Open Source Developers Guide to the EU AI Act

AI Policy @🤗: Open ML Considerations in the EU AI Act

Advancing responsible AI across Europe

OpenAI shares how its safety, security, transparency, and provenance practices support responsible AI governance in Europe. The work will continue as the EU AI Act advances.

The EU Code of Practice and future of AI in Europe

OpenAI joins the EU Code of Practice, advancing responsible AI while partnering with European governments to drive innovation, infrastructure, and economic growth.

Supporting Europe’s work in ensuring a trustworthy AI ecosystem

OpenAI supports the EU Code of Practice on AI content transparency, advancing provenance standards and tools to help people understand AI-generated content.

Accelerating AI adoption in Europe

OpenAI and Allied for Startups release the Hacktivate AI report with 20 actionable policy ideas to accelerate AI adoption in Europe, boost competitiveness, and empower innovators.

The next chapter for AI in the EU

OpenAI launches the EU Economic Blueprint 2. 0 with new data, partnerships, and initiatives to accelerate AI adoption, skills, and growth across Europe.

OpenRAIL: Towards open and responsible AI licensing frameworks

Building standards for the next phase of AI

OpenAI outlines a path to shared global AI standards, calling for coordinated evaluation, reporting, and governance to improve safety.

Codex is Open Sourcing AI models

OpenAI’s EU Economic Blueprint

Today, OpenAI is sharing the EU Economic Blueprint—a set of proposals to help Europe seize the promise of artificial intelligence, drive sustainable economic growth across the region, and ensure that AI is developed and deployed by Europe, in Europe, for Europe.

Introducing OpenAI for Countries

A new initiative to support countries around the world that want to build on democratic AI rails.

From Legal Text to AI-specific Risk Sources: A Systematic Analysis of the EU AI Act's High-Risk Requirements

The paper systematically classifies the EU AI Act’s high‑risk requirements, finding that only a minority directly address AI‑specific risk sources while most impose organizational and documentation obligations. From these risk‑related requirements, the authors derive a consolidated list of distinct AI‑specific risk sources, creating an EU AI Act Risk Source List. This list aims to bridge the gap between legal obligations and AI risk‑management practice by providing a structured reference for comparing the Act’s implicit risk coverage with existing AI risk taxonomies.