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Using custom GPTs ChatGPT for customer success teams Applications of AI at OpenAI Research with ChatGPT Analyzing data with ChatGPT Financial services Responsible and safe use of AI Writing with ChatGPT ChatGPT for research Creating images with ChatGPT Personalizing ChatGPT ChatGPT for finance teams Getting started with ChatGPT Working with files in ChatGPT ChatGPT for sales teams Prompting fundamentals ChatGPT for managers Using projects in ChatGPT ChatGPT for marketing teams Brainstorming with ChatGPT AI fundamentals ChatGPT for operations teams Healthcare Our response to the Axios developer tool compromise Using skills OpenAI Full Fan Mode Contest: Terms & Conditions CyberAgent moves faster with ChatGPT Enterprise and Codex The next phase of enterprise AI Introducing the Child Safety Blueprint Introducing the OpenAI Safety Fellowship Industrial policy for the Intelligence Age OpenAI acquires TBPN Codex now offers more flexible pricing for teams Gradient Labs gives every bank customer an AI account manager OpenAI raises $122 billion to accelerate the next phase of AI Helping disaster response teams turn AI into action across Asia STADLER reshapes knowledge work at a 230-year-old company Inside our approach to the Model Spec Introducing the OpenAI Safety Bug Bounty program Helping developers build safer AI experiences for teens Update on the OpenAI Foundation Powering Product Discovery in ChatGPT Creating with Sora Safely How we monitor internal coding agents for misalignment OpenAI to acquire Astral Introducing GPT-5.4 mini and nano OpenAI Japan announces Japan Teen Safety Blueprint to put teen safety first Equipping workers with insights about compensation Why Codex Security Doesn’t Include a SAST Report Designing AI agents to resist prompt injection From model to agent: Equipping the Responses API with a computer environment Rakuten fixes issues twice as fast with Codex Wayfair boosts catalog accuracy and support speed with OpenAI Improving instruction hierarchy in frontier LLMs New ways to learn math and science in ChatGPT OpenAI to acquire Promptfoo Codex Security: now in research preview How Descript engineers multilingual video dubbing at scale How Balyasny Asset Management built an AI research engine Reasoning models struggle to control their chains of thought, and that’s good Introducing GPT-5.4 GPT-5.4 Thinking System Card Ensuring AI use in education leads to opportunity VfL Wolfsburg turns ChatGPT into a club-wide capability OpenAI and NORAD team up to bring new magic to “NORAD Tracks Santa” Accenture and OpenAI accelerate enterprise AI success OpenAI takes an ownership stake in Thrive Holdings to accelerate enterprise AI adoption What to know about a recent Mixpanel security incident Expanding data residency access to business customers worldwide Our approach to mental health-related litigation Inside JetBrains—the company reshaping how the world writes code Introducing shopping research in ChatGPT How GPT-5 helped mathematician Ernest Ryu solve a 40-year-old open problem OpenAI and Foxconn collaborate to strengthen U.S. manufacturing across the AI supply chain Disrupting malicious uses of AI: June 2025 Creating websites in minutes with AI Website Builder Addendum to OpenAI o3 and o4-mini system card: OpenAI o3 Operator OpenAI Deutschland Shipping code faster with o3, o4-mini, and GPT-4.1 Introducing Stargate UAE New tools and features in the Responses API Introducing Codex Addendum to o3 and o4-mini system card: Codex AI powers Expedia’s marketing evolution Strengthening America’s AI leadership with the U.S. National Laboratories Introducing ChatGPT Gov Operator System Card Computer-Using Agent Introducing Operator Bertelsmann powers creativity and productivity with OpenAI Trading Inference-Time Compute for Adversarial Robustness Announcing The Stargate Project Stargate Infrastructure The power of personalized AI Delivering LLM-powered health solutions Increasing accuracy of pediatric visit notes Practices for Governing Agentic AI Systems Superalignment Fast Grants Weak-to-strong generalization Partnership with Axel Springer to deepen beneficial use of AI in journalism
A Primer on the EU AI Act: What It Means for AI Providers and Deployers
2024-07-30 · via OpenAI News

Update from July 11, 2025: Following the publication of the final text of the Code of Practice for General Purpose AI, we’re sharing an overview of how we are approaching the entry into force of provisions applicable to General Purpose AI Models on August 2, 2025. 

Last year, we published this primer on the EU AI Act to lay out preliminary insight into how we were preparing for the implementation of these new legal requirements. 

Since then we’ve been actively involved in the implementation of the text by taking part in the elaboration of the Code of Practice for General Purpose AI, a framework for AI providers to comply with the EU AI Act. After months of collective efforts alongside experts, civil society and industry, a final Code has been published. Today, we are announcing our decision to sign the Code of Practice and use it to demonstrate compliance with our relevant obligations under the EU AI Act.  

