Ai Agent Governance
Ai Agent Governance resources for enterprise AI governance.
AI agents are moving from isolated experiments into enterprise workflows where they can execute business tasks, trigger workflow steps, access enterprise data and coordinate work across multiple systems.
That shift creates a governance problem: organizations need to know which agents exist, what workflows they support, what they are allowed to do, which systems they may access, who approved that scope and who remains accountable.
AI agent governance starts with discovery, visibility, inventory and accountable ownership before governance controls can operate. It gives teams an operating model for agent visibility, delegated authority, human oversight, lifecycle review and audit-ready evidence.
Explore the Enterprise Guide to AI Agent Governance for a deeper view of ownership, accountability and governance across the AI agent lifecycle.
For a concise explanation of the operating discipline, see the AI Agent Governance definition.
This pillar is related to broader AI governance, risk and compliance, but it remains a distinct resource for agentic systems and workflows.