Model Governance

The subset of AI governance focused specifically on managing individual AI models through their lifecycle -- from development and validation through deployment, monitoring, and retirement. Model governance includes version control for model weights, performance monitoring in production, drift detection, and change management. Financial institutions have done this for credit models for decades; the rest of the market is catching up.