Audit Readiness
Build evidence pipelines for AI controls before formal audits begin.
Written and reviewed by Eric Han · Co-founder & CTO, reopt
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.
Article 50: separate roles and evidence
| Provision | Main obligation | Evidence example |
|---|---|---|
| 50(1) | Disclose interaction with AI, subject to exceptions such as obvious interaction | First-contact UI/audio and applicability decision |
| 50(2) | Provider machine-readable marking and detectability of synthetic content | Output markings and transformation checks |
| 50(3) | Inform people exposed to emotion recognition or biometric categorization | Notice, context, and delivery time |
| 50(4) | Deployer disclosure for deepfakes and AI-generated public-interest text | Human-readable labels and editorial review/responsibility records |
First establish the role and applicable exceptions. Machine-readable markings alone do not discharge a deployer's human-facing disclosure obligation. The public-interest text exception requires substantive human review/editorial control and editorial responsibility. The December 2, 2026 grace period covers only Article 50(2) for systems placed on the market before August 2, not all transparency notices.
AI Omnibus entry into force · Article 50 FAQ
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.