By signing the Code we are taking a concrete step in our broader compliance plan with the EU AI Act. It reflects our commitment to ensuring continuity, reliability, and trust as regulations take effect, while continuing to partner with European businesses and citizens, bringing them increasingly capable, safe, and secure AI models to reap the benefits of the AI revolution.

Signing the Code reinforces many of the industry-leading safety and transparency measures we have pioneered over the past several years. We were one of the first companies to publish a comprehensive safety and security protocol, our Preparedness Framework (2023), which outlines our approach to deploying frontier AI models safely. 

In keeping with our commitment to continuously review and improve internal accountability and governance frameworks, we published an updated Preparedness Framework in April 2025. 

As we continue to develop and deploy increasingly capable technology, we actively monitor and mitigate a broad range of novel risks and real-world safety concerns to keep our models reliable and secure. And we are constantly refining and improving these processes. 

  • We have long published detailed System Cards and technical documentation with our major releases that lay out what our models can and can’t do, what risks we’ve tested for, and where we’re still learning. 
  • The Safety Hub provides public access to safety evaluation results for our models.
  • Our Red Teaming Network brings in external experts to pressure-test our models
  • The Model Spec offers a window into how we shape model behaviour to reflect human values and democratic norms.

Together, this work has been instrumental for setting security and safety standards in the industry and informing the development of a workable Code of Practice based on industry best practices. Building safe and responsible AI is never finished. We will continue to iteratively improve our approach to safety to help ensure that our technology is used to benefit everyone responsibly, wherever they are in the world.

We will work closely with the EU AI Office, relevant authorities and our customers as the AI Act is implemented in the coming months and years, so we can collectively secure the benefits of AI for Europe’s society and economy. 


Update: On September 25, 2024, we signed up to the three core commitments in the EU AI Pact.

  1. Adopt an AI governance strategy to foster the uptake of AI in the organization and work towards future compliance with the AI Act;
  2. carry out to the extent feasible a mapping of AI systems provided or deployed in areas that would be considered high-risk under the AI Act;
  3. promote awareness and AI literacy of their staff and other persons dealing with AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons affected by the use of the AI systems.

We believe the AI Pact’s core focus on AI literacy, adoption, and governance targets the right priorities to ensure the gains of AI are broadly distributed. Furthermore, they are aligned with our mission to provide safe, cutting-edge technologies that benefit everyone.


The EU AI Act(opens in a new window) is a significant regulatory framework designed to manage the development, deployment, and use of AI across Europe. It has a substantial focus on safety to promote trustworthy AI adoption in Europe while protecting health, safety, and fundamental rights. It introduces new requirements based on the risks associated with AI systems, with a particular focus on high-risk and unacceptable-use cases, as well as special obligations for general purpose AI (GPAI) models and systems. 

While the legislative process is complete and the law will enter into force in August 2024, further guidance and implementing legislation will be required to define the scope of the law, especially as it applies to GPAI models like OpenAI’s. 

At OpenAI, we are committed to complying with the Act, not only because this is a legal obligation, but also because the goal of the law aligns with our mission to develop and deploy safe AI to benefit all of humanity. We are proud to release models that are industry leading on both capabilities and safety. We believe in a balanced, scientific approach where safety measures are integrated into the development process from the outset. Our teams span a wide spectrum of technical efforts tackling AI safety challenges including, evaluations of models under our Preparedness Framework prior to their deployment, internal and external red-teaming, post-deployment monitoring for abuse, Bug Bounty and Cybersecurity Grant Programs, and contribution to authenticity standards, among others. 

We will work closely with the EU AI Office and other relevant authorities as the new law is implemented in the coming months, and we hope that the expertise we’ve built will help advance the objectives of the Act when it comes to deploying safe and beneficial AI.  

In this post, we provide an overview of some key topics in the AI Act, with a special focus on prohibited and high-risk use cases.

The AI Act principally applies to “AI systems,” which the Act defines as “a machine‑based system designed to operate with varying levels of autonomy, that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.”  This definition is broadly consistent with the OECD’s definition of “AI systems” issued in 2023 and the definition used in the Biden Administration’s Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.  

Importantly, the AI Act differentiates between providers and deployers of AI systems. Providers are entities, like OpenAI, that develop an AI system or a general-purpose AI model. It also includes entities that have an AI system or a general-purpose AI model developed and place it on the market or who put the AI system into service under its own name or trademark, whether for payment or free of charge. 

Deployers are customers or partners who use these systems or models in their own applications, such as integrating GPT‑4o into a specific use case. Although the majority of obligations under the AI Act fall on providers rather than deployers, it’s important to note that a deployer that integrates an AI model into their own AI system can become a provider under the Act, such as by using their own trademark on an AI system or modifying the AI system in ways that weren’t intended by the provider.

Other AI systems that do not pose unacceptable or high-risks face only limited requirements, such as transparency obligations. For example, the Act specifies that individuals should be informed when they are interacting with an AI system like a chatbot, and that artificially manipulated images, audio, or video content need to be clearly labeled. Most AI systems on the market are likely to fall under this category.