Correction, 11 October 2026: this post first gave the EU AI Act high-risk dates as they stood before the amendment. Regulation (EU) 2026/1744, in force since 27 July 2026, moved the high-risk dates to 2 December 2027 for Annex III systems (originally 2 August 2026) and 2 August 2028 for Annex I systems (originally 2 August 2027). The text below uses the amended dates.
The EU AI Act becomes enforceable for high-risk AI systems on 2 December 2027 (Annex III standalone systems) and 2 August 2028 (high-risk AI embedded in regulated products), under the Digital Omnibus deferral enacted as Regulation (EU) 2026/1744 (in force 27 July 2026). Annex III lists specific uses rather than whole sectors. An AI agent that screens job applicants, scores creditworthiness, prices life and health insurance or triages emergency calls falls under it. An agent in a bank or a hospital that does none of these things does not fall under Annex III because of its sector alone. Fines reach 15 million EUR or 3% of worldwide annual turnover (Article 99(4)).
What the regulation requires
Article 12: Record-Keeping
Article 12(1) says high-risk AI systems "shall technically allow for the automatic recording of events (logs) over the lifetime of the system". Under Article 12(2) the logs must enable the recording of events relevant to risk situations or substantial modifications, to post-market monitoring and to the deployer's monitoring under Article 26(5). Article 12(3) adds a minimum list for remote biometric identification systems only: the period of each use, the reference database, the input data that led to a match and the people who verified the results. The NIST AI Risk Management Framework provides complementary guidance on structured logging practices.
Article 19: Log Retention
Article 19(1) says providers must keep the logs under their control "for a period appropriate to the intended purpose of the high-risk AI system, of at least six months", unless other Union or national law says otherwise. Under Article 21(2), a provider must give a competent authority access to those logs upon a reasoned request.
Article 26: Deployer Obligations
Deployers (not just providers) must monitor AI system operation, retain logs independently, ensure input data relevance, and inform individuals subject to AI decisions. Audit trail capabilities must be designed in from the start.
Supporting Articles
Article 9 requires lifecycle risk management, with audit trails as the primary data input. Article 13 requires transparency through reviewable operational records. Article 14 requires human oversight, which depends on accessible audit trails. ISO 42001 provides a management system framework aligned with these requirements.
Audit trail checklist
- Every agent action logged automatically. No optional logging that developers can toggle off.
- Structured, complete records. Timestamp, agent identity, action type, input data, output, context.
- Tamper-evident. Cryptographic measures, not just access controls. If logs can be silently modified, they cannot serve as evidence.
- Retained for at least six months. Enforced by infrastructure, not documentation.
- Exportable for regulator review. Structured, readable format within a reasonable timeframe.
- Independently verifiable. Auditors can verify records have not been altered without relying on your assertion.
- Accessible for human oversight. Interpretable by people responsible for overseeing the AI system.
Most organizations satisfy the first two and struggle with the rest.
Why traditional logging falls short
Application logs are mutable. Anyone with server access can edit them. Database records can be updated or deleted. Timestamps can be fabricated without independent anchoring. Without cryptographic proof, "we logged it" is a claim, not evidence.
How to prepare
Step 1: Identify which AI systems fall under Annex III high-risk categories.
Step 2: Evaluate logging against the seven-point checklist above. Document the gaps.
Step 3: Implement cryptographic audit trails. The single largest gap for most organizations is tamper-evidence.
Asqav provides tamper-evident audit trails for AI agents. Every action is signed with ML-DSA (NIST FIPS 204), creating tamper-evident records that support Articles 12, 19, and 26. See our EU AI Act compliance page for a detailed mapping.