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Implements a risk-based regulatory framework for AI, with specific attention to single-purpose AI systems used in risky contexts and general-purpose AI systems with significant capability. Imposes risk-dependent requirements related to accuracy, cybersecurity, evaluation, monitoring, transparency, and registration. Defines exceptions, penalties, and governance structures.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has comprehensive coverage of approximately 15-18 subdomains, with strong focus on AI system security (2.2), malicious actors (4.1, 4.2, 4.3), governance failure (6.5), competitive dynamics (6.4), and AI safety failures (7.1, 7.2, 7.3, 7.4). Coverage is concentrated in security, misuse prevention, governance, and AI system safety domains, with significant attention to discrimination risks (1.1, 1.3) and privacy concerns (2.1).
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
The regulation governs AI use across 10 major sectors with particularly detailed coverage of Public Administration, National Security, Health Care, Education, Finance and Insurance, and Professional Services. High-risk AI systems are specifically identified in law enforcement, border control, critical infrastructure, employment, education, healthcare, and justice administration.
Hard Law
Legislative Status Summary
This is a binding EU Regulation with comprehensive enforcement mechanisms, mandatory obligations, administrative penalties up to EUR 35 million or 7% of global turnover, and designated enforcement authorities.
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Target
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Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document comprehensively covers all AI lifecycle stages from planning through operational monitoring. It provides detailed requirements for data collection and processing, model development, validation and testing, deployment procedures, and ongoing monitoring. The regulation addresses both high-risk AI systems and general-purpose AI models across the entire lifecycle.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly distinguishes between AI systems and AI models, with comprehensive coverage of general-purpose AI (GPAI) including systemic risk models. It defines compute thresholds (10^25 FLOPs) for GPAI classification and addresses open-source models with specific exemptions. The regulation does not explicitly use terms 'frontier AI', 'foundation models', 'generative AI', 'predictive AI', or 'task-specific AI' but covers these concepts through its definitions and requirements.
Document data from AGORA, CSET Emerging Technology Observatory.