Audit Readiness
Build evidence pipelines for AI controls before formal audits begin.
Key takeaways
- Audit readiness comes from evidence produced by normal operations, not a one-time scramble during audit season.
- Map each control to concrete evidence: system register, data classification, role matrix and approval logs, deployment records, monitoring dashboards, and vendor DPAs.
- Assign an owner to every control and evidence source, and store proof in a durable, access-controlled location.
- Link audit requests to existing control IDs and review gaps after every audit, incident, or major product change.
- Good evidence answers who did what, when, why, under which policy, and with what result.
Audit readiness is easier when evidence is produced by normal operations. A control that cannot be proven later will not satisfy auditors or leadership.
Evidence Map
| Control | Evidence examples |
|---|---|
| System inventory | AI system register, owner list, model/vendor list |
| Data protection | Data classification, retention policy, access review |
| Access control | Role matrix, approval logs, token rotation record |
| Change management | Pull requests, deployment records, review approvals |
| Monitoring | Logs, alerts, incidents, dashboard snapshots |
| Vendor governance | DPA, subprocessor list, security review |
Operating Cadence
- Collect evidence continuously, not only during audit season.
- Assign an owner to every control and evidence source.
- Store evidence in a durable, access-controlled location.
- Link audit requests to existing control IDs.
- Review gaps after every audit, incident, or major product change.
Quality Check
Good evidence answers who did what, when, why, under which policy, and with what result.