AI Agent Governance

Govern AI agents and agentic workflows with inventory visibility, ownership, tool controls, evidence records and continuous operational review.

AI agents are moving from isolated experiments into enterprise workflows where they can draft, summarize, route, transform and coordinate work across teams.

That shift creates a governance problem: organizations need to know where agents are used, what workflows they support, who owns the activity, which systems are affected and what evidence exists around review and oversight.

AI agent governance gives teams an operating model for agent visibility, inventory, ownership, risk context, human review and audit-ready evidence.

This pillar is related to broader AI governance, risk and compliance, but it remains a distinct resource for agentic systems and workflows.