Field notes on leading the shift.
What I learned going from consultant to operator to builder, and what it means for how you lead in the AI era.
Adoption is a vanity metric
High adoption feels like progress. The number that counts is output tied to a business objective, at finance-grade accuracy.
Read →Your biggest AI risk is the one you can't see
The risk in finance isn't a bad prediction. It's ungoverned data moving through systems nobody approved.
Read →Knowing what's good is the edge
Execution looked like the edge. It never was. The skill now is knowing what good looks like, and directing the work to it.
Read →Data is the constraint
The bottleneck with AI is almost never the model. It's whether you have access to data worth thinking about.
Read →You're asking the wrong question about AI
Most leaders ask whether AI can do the job. The question that moves you forward is whether you should, and how you will direct it.
Read →Consultant, operator, builder: what each one taught me about AI
I advised companies on change, then had to execute it, then build it myself. Each seat taught me something the one before couldn't.
Read →Why executives need to become citizen builders
The hardest calls in AI aren't technical. They're business judgment, and they're yours to make. You can't make them without building.
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