The institutional architecture required to govern AI is forming in real time. Most organizations using AI have no formal governance framework. State and supranational regulators are converging on lifecycle governance requirements, meaning continuous post-deployment monitoring rather than point-in-time review. The supervisory expectation is shifting from compliance to organizational design.
The Institute's Responsible AI work begins from a structural premise. The organizational architectures designed for predictable, point-in-time AI systems are insufficient for agentic systems and lifecycle governance regimes. The gap is not regulatory but institutional. Closing it requires reorganizing model risk, compliance, technology, and legal functions into integrated governance systems that operate on a different clock than traditional examination cycles.