A comprehensive walkthrough of the fourteen elements required by Annex IV, cross-referenced against Articles 9 through 16 and the implementing acts. Includes worked examples across three Annex III use case categories — credit scoring, recruitment screening, and medical device AI — with annotated documentation templates and common pitfalls drawn from early-adopter implementations.
Scope
This paper covers every element that Annex IV of the EU AI Act requires providers of high-risk AI systems to include in their technical documentation. Each element is examined in turn, with references to the specific Articles that impose the underlying obligation.
The fourteen elements span the full lifecycle of an AI system: from a general description of the system and its intended purpose, through the design and development methodology, training and validation data governance, testing procedures, risk management measures, and post-market monitoring plans.
Worked examples
Three worked examples are included, each drawn from a different Annex III use case category:
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Credit scoring (Annex III, Section 5b): A provider operating a credit risk assessment model used by banks across four EU member states. The example covers multi-jurisdiction deployment, GDPR Article 9 special category data handling, and the interaction between the AI Act’s data governance requirements and existing EBA guidelines.
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Recruitment screening (Annex III, Section 4a): A deployer using a third-party AI system for CV screening and candidate shortlisting. The example addresses deployer-specific obligations under Article 26, the Article 27 FRIA requirement, and what deployers should demand from providers under Article 25.
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Medical device AI (Annex III, Section 5a): A provider of a clinical decision-support system classified as both a medical device and a high-risk AI system. The example covers dual conformity assessment, the interaction between the AI Act and the Medical Device Regulation, and notified body involvement.
Common pitfalls
The paper concludes with a catalogue of documentation failures observed in early-adopter implementations, including incomplete risk management system descriptions, missing post-market monitoring plans, inadequate human oversight documentation, and version control gaps that undermine the auditability of the documentation set.