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An AI incident file should let someone who was not present reconstruct the system involved, what happened and when, what evidence was preserved, how the organization assessed risk and possible causes, what it did in response, and who it notified. For certain serious incidents involving high-risk AI systems in the EU, providers have reporting duties under Article 73 of the EU AI Act. The Act does not prescribe one universal incident-file template, and its rules do not apply to every organization or AI incident.
Start by identifying the role and legal regime
Before assembling a file, record who operated in which role and which rules may apply. An AI provider’s reporting and documentation duties are not interchangeable with a deployer’s logging duties. Providers of general-purpose AI (GPAI) models with systemic risk have a separate incident-reporting regime.
- Provider of a high-risk AI system: Article 73 requires reporting certain serious incidents to the relevant market-surveillance authorities. After reporting, the provider must investigate, assess risk, take corrective action as needed, and cooperate with authorities.
- Deployer of a high-risk AI system: Article 26 includes duties concerning logs under the deployer’s control. The six-month minimum described below is a deployer-log rule, not a general incident-file retention period.
- Provider of a systemic-risk GPAI model: Commission materials describe separate duties to track, document, and report relevant serious incidents and possible corrective measures to the AI Office and, as appropriate, national competent authorities.
These EU rules are not a universal template for all AI incidents worldwide. Other applicable sectoral, national, privacy, product-safety, cybersecurity, or contractual requirements may affect what must be recorded, retained, or reported.
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Use a structured incident record with links to supporting evidence, rather than relying on a single narrative report. The following is a practical file design based on the duties and traceability needs described in the EU materials; it is not a list of fields expressly required in every case.
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1. Identify the system and its operating context
- System name, version, and relevant configuration at the time of the event.
- Provider, deployer, and the people or teams responsible for operation and incident response.
- Intended purpose, deployment context, and the workflow in which the system was used.
- Relevant changes to the model, system, configuration, data, or surrounding workflow, with dates where available.
Context matters because the same model or component can behave differently across deployments. Record what the system was meant to do and how it was actually being used, without treating those two things as necessarily identical.
2. Record what happened and how it was detected
- Detection time and the time the organization became aware of the incident; include time zones and distinguish them from the time the event itself occurred.
- A chronological account of observed events, affected people or processes, and the outcome known so far.
- The source of each observation, such as a user report, monitoring alert, system log, or investigator finding.
- An initial severity assessment and the basis for it, including uncertainty and what is still unknown.
Keep direct observations separate from hypotheses. For example, label a suspected link between an output and harm as a hypothesis until the evidence supports a stronger conclusion.
3. Preserve relevant technical evidence
- Relevant automatically generated logs and monitoring signals, along with the system version and configuration state they relate to.
- Input and output records where they can lawfully be retained and are relevant to understanding the event.
- Evidence of who accessed, exported, or changed records, and when; document custody and handling so later reviewers can understand whether evidence may have changed.
- Any known gaps, retention limits, clock differences, or other constraints that affect how the evidence should be interpreted.
The AI Act requires high-risk AI systems to technically support automatic event logging over their lifetime. Logging is intended to support risk identification and post-market and operational monitoring. For certain high-risk law-enforcement systems covered by Annex III, point 1(a), Article 12 specifies minimum log information that includes each use’s start and end, the reference database, matched input data, and the human verifiers.
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4. Document the assessment and investigation
- The suspected causal relationship, or why a causal relationship is reasonably likely, and the evidence supporting that assessment.
- Alternative explanations considered, investigation steps taken, and what those steps found.
- Risk assessment, including the potential scope and seriousness of harm and any uncertainty that remains.
- Evidence limitations and decisions about what additional information is needed.
Do not state that the system caused an outcome merely because the event followed its use. Preserve the distinction between a confirmed cause, a suspected connection, and an unresolved question.
5. Track response decisions and corrective action
- Containment or mitigation steps, who approved them, and when they took effect.
- Decisions to change, disable, roll back, or continue using the system, including the reasons and evidence considered.
- Any system or model changes, validation performed after changes, and the results relevant to the incident.
- Open actions, owners, due dates, and the evidence used to close them.
Following an Article 73 report, the provider must investigate without delay, including risk assessment and corrective action. The provider must cooperate with competent authorities. If a change could affect later evaluation of the cause, the provider should inform authorities before making that change.
6. Keep a complete notification and follow-up record
- Who was notified, when, by whom, and what information was sent.
