Governing Multi-User AI Agents
A CIO reference for per-action authorization
An agent acting in production for many users needs deterministic control on every action it takes, and that control has to sit outside the model, because anything the model can reach, the model can be talked around.
What's in the reference
-
Why service-account and inherited access both fail
-
Guardrails vs. governance, as an audit-ready table
-
The eight-step per-action authorization flow
-
Eleven questions to ask before production
-
A 60-second agent posture check
Trusted in prod by
You might also like
About Arcade
Arcade is the actions runtime for governing enterprise AI agents. We enforce your security policies on every action, bring every agent and tool under a single control plane with full auditability, and a clear path to production for every agent. We grant privileges just-in-time, vault credentials separate from the agent, and hook into the IdP, DLP, and SIEM you already run.
Additional resources
