Audit AI agent actions with action-level logging that records what the agent was asked, what it decided, which tools and systems it touched, which credential it used, what it proposed, who approved it, and what changed. This produces one traceable record per business action rather than fragments scattered across systems. Mapping those logs to the NIST AI RMF or a MITRE ATLAS technique supports both incident response and compliance. Logging that captures decisions and credential use, not just model outputs, is what makes an agent’s behavior defensible after an incident.