AI Risk Classification Under the EU AI Act
For providers and deployers: find out which risk level your AI system has and what that level means for your duties.
How the Act sorts AI systems by risk
The Act sets duties by risk level. Prohibited AI practices (Article 5) are banned, with limited exceptions; the bans in points (ba) and (bb) apply from 2 December 2026. High-risk AI systems must meet the requirements and duties of Chapter III, Sections 1 to 3: from 2 December 2027 for Annex III systems and from 2 August 2028 for Annex I products, under Regulation (EU) 2026/1744. AI systems with transparency duties (Article 50), such as chatbots and generated content, must disclose that people deal with AI or that content is AI-generated. Other AI systems have no system-specific duties, but providers and deployers still owe general duties such as AI literacy (Article 4). Start with the decision tree to find your system's level.
Guides for classifying your AI system and documenting the result
Is My AI System High-Risk? A Decision Tree
Interactive EU AI Act risk classification decision tree. Covers Article 5 prohibited practices, all 8 Annex III high-risk categories, GPAI model obligations, and Article 50 transparency.
Annex III Deep Dive: All 8 High-Risk Categories
The 8 areas of EU AI Act Annex III in which AI systems are high-risk, with examples from the Annex wording, exclusions, and the Article 6(3) exception.
Annex I High-Risk AI Systems: The Product-Safety Route
Which AI systems in regulated products are high-risk under Article 6(1), which rules apply, and what changes for machinery.
Annex IV Technical Documentation: The Nine Points
The nine points of EU AI Act Annex IV for the technical documentation of high-risk AI systems, with the rules around them: timing, retention, SME form and scope.
Shadow AI: Building an AI System Inventory
How to find the AI systems in your organisation and record them in one register: five steps, a register template and the duties in Articles 4, 26 and 49.
Scanara prepares evidence from your repositories
Scanara reads your connected GitHub repositories and runs rule-based scans for standard AI and machine-learning patterns. It can miss non-standard code. Separately, it generates draft documentation from templates and your assessment answers as evidence for your compliance work. You make the classification decisions.