Providers of high-risk AI systems must prepare technical documentation before the system is placed on the market, following the content set out in Annex IV, and keep it up to date. The documentation shows how the system meets the requirements for high-risk AI.
Article 11 requires providers to draw up technical documentation before a high-risk system goes to market, and to keep it current for the life of the system. Annex IV sets the minimum content: a general description of the system, its development process, data requirements, monitoring and control arrangements, performance metrics, the risk management system, a list of changes, and the EU declaration of conformity.
The documentation has to demonstrate compliance with the core requirements: data governance under Article 10, record-keeping under Article 12, transparency for deployers under Article 13, human oversight under Article 14, and accuracy, robustness, and cybersecurity under Article 15.
In practice, documentation fails when it is written after the fact or scattered across teams. Assign one owner for the file, tie each entry to a version of the system, and record the reasoning behind design decisions, because auditors test whether the evidence matches what the system actually does.
Day 3 of the course covers documentation, evidence, and record-keeping, including the human oversight and transparency requirements that the file must prove.
Build the technical file alongside development rather than at the end. Assign one owner and tie each entry to a system version, so the evidence matches what is running in production.
“Build the technical file during development, then rebuilding it at audit time rarely matches what is running in production.”
This ISO/IEC 42001 Lead Auditor training prepares audit, risk, and compliance professionals to assess Artificial Intelligence Management Systems (AIMS) in a structured, defensible way. The course focuses on planning, conducting, and closing ISO/IEC 42001 audits in real organizational environments, addressing governance, ethical use of AI, risk management, and regulatory expectations shaping 2024–2025. Participants learn to interpret ISO/IEC 42001 requirements from an auditor’s perspective, evaluate objective evidence, and formulate audit conclusions that stand up to certification scrutiny and executive review.
View courseThis Lead AI Risk Manager training prepares professionals to design, operate, and defend an AI risk management program aligned with regulatory and governance expectations. The course focuses on practical risk identification, decision traceability, and defensible mitigation strategies across the AI.
View courseThis ISO/IEC 42001 Lead Implementer course trains professionals to design and deploy an Artificial Intelligence Management System that stands up to regulatory, ethical, and operational scrutiny.
View courseThe EU AI Act applies to AI systems placed on the EU market, put into service there, or whose outputs are used in the EU, wherever the company is based. Applicability is decided per system and per use case.
The course suits compliance and AI governance leads, legal counsel and data protection officers, technical AI teams, and consultants or executives who must show defensible AI governance. Each role works through a different part of the AI Act.
The EU AI Act sorts AI systems into four levels: unacceptable risk (prohibited), high risk, limited risk with transparency duties, and minimal risk. A system is high risk if it is a safety component covered by EU product legislation or falls under a use case listed in Annex III.
A fundamental rights impact assessment (FRIA) is a documented evaluation of how a high-risk AI system could affect people's fundamental rights before it is deployed. Under Article 27, it applies to certain deployers, including public bodies and private entities providing public services.
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