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Overview: The EU General-Purpose AI Code of Practice

Why Do We Need a Code of Practice?

On August 2, 2025, the general-purpose AI (GPAI) provisions of the EU AI Act went into effect. GPAI models (including models that support most generative AI, like ChatGPT), now face certain obligations in the EU, including requirements around transparency, copyright and systemic risk. However, the EU AI Act is a framework: it defines obligations but leaves technical details to harmonized standards and codes of practice. While this approach sets certain expectations and allows the EU AI Act to remain technology-neutral, it also leaves questions about how businesses substantially comply with the EU AI Act. To bridge this gap, a multi-stakeholder group drafted the General-Purpose AI Code of Practice (GPAI Code). On August 1, 2025, the European Commission issued a formal opinion confirming the GPAI Code is an “adequate tool” to help demonstrate compliance with the EU AI Act. Why is the Code significant? This opinion signals that organizations who adopt the GPAI Code may be able to demonstrate good-faith efforts to comply with the relevant provisions of the EU AI Act –  according to the Commission’s website: “The Code of Practice helps industry comply with the AI Act legal obligations…of general-purpose AI models.” In its opinion, the Commission notes that the Code provides actionable commitments and reporting mechanisms, especially for high-risk models. Additionally, the Commission emphasized that the Code provides a practical framework to demonstrate regulatory compliance. Following this endorsement, providers of GPAI models can voluntarily sign the Code, which “will reduce their administrative burden and give them more legal certainty than if they proved compliance through other methods.” Still, signatories should be aware that the Code explicitly states that adherence to the Code does not necessarily constitute evidence of compliance with the EU AI Act.

What is a General-Purpose AI Model?

A GPAI model is a component of an AI system with a wide range of possible uses, whether intentional or unintentional. It is important to note that these models are not systems in themselves but are part of AI systems. Additional elements, like user interfaces, are necessary to make these models fully operational systems. Under Article 3(63) of the EU AI Act, a GPAI model includes those trained on a “large amount of data using self-supervision at scale.”  They can be applied across sectors or tasks, usually without substantial modification, meaning GPAI models “can be integrated into a variety of downstream systems or applications.” Recital 98 of the EU AI Act states that the generality of the model can also be determined by the number of parameters, and “models with at least a billion parameters…should be considered to display significant generality and to competently perform a wide range of distinctive tasks.” GPAI models are sometimes called “foundation” or “frontier” models, and while they may include large language models (LLMs), they can also process audio, physical, textual or visual data, powering systems like DALL-E, GPT-4, Gemini, LaMDA, SEER, ALIGN, and more.

How are general-purpose AI models regulated?

Under the EU AI Act, the chapter on GPAI both addresses generative AI and outlines some of the most stringent requirements under the Act. However, all requirements for GPAI under the EU AI Act are directed to providers as opposed to deployers. Providers of GPAI models have a range of obligations under the EU AI act, both directly to supervising authorities and onward to AI providers who integrate the GPAI models into their systems. Obligations of Providers of GPAI Models If a provider places a GPAI model on the EU market, or integrates such a model into its own AI system on the EU market, it must:
  • Prepare and maintain technical documentation for regulators. This should include at least a general description of the GPAI model, including the tasks it’s designed to perform and the types of systems in which it can be integrated; acceptable use policies; and information on training process.
  • Prepare and maintain documentation for downstream providers. This should include information that allows the downstream AI system providers to comply with their own obligations under Article 53(1)(b). Similar to the technical documentation, this includes but is not limited to a general description of the model, and a description of its elements and development process.
  • Prepare an EU copyright policy. This policy should establish a means to comply with EU regulations on copyright and related rights.
  • Prepare and publish a summary of training content. Using the template provided by the AI Office, providers of GPAI must share a comprehensive summary of AI training information. This should allow stakeholders to exercise their rights by informing them of the information used to train the GPAI model.
  • Cooperate with relevant authorities and appoint an authorized representative. Providers must also cooperate with relevant authorities, and if they are established outside the EU, appoint an authorized representative located in the EU.
It is notable that under Recital 85, the EU AI Act states that GPAI systems “may be used as high-risk systems by themselves or be components of other high-risk systems.” Therefore, the providers of GPAI systems must work closely with providers of high-risk AI systems to ensure compliance with any requirements of high-risk systems under the Act. Obligations of Providers of GPAI Models with Systemic Risk What does “systemic risk” mean? GPAI models with systemic risk include models that reasonably pose foreseeable negative effects relating to major accidents, disruption of critical sectors, serious consequences to public health and safety, public and economic security, democratic processes, and the dissemination of false or discriminatory content, or other similar effect. Under Article 51(1) of the EU AI Act, a GPAI model will be classified as having systemic risk if:
  • It has high impact capabilities, or
  • It is designated by the Commission to have high impact capabilities based on the criteria in Annex XIII (i.e., the number of parameters in the model, the size of the data set, the amount of computation used to train the model, etc.).
What are the additional obligations for these models? In addition to the requirements for all GPAI models, those with systemic risk have additional obligations related to:
  • Model evaluation, assessment, and mitigation of systemic risks;
  • Incident management and reporting; and
  • Cybersecurity protections and technical documentation.
Because there are differences in the obligations between GPAI systems generally and GPAI systems with systemic risk, this classification procedure should be noted by providers of GPAI systems; it is essential to understand where each GPAI model falls, and what requirements the model has under the EU AI Act. According to Article 52(6), a list of GPAI models with systemic risk will be published and updated by the European Commission, but it has not been published at the time of writing.

