Separating Policy Authors from Policy Approvers with RBAC in an AI Governance Proxy
To separate policy authorship from approval in an AI governance proxy, define distinct roles for authoring, approving, deploying, and administering policy. Enforce the boundaries in the proxy itself: block an identity from approving its own change, deploy only approved and immutable policy versions, and log every step under a distinct identity. Treat emergency access and administrator privileges as controlled exceptions, not as bypasses.
Why authoring and approval need a technical boundary
Separation of duties in AI policy changes only holds when the proxy itself enforces it. A boundary that depends on convention can be crossed by a single identity that both writes and approves a change. The proxy therefore needs to enforce three things:
- An identity cannot approve its own change.
- Only approved and immutable policy versions are deployed.
- Every step is logged under a distinct identity.
Role and permission boundaries
Define distinct roles for authoring, approving, deploying, and administering policy. Each role holds only the permissions needed for its part of the change.
| Role | Boundary |
|---|---|
| Author | Drafts and revises policy but cannot approve or activate it. |
| Approver | Reviews the exact change and approves it, never their own. |
| Deployer | Activates only approved, versioned policy. |
| Administrator | Administers policy. Administrator privileges are a controlled exception, not a bypass. |
Policy lifecycle with enforced separation
Each change moves through four gates: draft, review, approve, deploy. The audit trail records each actor, action, and policy version along the way.
Draft
The author drafts and revises policy but cannot approve or activate it.
Review
The approver reviews the exact change.
Approve
The approver approves the change, never their own.
Deploy
The deployer activates only approved, versioned policy.
Self-approval, identity, administrators, and emergencies
Block self-approval
Enforce the boundary in the proxy itself: an identity must be blocked from approving its own change, so that an approver is never the author of the change under review.
Use distinct identities at every step
Log every step under a distinct identity. Authors, reviewers, approvers, and deployers should each be traceable to their own actions, and deployment should activate only approved and immutable policy versions.
Failure modes and where runtime governance fits
The main failure mode is treating emergency access or administrator privileges as a way around the approval workflow. When those paths bypass the gates, the separation between authors and approvers no longer holds.
Runtime governance fits at the proxy, where the role boundaries, approval gates, and deployment rules are enforced and where each step is logged.
Audit records that show the separation works
Audit evidence should let a reviewer confirm that the boundaries held for each change. Capture the following:
- Distinct author, reviewer, approver, and deployer identities for each change
- Timestamps for submission, review, approval, and deployment
- Policy version identifier and a content hash or diff reference
- Approval decisions with comments, including rejections
- Role assignment changes and the identity that made them
- Break-glass use with reason, duration, and post-incident review outcome
Review your policy approval model
Talk with our team about applying runtime policy enforcement, least-privilege roles, and audit logging to your AI agent environment.
Talk to an Expert