AI agent governance is the set of security controls that limit what autonomous software can access, decide, and execute. It goes beyond model safety and focuses on the agent’s real powers: credentials, tools, APIs, data sources, and system actions. Good governance uses scoped identity, least privilege, approval workflows, logging, and fast revocation so an agent can only do what it is allowed to do.
This matters because an AI agent can chain multiple steps without waiting for a person. If permissions are too broad, a prompt injection, stolen token, or buggy workflow can let the agent read sensitive data, send messages, create users, or change systems at machine speed. Defenders use governance to inventory agents, define policy per task, monitor behavior, and keep audit trails for incident response. In attacks, poor governance turns a helpful automation into a high-value foothold; in defense, it makes autonomous systems observable, controllable, and safer to trust.