AI Governance: Controlling Autonomous Agents at Runtime

Autonomous AI agents are creating a new kind of insider risk. These agents can hold identities, credentials, and authority, acting across enterprise systems. This is according to Camille Stewart Gloster, CEO of CAS Strategies. Traditional governance models look at permissions and technical abilities. But agentic AI needs organizations to define how much authority an agent has and when human approval is required. Organizations also need runtime enforcement because policies alone won't control agents. The goal is to enforce boundaries at the point of action and continuously learn. Gloster also discussed how agent inventories help maintain human oversight. She emphasized why chief executives should own cross-functional AI governance. The challenge is balancing fast AI development with meaningful control. This information is crucial for anyone involved in managing AI within an organization.