What is the General-Purpose AI Code of Practice?

While not legally binding, providers of GPAI models can use the Code of Practice to demonstrate compliance with their obligations under the EU AI Act. The Code consists of three chapters on 1) transparency, 2) copyright, and 3) safety and security. The first two chapters apply to all providers of general-purpose AI models, providing a way to demonstrate compliance with obligations under Article 53 of the AI Act. The final chapter applies only to general-purpose AI models with systemic risk under Article 55 of the AI Act. Chapter 1: Transparency Among other things, this chapter requires signatories to create and maintain documentation for all GPAI models distributed within the EU for up to ten years. There are exceptions for models that are free, open-source, and do not pose systemic risk. When completing this documentation, signatories must use a standard Model Documentation Form, which includes information on licensing, technical specifications, training data, and other parameters of the GPAI model. The Code encourages publication of this information to promote transparency. Chapter 2: Copyright This chapter requires signatories to create and maintain a copyright policy that complies with the EU’s legal standards. This includes, but is not limited to, ensuring that data collected by web crawling is lawfully accessible, and certain websites flagged for copyright infringement are avoided. Importantly, signatories must designate a contact for copyright holders to submit complaints, along with a process for handling those complaints. Chapter 3: Safety & Security (GPAI with systemic risk only) One of the main elements of this chapter is the requirement for signatories to develop a state-of-the-art Safety and Security Framework before releasing any GPAI model categorized as posing a systemic risk. Additionally, systemic risks should be identified and inventoried, and before progressing with development or deployment, the signatories should weigh the relative risks and determine if they are acceptable, among other requirements.

What’s next?

The Code will be monitored and reviewed at regular intervals by the AI Office, and may be updated in response to emerging risks, technological developments, or incidents involving general-purpose AI models.
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AI Updates: An Overview of the Legal Landscape

As AI continues to advance, so do regulatory efforts. During the 2024 legislative session, 45 states along with Puerto Rico, the Virgin Islands, and Washington D.C. all introduced AI bills. With the legislative session for 2025 wrapping up, we are seeing similar tends this year. As new legal requirements emerge, organizations across the U.S. and EU may face overlapping – yet not identical – regulations that touch on issues of bias, safety, privacy, and transparency. Additionally, these laws may categorize the same AI system differently in different jurisdictions, requiring a nuanced approach to navigating these laws. Keeping this in mind, this article provides a brief overview of a handful of these laws. The practical takeaway? Businesses operating in the U.S. or EU should be aware of their legal requirements. Additionally, these organizations may want to consider a programmatic, auditable, and documented approach to AI governance, which may allow the business to map their AI controls to multiple legal frameworks.

Converging Themes

While details of AI laws differ across jurisdictions, trends seem to be converging on risk-based classification, transparency requirements, and enforcement efforts. Regulators are moving toward risk-based classification. This means AI uses are categorized according to their use case (and the risk associated with that use case). As seen in the EU AI Act, the Colorado AI Act, and TRAIGA, systems may be prohibited or classified by risk. High-risk systems tend to have stricter governance, testing and documentation requirements. Another shared theme is transparency. Laws including the EU AI Act, Colorado AI Act, Utah AI Policy Act, may require covered entities to tell people when AI is in use, while other laws may require the developer or deployer to explain the logic behind certain outputs, and provide consumers with a methods of contesting certain decisions, or opt out of certain types of decisionmaking entirely. The California AI Transparency Act and the EU AI Act may also require labeling of certain AI-generated content. Finally, enforcement is sharpening. The EU AI Act comes with regulatory teeth, with fines of the higher of €35,000,000 or 7% global annual turnover for violation of prohibited practices. In the U.S., state attorneys general and regulators have been active in monitoring AI missteps, including consumer protection and privacy violations. For example, attorneys general in Massachusetts and Oregon have issued advisories on how consumer protection laws apply to AI, while Texas Attorney General Ken Paxton reached the first-of-its-kind settlement in a healthcare generative AI investigation.

