AI today is alchemy. My job is turning it into chemistry.

Make AI boring.

Real value comes from AI that’s in production, measured, and trusted exactly as far as it’s reliable. These are the methods I use to get there, and the work that proves them.

George Andersen
George AndersenAnalytics & AI leader

How I think

Make AI boring is the philosophy. Three methods put it to work at three altitudes: the portfolio, the workflow, and the single decision.

  1. What should we do first?

    Risk-Tiered AI Adoption

    Sequence AI by risk, not by one ROI gate: start inside, build the muscle, then go customer-facing.

    Reviewed

  2. Where does AI fit in the work?

    Fix First, AI Last

    Map the work before you buy the tool: most stuck points need a process fix or a simple rule, not AI.

    Reviewed

  3. How far should we trust it?

    Calibrated Trust

    Fluency isn’t truth. Use AI where checking is cheaper than doing, and trust it exactly as far as it has earned.

    Reviewed

The proof

Frameworks are claims until something ships. Each project below puts at least one of them into practice.

About

Today I lead AI enablement for a large commercial organization: finding where AI fits, guiding it through governance, and reporting what it actually delivers. I got here through analytics, turning marketing and commerce data into decisions teams could act on. The habit underneath it all started with a journalism degree: make complicated things clear to people with no time to spare.

More about my path

The through-line
  1. Where it started · Journalism degreea story
  2. Data & analyticsa decision
  3. AI strategy & governancea system people can trust

One job throughout: making complex things clear.

Latest lab notes

All lab notes

Contact

Let’s talk about getting AI into production.