Agent governance is the control of what an AI agent may do — which tools it may invoke, what data it may reach, how far it may act without approval, and under whose authority — enforced on every step of execution rather than at the point the agent was launched.
What is AI agent governance?
An agent is not a single request but a sequence of decisions, each of which can retrieve data, call a tool, write memory or delegate to another agent. Approving the agent once and trusting the sequence is the central failure mode. Agent governance evaluates each step against policy in the context of the steps that preceded it, constrains autonomy by defined levels with human approval at the boundaries, and produces a trace of what the agent did and why. It is what turns an agent from a demonstration into something an enterprise can accept in production.