I came to AI adoption through fifteen years of watching organizations struggle with the same pattern: a tool gets introduced, the rollout looks fine on paper, and six months later nobody’s using it the way it was meant to be used. The tool wasn’t the problem. The work around the tool was.

That’s the throughline of my career.

Knowledge management, technical writing, change management — different disciplines, same underlying problem. People don’t adopt what they don’t understand, and they don’t understand what hasn’t been built with them in mind.

The compound skill set

Knowledge management taught me that systems succeed or fail at the gaps between people and information.

Technical writing taught me that if you can’t explain a process clearly, you can’t expect people to follow it, much less feel confident about it.

Running writing operations at scale taught me what it takes to keep quality consistent across reviewers, contributors, and revision cycles.

Change management taught me that adoption is a practice, not an event.

AI adoption draws on all four.

When I assess a workflow, I’m not just looking at where AI could plug in. I’m looking at whether the workflow itself is clear enough to support AI in the first place. It isn’t, more often than you might think. That gap is where the real work lives.

Prework beats rework.

What I’ve worked on

My engagements to date have mostly involved content-driven organizations: nonprofits with communications functions, mid-sized businesses with internal documentation needs, and small consultancies with research and writing at the center of what they do.

Some of the work has focused on the writing itself: tightening editorial and review workflows, building quality-control systems, deploying AI where it amplifies what writers and editors already do well. 

Some of it has focused on decision-making support: building tools that help leaders think through problems, pressure-test plans, and work through strategic questions in structured conversation rather than scattered notes.

Different surface, same underlying pattern. The tool serves the thinking, not the other way around.

Credentials

– AI Operator Certified
– 15+ years in knowledge management, technical writing, and change management
Contributing author, The Most Amazing Marketing Book Ever (co-wrote the chapter on copywriting)
– Engagements across nonprofit, corporate, and small-business contexts

Get in touch

If you’re hiring for an AI adoption or enablement role, considering a selective engagement, or want to compare notes on this work, I’d like to hear from you.