- Copies or controlled records of initial and follow-up reports, regulator requests, and responses.
- Cooperation with competent authorities and the status of requested evidence or actions.
An initial Article 73 report may be incomplete and followed by a complete report. Record which information was available at each stage rather than silently replacing the earlier account.
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Apply the Article 73 reporting clock carefully
The Article 73 deadlines apply to providers reporting serious incidents involving high-risk AI systems under the EU AI Act. The provider must report immediately once it establishes a causal link between the high-risk system and the serious incident, or a reasonable likelihood of such a link. The applicable maximum is measured from awareness, so record when the provider—or, where applicable, the deployer—became aware.
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| Case | Reporting timing under Article 73 |
|---|---|
| General serious-incident case | Immediately after the causal link or reasonable likelihood is established; no later than 15 days after awareness. |
| Specified widespread infringement or serious-incident case | Immediately; no later than two days after awareness. |
| Death-related case | Immediately after a causal link is established or suspected; no later than 10 days after awareness. |
These are maximum deadlines, not waiting periods. The exact trigger and applicable category matter; document the facts and timing used to determine them. If the report is initially incomplete, submit the information available and follow it with a complete report as permitted by Article 73.
Do not conflate the two retention periods
The AI Act sets different retention rules for deployer-controlled logs and specified provider compliance documents. Neither should be casually described as a universal retention period for every incident record.
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| Record type | Who keeps it | Period described in the Act |
|---|---|---|
| Automatically generated logs under the deployer’s control for a high-risk AI system | Deployer | For a period appropriate to the intended purpose and at least six months, unless applicable Union or national law provides otherwise (Article 26). |
| Enumerated compliance documentation, including technical documentation, quality-management documentation, certain notified-body records, and the EU declaration of conformity | Provider of a high-risk AI system | Available to national competent authorities for 10 years after market placement or putting into service (Article 18). |
For the incident file itself, document the retention basis, the role responsible for each record, access controls, and any privacy or confidentiality limits. Set retention with the applicable laws and the organization’s evidence needs in view; Article 18’s ten-year period is not a blanket rule that all incident data must be stored for ten years.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Handle systemic-risk GPAI incidents as a separate track
Providers of systemic-risk GPAI models have distinct duties from providers of high-risk AI systems. The Commission says they must track, document, and report relevant serious-incident information and possible corrective measures without undue delay to the AI Office and, as appropriate, national competent authorities. Relevant incidents can include serious cybersecurity breaches involving a model or its physical infrastructure, such as model-parameter exfiltration or cyberattacks, where they relate to the Act’s systemic-risk duties.
Commission guidance also addresses documented adversarial testing, assessment and mitigation of systemic risks, incident reporting, and cybersecurity safeguards. A file for this regime should make those assessments, incident facts, and proposed or completed corrective measures traceable without importing Article 73’s high-risk-system deadlines as if they automatically applied to GPAI providers.
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Make the file usable under pressure
A regulator-ready file is not just a document assembled at reporting time. Store the incident narrative, evidence references, decision history, and notification record so that authorized responders can locate them quickly and understand how they fit together.
- Use a clear incident identifier and timestamped chronology.
- Keep original evidence or controlled references to it distinct from summaries and interpretations.
- Record the author, date, and basis for material assessments and decisions.
- Restrict access appropriately, while preserving an auditable record of access and changes.
- Track unanswered questions and follow-up actions instead of presenting an incomplete investigation as settled.
A Carnegie Mellon University Software Engineering Institute presentation dated May 14, 2026, identifies deployment context, lifecycle events, and explainability as practical documentation challenges. Its observations are useful context, not EU legal requirements; the presentation states that its opinions should not be construed as an official U.S. Government position.
What this means outside the EU
The legal duties described here are EU-focused. They do not establish a single mandatory AI incident-file format for all U.S. organizations or for other jurisdictions. Requirements may still arise under sectoral, state, privacy, product-safety, cybersecurity, or contractual rules, so determine the applicable obligations for the specific system, organization, and location before relying on this file structure as a compliance checklist.
The European Commission’s explanatory materials describe the AI Act using the consolidated text as of July 27, 2026, and characterize explanatory summaries as non-binding. For a legal obligation, consult the enacted EU AI Act text, particularly Articles 12, 18, 26, and 73, and obtain qualified advice where applicability or reporting triggers are uncertain.
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