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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →There is no universal retention period for AI safety logs. Under the EU AI Act, providers and deployers of covered high-risk AI systems must keep certain automatically generated logs under their control for a period appropriate to the system’s intended purpose and for at least six months, subject to applicable law. Outside that specific scope, set and document a period for each log category based on its purpose, privacy impact, and applicable legal and contractual requirements.
What retention period does the EU AI Act require?
For high-risk AI systems covered by Regulation (EU) 2024/1689, the answer depends on who controls the logs. Article 19(1) applies to providers; Article 26(6) applies to deployers. Each provision concerns automatically generated logs under that operator’s control. The required period must suit the system’s intended purpose and be at least six months, unless applicable Union or national law provides otherwise, particularly data-protection law. See the consolidated EU AI Act text (version dated 2026-07-27).
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| Question | What the Act says |
|---|---|
| Which systems? | High-risk AI systems within the Act’s relevant scope. |
| Which logs? | Automatically generated logs under the relevant provider’s or deployer’s control. |
| How long? | A period appropriate to the system’s intended purpose, with a minimum of six months unless applicable Union or national law provides otherwise. |
| Who is responsible? | Providers under Article 19(1) and deployers under Article 26(6), for logs under their respective control. |
Do not apply six months automatically to every AI system, every log, or every organization. First establish that the system and the operator’s role fall within the relevant provisions, and identify which records are under that operator’s control. National, sector-specific, contractual, and data-protection requirements may affect the period.
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Logging capability is not the same as retention
Article 12 requires covered high-risk AI systems to technically allow automatic recording of events over the system’s lifetime. That capability supports identifying situations that may create risk, post-market monitoring, and monitoring system operation. Articles 19 and 26 address how long covered logs under a provider’s or deployer’s control must be kept. A system’s ability to record events throughout its lifetime does not itself mean every recorded log must be retained for that entire time.
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Do not confuse logs with provider documentation
Article 18’s ten-year period after placing a system on the market or putting it into service applies to specified provider documentation, including technical documentation and quality-management-system documentation. It is not a general ten-year retention period for operational safety logs.
How does personal data change the decision?
If logs contain personal data, the GDPR’s storage-limitation principle applies to processing within its scope. Article 5(1)(e) says personal data should be “kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed.” The GDPR also recognizes specified exceptions and safeguards. The AI Act’s logging provisions expressly leave room for applicable data-protection law.
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That means a retention schedule should distinguish useful safety evidence from identifiable content that no longer needs to be kept. Consider whether redaction, aggregation, or anonymisation can preserve information needed for monitoring or investigation while reducing exposure. The appropriate treatment depends on the actual fields and purpose; a label such as “safety log” does not by itself settle whether the data can be kept.
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How to build a practical retention policy
A sound policy assigns periods by log category rather than inventing one organization-wide duration for all AI records. The steps below are a policy-design approach, not a universal period prescribed by a single standard.
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- Inventory the records. List each category, such as safety events, model or system version and configuration, input/output traces, human interventions, incident records, access or security events, and operational telemetry. Record the system, record owner, storage location, and whether the data is personal or sensitive.
- State the purpose for each category. Specify the concrete need—such as risk detection, incident investigation, post-market monitoring, security response, audit, or a defined legal or contractual obligation. Avoid keeping identifiable content solely because it might be useful someday.
- Map scope, control, and obligations. Establish the system’s AI Act classification, your role as provider or deployer, and which records you control. Check applicable data-protection law, sector requirements, contracts, national rules, and any litigation hold. Where a legal minimum may apply, incorporate it into the schedule and obtain qualified jurisdiction-specific advice on conflicts or exceptions.
- Choose and document a period. Set a period that covers the legitimate monitoring, investigation, or accountability need, while accounting for applicable requirements. Document why it is suitable for that log category. No single default duration is established here for non-high-risk systems, ordinary telemetry, or all jurisdictions.
- Set review and expiry actions. Define who reviews the schedule, when the review occurs, and how records are erased or anonymised when the purpose ends. For a hold or other basis that requires longer retention, record its basis, scope, owner, and review date. The UK Information Commissioner’s Office (ICO) recommends documented periods where possible, regular review, and deletion or anonymisation when data is no longer needed in its storage-limitation guidance.
- Protect retained records. Treat access controls and security safeguards as separate from the retention decision. Longer retention increases the amount of data that must be protected; access restrictions do not justify keeping data beyond its purpose. The GDPR includes both storage limitation and integrity and confidentiality principles.
How to choose between keeping, reducing, or deleting a log
For each category, weigh the factors that determine whether the record remains useful and proportionate:
- Purpose and detection window: How long after an event could it realistically be detected, investigated, or used for monitoring?
- Legal or contractual floor: Does a specific rule or agreement require a minimum period or a hold?
- Identifiability and sensitivity: Does the log contain personal, sensitive, or otherwise high-impact information, and can it be made less identifying?
- Role and control: Is your organization the provider, deployer, or another party, and who actually controls the record?
- Consequences of retaining or deleting: What investigation or accountability evidence could be lost, and what privacy or security exposure comes with continued retention?
- Alternatives and operations: Would aggregation, redaction, or anonymisation preserve the safety value? Can the organization retrieve and securely delete the records as scheduled?
Longer retention can preserve evidence for later review but prolongs the period during which personal or sensitive data must be protected. Shorter retention limits that exposure but may remove evidence needed for a justified investigation or monitoring purpose. No universal benchmark duration is established by the sources cited here.
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What other guidance says—and does not say
The ICO’s UK GDPR storage-limitation guidance says there are no fixed retention time limits by data type under the UK GDPR; it recommends documented periods, regular review, and erasure or anonymisation when data is no longer needed. The ICO page also says the guidance is under review following changes made by the UK Data (Use and Access) Act. Its AI data-minimisation guidance discusses retention schedules and AI data-minimisation measures. This is practical regulator guidance, not a substitute for checking the current law applicable to a particular organization.
NIST’s AI Risk Management Framework page reports that version 1.0 is being revised and does not establish a specific AI log-retention period. Neither that framework page nor the cited regulator guidance supplies one universal duration for all AI safety logs.
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- Offline conversations on your PC: Draft, brainstorm and ask questions without a cloud account or subscription for the included local model. Your computer's CPU and RAM run the AI; the USB stores the package and a browser displays the controls.
- Choose what you keep: Private Session does not save new app chats or pinned memories. Memory Mode retains them on the drive for reuse. Neither mode promises secure erasure of Windows/browser traces; local diagnostic logs are separate.
- Check your Windows PC: Windows 10/11 64-bit with a compatible x64 CPU; the launcher checks CPU support and available resources. Essential has an 8 GB RAM starting floor. USB 3.0 or faster is recommended. Startup and response speed vary by PC.
- Polished prototype, human support: An evolving 1MatrixTech product with clear setup guidance and company troubleshooting support. Extract a ZIP first, if supplied, then run aibrain.exe from the complete folder. Verify important AI answers.
What must be checked for a real policy?
The right period for a specific organization cannot be determined without details such as the system’s classification and deployment context, log fields and purposes, operator roles, countries, sector requirements, and contracts. The cited sources do not settle every national or sectoral regime, or how the AI Act minimum and data-protection duties interact for every possible log set. Have qualified counsel review jurisdiction-specific requirements before adopting a policy.
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