Oversight log: how to document human oversight under the EU AI Act

Updated: June 2026

Introduction: why oversight documentation matters

Art. 26.2 requires human oversighthuman oversightDesigned-in human ability to monitor, intervene in, override or shut down an AI system. It is meaningful only when the human has authority, information and time to act. One of the seven pillars of responsible AI, and under the EU AI Act a requirement for high-risk AI systems: Article 14 requires that those systems are designed so natural persons can effectively oversee them. Oversight that exists on paper but amounts to confirming in practice does not meet that bar. See override rate, automation bias, high-risk AI system, fairness, safety and reliability, privacy, security and robustness, transparency and explainability, accountability, responsible AI. In the IAPP AIGP body of knowledge, this principle appears as human-centricity, with human oversight as one of its elements.Open full entry → of high-risk AI systemshigh-risk AI systemAn AI system that falls under the EU AI Act's strictest requirements, following Article 6. There are two routes in: a system that is a product or safety component covered by the Union harmonization legislation in Annex I and subject to third-party conformity assessment, or a system used in one of the areas listed in Annex III, such as employment, education, or access to essential services. Article 6(3) contains a filter: an Annex III system is not high-risk if it does not pose a significant risk of harm to health, safety, or fundamental rights, although a system that profiles natural persons is always high-risk. See EU AI Act, Annex III, conformity assessment.Open full entry →. But oversight without documentation is invisible to supervisory authorities. When the supervisory authority investigates a complaint or conducts a compliance audit, the question will not be "do you have oversight?" but "can you demonstrate oversight?" A well-maintained oversight log is your primary evidenceevidenceThe concrete proof that a control is designed, implemented, and working: a test report, an audit trail, an impact assessment, a monitoring log. Each link in the governance chain produces an artifact, and together they are what an organization hands to its own board, a regulator, a customer, or an affected person to show, not say, that a system is governed. Its absence is itself the failure: a risk register without test results, or a mitigation claimed without validation, is a governance gap, not a paperwork one. The closing link of the governance chain. See control, governance.Open full entry →.

This guide explains what an oversight log must contain, how to structure it, and how to maintain it efficiently in practice.

What is an oversight log?

An oversight log is a contemporaneous record of human oversight activities for high-riskriskIn the EU AI Act's terms, the combination of the likelihood that a harm occurs and the severity of it if it does. The link between a principle (via the harm that would breach it) and a control (the measure that reduces it). Naming the harm and assessing its risk is required by Art. 9 before any mitigation measure is chosen. See harm, control, residual risk.Open full entry → AI systemsAI systemA machine-based system that, for explicit or implicit objectives, infers from input how to generate outputs (predictions, content, recommendations or decisions) that can influence physical or virtual environments. The OECD-style definition followed by the EU AI Act.Open full entry →. It documents that a qualified person reviewed AI outputs before or shortly after they influenced significant decisions, and records the outcome of that review.

The log serves three functions:

1. Compliance evidence: Demonstrates to the supervisory authority and to affected individuals that meaningful oversight occurred
2. Performance monitoring: The log data reveals patterns, rising override ratesoverride rateThe share of proposals from an AI system that a human reviewer changes or rejects, used as an indicator of whether human oversight is functioning. A structural zero is a reason to investigate rather than a reassurance, because it can mean the system performs well or that the reviewer has stopped examining. It is a signal, not a standalone quality measure. See human oversight, automation bias.Open full entry → signal model degradation
3. Learning and improvement: Override reasons documented over time build institutional knowledge about AI system strengths and weaknesses

What must an oversight log contain?

Minimum required elements for each oversight event:

Field	Description
Date and time	When was the oversight conducted?
AI system	Which AI system generated the output being reviewed?
Overseer identity	Who conducted the oversight (name/role)?
AI output summary	What did the AI system recommend or decide?
Oversight decision	Accept / override / escalate
Override rationale	If overridden: why? (required for audit trail quality)
Final decision	What decision was ultimately made?

Oversight frequency

Oversight frequency depends on the AI system's decision volume and risk level:

• High-volume, high-stakes systems (credit scoring, CV screening): Oversight on every individual decision, or at minimum a structured sample of decisions with defined statistical coverage
• Lower-volume systems (performance appraisal AI): Oversight on every decision
• Monitoring-only systems (anomaly detection AI that generates alerts): Oversight review of all alerts before action is taken

Oversight log implementation options

• Integrated in the AI platform: Ideal, many enterprise AI platforms have built-in human review workflows. Configure the platform to capture oversight decisions as part of the workflow.
• Ticketing system (Jira, ServiceNow): Create oversight tickets linked to AI outputs. The ticket trail serves as the log.
• Structured spreadsheet: Acceptable for low-volume systems. Use a shared spreadsheet with protected formatting to maintain integrity.
• Document management system: Monthly oversight review reports filed in a versioned document system.

Retention

Oversight logs are AI system logs within the meaning of Art. 26.6. You must retain them for at least 6 months, or longer if sector-specific law requires.

Compliance checklist

1. Is there an oversight log for every high-risk AI system?
2. Does each log entry contain all required elements?
3. Are override rationales documented for all overrides?
4. Is the oversight frequency appropriate for the decision volume and risk level?
5. Are logs retained for the required period?
6. Is override rate data regularly analyzed for performance monitoring purposes?