AI agent approval workflow
Build approval workflows for AI actions: explicit steps, policy routing, evidence prerequisites, and audit trails - so automation is reviewable and safe for real money.
Approval workflow requirements
Policy-driven routing
Route approvals to the right owner chain based on policy, not ad-hoc message forwarding.
- ✓Approval policies
- ✓Escalations
- ✓Audit trail on changes
Evidence prerequisites
Require evidence before approvals so decisions can be audited and defended later.
- ✓Document linkage
- ✓Evidence checks
- ✓Decision chain
Fail-closed behavior
When prerequisites are missing, deny actions and log reasons. No silent bypasses.
- ✓Logged denials
- ✓Approval gating
- ✓Separation of duties
How agents behave around approvals
Prepare a decision-ready pack
Agents extract, normalize, summarize, and flag exceptions so approvers review the right evidence.
- ✓Draft-first outputs
- ✓Exception flags
- ✓Summary packs
Make uncertainty explicit
Confidence and flags route to review queues with reasons instead of silent guesses.
- ✓Confidence/flags
- ✓Reason codes
- ✓Review queues
Safe reruns after approval
Rerun safely without duplicating side effects, preserving audit trails and decision history.
- ✓Idempotency patterns
- ✓Deterministic reruns
- ✓Audit trails
Related
Follow the runtime and governance surface into specific product workflows.
FAQ
Clear answers for teams evaluating governance and runtime design.
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