How long must AI model documentation be retained after retirement?

Under EU AI Act Article 18(1), providers must retain technical documentation for 10 years after the last AI system covered by it is placed on the market. GDPR records must be retained for the applicable limitation period.

What notice period should be given before retiring an AI model?

Minimum 6 months for production models with external users, minimum 3 months for internal models. Critical infrastructure models may require longer notice periods based on contractual or regulatory obligations.

Must training data be deleted when an AI model is retired?

Apply GDPR data minimization and purpose limitation principles. If training data was collected solely for the retired model and no other lawful purpose exists, it should be deleted. Retention requires a documented lawful basis.

How do you handle pending complaints about a retired AI model?

Complete investigation of all pending complaints before or after retirement. Retain sufficient documentation and system information to investigate complaints that arrive after retirement, for the applicable limitation period.

Can a retired AI model be reactivated?

Only after re-completing the deployment approval process, verifying that training data is still representative, confirming regulatory compliance, and updating technical documentation. Treat reactivation as a new deployment.

Quick answer

An AI model retirement policy governs how organizations decommission AI models, covering timeline communication, user migration, data retention and deletion, knowledge preservation, and compliance with EU AI Act post-market monitoring obligations that extend beyond active deployment.

Updated June 2026 · MmowW AI Compliance

AI Model Retirement Policy: End-of-Life Planning, Migration, and Data Handling

Why AI Model Retirement Needs a Policy

AI models are not permanent assets. They degrade as data distributions shift, regulations change, superior alternatives emerge, or the use case becomes obsolete. Without formal retirement procedures, organizations accumulate technical debt, maintain unnecessary security exposure, and risk using degraded models for critical decisions.

The EU AI Act Article 72 addresses post-market monitoring obligations for high-risk AI, and these obligations do not terminate simply because a model is retired. Documentation, incident records, and monitoring data must be retained for defined periods.

Retirement Triggers and Decision Framework

Trigger	Assessment Criteria	Decision
Performance degradation	Accuracy below defined threshold for 3 consecutive months	Retire or retrain
Regulatory change	Model cannot meet new compliance requirements	Retire and replace
Superior replacement	Successor model validated and deployment-ready	Retire after migration
Security vulnerability	Unfixable vulnerability in model architecture or dependencies	Immediate retirement
Business discontinuation	Use case no longer supported by business strategy	Retire with archival
Data obsolescence	Training data no longer representative of current population	Retire or retrain with current data

Retirement Process Phases

Phase 1: Decision and Planning (4-8 weeks before retirement)

Document the retirement rationale, identify all dependent systems and users, plan migration to successor model or alternative workflow, and define the retirement timeline. Notify all deployers (for provider-side retirement) or affected business units (for deployer-side retirement).

Phase 2: Migration (2-4 weeks before retirement)

Deploy the successor model in parallel. Run dual-mode operation to validate equivalent or superior performance. Migrate integrations, monitoring, and documentation to the successor. Provide transition support to users and downstream systems.

Phase 3: Decommission (retirement date)

Remove the model from production serving. Disable API endpoints with informative error responses directing users to the successor. Revoke access credentials specific to the retired model. Archive model artifacts according to retention policy.

Phase 4: Post-Retirement (ongoing)

Retain documentation and audit records per regulatory requirements. Process any pending complaints or incident investigations. Delete training and operational data according to data retention schedules. Monitor for unauthorized continued use of the retired model.

Data Handling During Retirement

Data associated with retired models falls into four categories:

Training data: Retain or delete based on GDPR data minimization (Article 5(1)(c)) and purpose limitation (Article 5(1)(b)). If data was collected solely for the retired model, delete it unless another lawful purpose exists
Model weights and artifacts: Archive for regulatory audit purposes. EU AI Act requires technical documentation retention for 10 years after the last unit is placed on the market (Article 18(1))
Operational logs: Retain for the period specified in logging policy and applicable regulation. High-risk AI logs must be kept for the period required by Annex IV
User data and outputs: Process deletion requests. Retain only what is necessary for ongoing legal obligations or legitimate interests

Communication and Notification

Provide clear retirement notices: minimum 6 months for production models with external users, minimum 3 months for internal models. Include: retirement date, rationale, migration path, successor model details, support availability during transition, and data handling plans. For API-served models, implement deprecation headers before retirement.

Knowledge Preservation

Before retirement, document lessons learned: model design decisions, performance characteristics, known limitations, failure modes, and deployment insights. This knowledge informs successor model development and prevents repeating past mistakes. Store post-mortem documentation in the organization's AI knowledge base.

Regulatory Compliance After Retirement

EU AI Act Article 72 post-market monitoring obligations survive model retirement for the documentation retention period. Providers must retain technical documentation, conformity assessment records, and EU declaration of conformity for 10 years. Deployers must retain logs generated by the AI system for the period required by applicable law. National data protection authorities may request access to these records during the retention period.

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This article is for informational purposes only and does not constitute legal advice. Regulatory requirements change frequently — verify current rules with official sources. Built by Sawai Gyoseishoshi Office, Hiroshima, Japan.