The short answer
Review an AI workflow by tracing one real operating task from source input through model interpretation, recommendation, approval, external action, receipt, reconciliation, and recovery. For each stage, record a plausible failure, impact, detection signal, preventive boundary, containment action, owner, and test. Include failures where the output looks reasonable but references the wrong property, version, or authority.
Key takeaways
Start with a concrete action chain
Name the source records, model task, allowed outputs, human decisions, tools, external systems, and final evidence. “AI handles maintenance” is not reviewable; “AI classifies a request and drafts a routing suggestion while a person approves dispatch” is.
NIST’s voluntary AI RMF emphasizes documented roles, monitoring, testing, accountability, and lifecycle governance. Use it as a risk-management reference, not as certification that a workflow is safe.
Build a stage-level failure register
Prioritize with the organization’s own impact and risk approach. A numeric score should not conceal uncertainty.
| Stage | Plausible failure | Detection | Containment/recovery |
|---|---|---|---|
| Input | Wrong property, stale record, missing attachment | Identity/version checks | Stop and request governed source |
| Interpretation | Confident but unsupported classification | Evidence display and disagreement sample | Human route or abstention |
| Decision | Recommendation exceeds policy or authority | Policy gate and reviewer visibility | Block release; record override |
| Action | Duplicate, wrong recipient, or unintended external write | Action identity and preflight | Disable action; reconcile outcome |
| Evidence | Success shown without provider receipt | External-state check | Keep outcome unknown and investigate |
| Recovery | Override stays active or correction is not propagated | Expiry and downstream reconciliation | Rollback, repair, and closeout review |
Turn the register into tests
Test ordinary cases, boundary cases, missing data, stale versions, tool timeouts, repeated events, contradictory evidence, unauthorized requests, and recovery after partial execution. Record expected and observed results.
A safe test environment may not prove production permissions or external effects. Identify what requires controlled production verification and who approves it.
Connect failures to incident and provider-change controls
Define which signals pause authority and open an incident, which action evidence is needed to reconstruct the affected population, and which recovery gates must pass before restoration. A register that stops at detection leaves the most consequential states undefined.
When a model or provider changes, reuse only tests whose assumptions still hold. Route behavior, tool, data, latency, cost, and observability changes through a bounded acceptance gate with rollback triggers.
Operational checklist
Mark your progress, then save a working copy. Selections reset when you leave this page. A checked box is not an approval or evidence of completion.
0 of 7 marked
Edge cases
Sources and references
Follow each source to check the underlying claim. Access checks and professional review are different steps.