach non-technical teams to move from apprehension to genuine capability — through literacy programs, practical templates, and guided practice designed for working adults, not engineers.
I've spent a career getting large institutions to adopt what was new, unfamiliar, and easy to resist — long before it became standard practice.
Early in my career, I was brought in to help a global financial institution adopt new project-delivery frameworks across its lines of business. Making an unfamiliar discipline usable inside an organization of that scale is precisely the work I do now with AI — the technology has changed, the human challenge has not.
Thirty years of leading enterprise technology taught me that adoption is never really a technology problem. It's a people problem wearing a technology costume. For the past several years I've worked hands-on with AI tools and workflows in my own practice, which means I understand both what these tools can actually do and the very human work of getting people to trust them. That combination — enterprise judgment paired with current, practitioner-level fluency — is what I bring to every engagement.
Specialization Certificate earned