AI governance conversations tend to start with the same question: what happens after the model is built? Who reviews the output? Who signs off before deployment? Those are fair questions, but they arrive too late to matter most. By the time an AI solution is built, the riskiest decisions have often already been made: in how the problem was framed, who was consulted, and what "success"...
