How do we govern AI agents that can autonomously act in our systems?

An AI agent with access to your CRM, billing system, and email is like giving an intern the keys to every filing cabinet on their first day with no supervisor and no training. The potential for productivity is enormous. So is the potential for damage. The difference between a productive agent and a destructive one is governance.

Scope containment is the most important control. Define exactly what the agent can access and what it cannot. Not as a suggestion. As a technical enforcement. The agent physically cannot reach systems outside its scope. If it needs access to something new, a human approves the expansion.

Action logging is your insurance policy. Every tool call, every API request, every decision the agent makes is logged with a timestamp, the input data, and the output. When something goes wrong, you need to reconstruct exactly what happened. Without logs, you are guessing.

Escalation triggers prevent the worst outcomes. Define thresholds: confidence below 80%? Escalate. Financial impact above $1,000? Escalate. Customer complaint detected? Escalate. The agent handles the routine. Humans handle the exceptions. Claude Guard provides all five controls out of the box, enforced at the architecture level.