Lifecycle coverage
From inception and design through deployment, post-market surveillance, modification, and end-of-life.
EN 18286
A QMS standard written for AI systems
EN 18286 specifies requirements for a quality management system for AI systems in the context of the EU AI Act. AI QMS Online is structured so teams can implement those requirements with operational records, not only policies.
What EN 18286 expects
Providers establish, implement, maintain, and continually improve a QMS that runs for the full life of the AI system.
Integrated specialisms
Risk management, cybersecurity, data governance, technical documentation, human oversight, and logging work as one system.
Written, controlled evidence
Documented information with review, change control, traceability, and retention suitable for regulatory scrutiny.
Clause-oriented platform map
Illustrative alignment of platform capability areas to EN 18286 themes.
| Clause theme | Platform support |
|---|---|
| 4 Context | Process establishment, regulatory determination, scope of the QMS and systems in scope, compliance strategy and essentials approach, documented information control. |
| 5 Leadership | Leadership commitment and quality policy records; roles, responsibilities, and authorities; accountability and RACI across the AI lifecycle. |
| 6 Planning | QMS-level risks and opportunities, quality objectives, planning of changes to the management system. |
| 7 Support | Resources, competence system design, awareness, internal and external communication including authority communications. |
| 8 Operation | Risk management for AI systems, lifecycle stages, design and development, data processes, external providers, release, technical documentation and instructions for use. |
| 9 Operation & control | Deployment and operational control, support services, supply chain, modification to AI systems, post-market monitoring, incidents, nonconformity and corrective action. |
| 10 Performance evaluation | Monitoring and measurement inputs, internal audit programmes and executions, management review, continual improvement. |
Essentials in practice
EN 18286 connects the QMS to essential requirements that high-risk AI systems must meet. The platform keeps those workstreams linked to each AI system identity.
- ARisk management
Ongoing risk process with residual risk decisions and re-evaluation after change or field findings. - BData & data governance
Quality, relevance, and control of data used for training, validation, and operation. - CTechnical documentation
Living TD and related design/release evidence assembled for conformity and inspection. - DRecord-keeping
Registers, retention, and archive for automatic logs and QMS records over regulatory horizons.
- ETransparency
Structured support for transparency and marking obligations where they apply. - FHuman oversight
Measures, competence, and operational evidence that humans can understand and intervene. - GAccuracy, robustness & cyber
Performance and cybersecurity control evidence tied into risk and operation. - QQuality management
The system that makes the essentials repeatable, auditable, and improvable.
Implement EN 18286 with operational discipline
See how clause workflows, evidence packages, and continuous processes look for your organisation.