AI Agent Governance: Controls for Systems That Can Act
An AI agent is not only a model response. It is a chain of decisions, tools, identities, data access, and actions that must be governed as a system.
Map the agent’s authority
Document what the agent can observe, decide, create, change, purchase, send, approve, and delete. List every tool and downstream system, the identity used, the data accessible, and the boundaries on each action. An agent with broad credentials inherits the risk of every connected system.
Use dedicated identities, least-privilege scopes, short-lived credentials, environment separation, and explicit allowlists. Do not rely on a prompt as the primary authorization layer.
Design approvals around consequences
Require human confirmation for actions that create external commitments, affect people, move money, publish information, change production, expose sensitive data, or are difficult to reverse. Low-risk reversible work can proceed autonomously within limits; higher-impact work should pause with enough context for an informed decision.
Set budgets for time, tokens, tool calls, transactions, and retries. Define circuit breakers for unexpected volume, repeated failures, policy violations, or anomalous destinations.
Observe the whole trajectory
Evaluate the agent on completed tasks, not isolated answers. Capture inputs, model and prompt versions, tool selections, arguments, results, approvals, errors, costs, latency, and final outcomes with appropriate privacy controls. Test prompt injection, poisoned context, permission escalation, ambiguous instructions, and unavailable dependencies.
Production governance needs incident response and rollback. Teams should know how to disable a tool, revoke an identity, pause the agent, preserve evidence, notify affected owners, and learn from near misses.
Leadership checklist
- Inventory every tool, permission, data source, and external action.
- Use technical authorization controls beyond prompts.
- Place human approval before consequential or irreversible actions.
- Trace complete task trajectories and maintain kill switches.