This appendix maps the obligations of Regulation (EU) 2024/1689 (the AI Act) (1, European Union, 2024) to the architectural controls that satisfy them, the evidence that demonstrates satisfaction, the owning roles and the pipeline gates at which evidence is checked. The mapping is an architectural instrument, not legal advice.
Each row names the article, a short paraphrase of the obligation (the legal text governs), the control, the evidence produced in the evidence-as-code manner of Chapter 11 and Architecture as Code (66, Nordqvist, 2025), the accountable role, and the gate: design (decision record review), build (continuous integration), evaluate, release (promotion to production), operate (scheduled checks) or change (triggered by a change of model, data or purpose). Chapter 8 explains the classification that selects the applicable rows.
Article 16 makes the provider responsible for the properties in Articles 9 to 15 and for the obligations that follow.
Primary topics explored
- How to read the mapping
- Providers of high-risk AI systems
- Deployers of high-risk AI systems
- Providers of general-purpose AI models
- Transparency obligations under Article 50
- The mapping as YAML
About AI Governance
AI Governance is Book 2 of The Transformed Architecture. It shows how large European enterprises and public authorities decide what artificial intelligence is used for, classify and manage its risks, meet the obligations of the EU AI Act and its neighbours, choose and contract their suppliers, organise the forums that take decisions, and produce the evidence that shows it is all true.
It builds on the conclusions of Architecture as Code.
Chief risk and compliance officers, AI governance boards, CIOs and chief architects, and senior officials in public authorities.
Gunnar Nordqvist
Conceived, directed and published the books of The Transformed Architecture.
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Appendix A: Appendix A: EU AI Act Obligation Mapping in AI Governance gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “Appendices” and is one of 32 drawn from the manuscript.