// Insights
Essays on AI, insurance, and the gap between tools and transformation.
Accuracy tells you whether a model works. It doesn't tell you where it's safe to deploy. Two questions — how reversible a wrong answer is, and whether a human is still making the call — sort your entire AI roadmap onto a grid that shows where to deploy now and where pilots go to die.
The models are good now. Pilots stall because of where you point them. Four structural properties of insurance work decide where AI pays off and where it won't — and telling the compounding layer from the judgment layer is what a decade inside a carrier teaches you.
The first mile — recognizing AI can materially improve insurance operations — is done. The last mile is everything between that recognition and production technology delivering tangible business impact. Most carriers are stuck there, and the gap is widening.
Every AI vendor can plug into your data. None of them can plug into your context. The institutional knowledge locked in your senior employees' heads is the real competitive advantage — and it's decaying every day it stays unstructured.
Everyone on our leadership team built their own team of specialized AI agents. None of them were asked to build one and most have never coded before (or since).
The organizational immune system is real. But so is the operational advantage incumbent carriers have—if they move fast enough.