About

I help organizations get AI out of pilots and into production. I got here through data.

AI strategy and governance

Today I lead AI enablement for a large commercial organization. I work with directors to find the AI use cases worth pursuing, guide them through intake and governance, track each pilot’s progress, risks and decisions, and report to senior leadership on what’s working.

AI is the most powerful tool I’ve worked with, the least understood, and the easiest to oversell. The job is deciding where it fits, which initiatives go first, and how far to trust the result, and building things that make AI understandable and useful for people who don’t work in tech.

The frameworks on this site come from that work. The projects are where I test them in public.

Analytics

Before AI, I spent years in marketing and commerce analytics: building reporting and data pipelines, leading a small team of analysts and engineers, advising executives on where to spend, and helping shape the data foundation and A/B testing practice for a large B2B commerce platform.

The work that mattered most was translation, turning an analysis into a decision someone could make on a Monday morning. A dashboard nobody acts on is a very expensive screensaver.

Where it started

I studied journalism, edited the student newspaper and directed the campus news show. That’s where I picked up the habit I still use most: find the one sentence that matters, and respect the audience’s time. Clarity and accuracy turn out to be the same discipline.

The through-line

Making complex things clear. In a newsroom that meant a story. In analytics it meant a decision. With AI it means a system people can rely on, because they understand what it’s good at and where it fails.

That’s what I mean by making AI boring.