AI agent governance is the control plane that lets enterprises run agents like a workforce: identity and RBAC/ABAC, policy before every tool call, human-in-the-loop queues, immutable audit, model routing, spend attribution, and kill-switches. Symbiosis AI implements governance as productized controls on Agent Cloud - the same plane every Symbiosis product uses - so pilots leave the lab.
- Agent catalog, ownership, risk class, and versioning
- Policy-as-code: allow/deny tools, data scopes, and spend ceilings
- Human approval queues with SLAs for high-consequence actions
- Immutable action logs for security, finance, and model-risk review
- Evaluation and drift gates before autonomy increases
Questions, answered
What is AI agent governance?
The set of controls - identity, policy, approval, audit, spend, and kill-switch - that make agent actions accountable enough for security and finance to approve production use.
Why do AI pilots fail security review?
Usually missing identity, uncontrolled tool access, no audit trail, and no human gate. Governance fixes those before the model choice debate.
Is Agent Cloud required?
It is Symbiosis AI's governance plane. You can discuss bring-your-own controls; production agents we ship still need equivalent accountability.