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In short: Six guides explain AI agent governance in practice: what it is, how to build an inventory and who owns an agent. Others cover approval rules, audit evidence and governing agents alongside Okta or Entra. The glossary, dated notes and FAQ support them with definitions and context.
Which guides should I read first?
- What is AI agent governance?. A plain guide to AI agent governance: what it covers, how it differs from identity and access management, and the controls that make it real.
- Building an agent inventory. How to build an AI agent inventory that stays current: what each entry needs, where to look for agents, how to find shadow agents, and how to keep it accurate.
- Who owns an AI agent?. How to assign an accountable owner to every AI agent, what the owner does, what happens when owners leave, and how ownership connects to review and incidents.
- Designing approval rules for agents. How to decide which AI agent actions need human approval, who approves, how fast, what happens on timeout, and how to test approval rules before go-live.
- Audit evidence for AI agents. What audit evidence AI agents should produce: per-action logs tied to a person, approvals, reviews, SIEM export, retention and answering an auditor.
- Governing agents alongside Okta or Entra. What Okta and Microsoft Entra already govern for AI agents, what a governance layer adds, and how to run both together without duplicating owners or policies.
Where are the definitions?
The glossary defines 40 terms, from agent governance to control crosswalk.
Where are quick answers?
The FAQ answers thirty common questions.