General Purpose AI Code of Practice, Transparency Chapter

• Authority: European Union
• Jurisdiction: Multinational
• Collections: Editors' Picks;Miscellaneous documents
• Most recent activity: Enacted
• Most recent activity date: 2025-07-10

Risk subdomain coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.

• Governance failure
• Lack of transparency or interpretability

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• AI system security vulnerabilities
• Competitive dynamics
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal risk domain coverage, focusing primarily on governance and transparency mechanisms rather than specific AI risks. It addresses governance failure (6.5) through documentation and oversight requirements, and touches on lack of transparency (7.4) through disclosure obligations. The document is procedural in nature, establishing compliance frameworks rather than directly addressing most risk categories.

Sector coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Information
• Scientific Research & Development Services

All other sectors had no coverage in this document.

Sectors Summary

This document does not govern specific economic sectors. Rather, it establishes horizontal transparency and documentation requirements for providers of general-purpose AI models across all sectors. The obligations apply to AI model providers regardless of the downstream sectors in which their models may be deployed.

Legislative Status

Soft Law

Legislative Status Summary

This is a voluntary Code of Practice that uses predominantly voluntary language ('commit to', 'will', 'are encouraged') and relies on signatories choosing to adhere to it. While it references binding obligations from the AI Act, the Code itself serves as guidance for demonstrating compliance rather than creating new binding legal obligations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: European Union; AI Office
• Summary: The document is a Code of Practice developed under the EU AI Act framework, with the AI Office playing a central role in its development and implementation as indicated by references to the AI Office's oversight responsibilities.

Target

• Entity Types: AI_Developer
• Entities: providers of general-purpose AI models; Signatories
• Summary: The Code explicitly targets providers of general-purpose AI models who become Signatories to the Code. These are the entities that must comply with the documentation and transparency obligations outlined.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: AI Office; national competent authorities
• Summary: The AI Office is designated as the primary enforcement body with authority to request information and assess compliance. National competent authorities also have supervisory roles, particularly for high-risk AI systems.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: AI Office; national competent authorities
• Summary: The AI Office monitors compliance through information requests and assessment procedures. National competent authorities also conduct supervisory monitoring, particularly for high-risk AI systems built on general-purpose AI models.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Build and Use Model
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document primarily covers the Deploy and Operate and Monitor stages of the AI lifecycle, focusing on documentation requirements when placing models on the market and ongoing obligations to update and provide information. It implicitly touches on Build and Use Model through documentation of model characteristics, but does not substantially address earlier stages like planning, design, or data collection.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• AI Systems
• General Purpose AI
• Open Weight / Open Source

Technical Scope Summary

The document explicitly focuses on general-purpose AI models as its primary scope, with specific provisions for models with systemic risk. It does not explicitly mention foundation models, generative AI, predictive AI, task-specific AI, or compute thresholds. Open-source models are mentioned with an exception clause.