The European Union Artificial Intelligence Act (EU AI Act)  

Overview: The EU AI Act is the world’s first comprehensive AI regulation and sets a high-water mark for governance expectations. The Act is technology neutral and uses risk-based classification to sort AI systems into risk-tiers, each with escalating obligations. Key Provisions:
  • Prohibited systems include cognitive behavioral manipulation, most real-time biometric identification, and systems used for social scoring. These systems are considered to pose an unacceptable risk to safety or fundamental rights.
  • High-risk systems include hiring tools, biometric identification, and critical safety technology. They must undergo conformity assessments, maintain technical documentation, and ensure human oversight.
  • Limited-risk systemsinclude chatbots, deepfake generators, and public facing generative AI. These systems have transparency obligations to ensure users understand they are interacting with AI.
  • Minimal-risk systems include AI-enabled spam filers, grammar checkers, and basic AI in video games. These systems have no specific obligations under the Act, but best practices are encouraged.
Key Dates & Enforcement:
  • February 2, 2025: Prohibitions on certain AI systems and requirements on AI literacy start to apply.
  • August 2, 2025: Rules on general practice AI models, governance, confidentiality, and penalties start to apply.
  • August 2, 2026: The remainder of the AI Act (except for Article 6(1)) applies.
The Act will be enforced by European AI Office and national market surveillance authorities. Non-compliance with the prohibition of AI practices is subject to an administrative fine of up to €35,000,000 or up to 7% worldwide annual turnover, whichever is higher. Non-compliance with other provisions shall be subject to administrative fines of up to €15,000,000 of up to 3% of its total worldwide annual turnover, whichever is higher.

Colorado: Consumer Protections for Artificial Intelligence Act (CO AI Act)

Overview: Enacted in May 2024, the CO AI Act was the first far-reaching AI law in the United States. This Act primarily focuses on high-risk AI systems, including but not limited to those which influence “consequential decisions” – those impacting areas such as employment, education, housing, healthcare, finance, insurance, legal services, and essential government services. Key Provisions: Developer and deployers must both exercise “reasonable care” to protect consumers from known or reasonably foreseeable risks of algorithmic discrimination. For both, this may include providing notice to the Colorado Attorney General within 90 days of becoming aware of new discrimination risks.
  • Developers. There is a rebuttable presumption that the developer used reasonable care if they disclose, among other things:
    • reasonably foreseeable uses and known inappropriate or harmful uses of the AI system (including of algorithmic discrimination) and the measures taken to mitigate them;
    • the intended purpose, benefits, uses and outputs of the AI system; and
    • high-level summaries of the data types used to train the AI system, including data governance measures.
  • Deployers must also exercise reasonable care to protect consumers from any known or reasonably foreseeable risks of algorithmic discrimination. Similarly, there is a rebuttable presumption that the deployer used reasonable care if they complete the following, among other things:
    • a risk-management program that considers the NIST AI Risk Management Framework (AI RMF) or another similarly recognized risk management framework with substantially similar requirements (for more information about conducting an AI Risk Assessment, you can check out our post here);
    • an impact assessment, that includes the purpose, use cases, deployment context, and an analysis of whether it poses any foreseeable risks of discrimination, along with steps taken to mitigate those risks;
    • notice to consumers when certain systems are being used that include the system purpose, contact information, and options to opt-out of AI processing for that purpose, correct personal information used in the decisionmaking process, and appeal the decisionmaking process.
  • Disclosure should be clear. Regardless of risk level, any AI system that is directly interacting with Colorado consumers must disclose that it is an AI system, unless that would be obvious to a reasonable person.
Key Dates & Enforcement: While this law was originally set to take effect in 2026, Colorado Governor Polis called a special legislative session to address budget issues, taking place on August 21. The impact of SB24-05 (Consumer Protections for AI) is on the agenda, which may result in a delayed enforcement deadline and substantive changes to the law’s provisions. Violations are treated as deceptive trade practices under Colorado’s Consumer Protection Act, subject to enforcement by the Colorado Attorney General and penalties of up to $20,000 per violation.

Texas Responsible AI Governance Act (TRAIGA)

Overview: While TRAIGA originally provided a comprehensive AI framework, the final version has been significantly pared down. With narrow substantive provisions, TRAIGA focuses on harms caused by AI, and the Act regulates – or completely bans – certain uses of these systems. TRAIGA applies broadly to private sector companies if they provide AI-generated content or services to Texas residents, even if they are located outside the state of Texas. Additionally, government agencies interacting with the public fall squarely within the scope of the Act. You can read more about TRAIGA at our blog post covering the Act here. Key Provisions:
  • Prohibited AI For Public and Private Sectors include but are not limited to intentionally inciting self-harm, violence or crime; infringing on an individual’s rights; or unlawfully discriminating (with purposeful intent). The Act also prohibits deploying AI systems that intentionally generate illegal content, as well as child sexual abuse material or sexually explicit chat systems that impersonate children.
  • Prohibited AI uses for the Public Sector include but are not limited to social scoring and uniquely identifying individuals with biometric data (with limited exceptions).
  • Transparency Requirements for Public Sector may require governmental agencies to, among other things, provide conspicuous notice to consumers that they are acting with an AI system.
Key Dates & Enforcement:   TRAIGA was signed into law in June 2025 and takes effect on January 1, 2026. With no private right of action, the Act can only be enforced by the Texas Attorney General. The Act requires the Attorney General to create an “online mechanism” on their website where consumers can submit complaints of potential violations. If the Attorney General determines a violation has occurred, there is a 60-day cure period. If the violation continues after this period, the Attorney General may bring a claim for, among other things:
  • an injunction;
  • a civil penalty for curable breaches between $10,000 and $12,000;
  • a civil penalty for uncurable breaches between $80,000 and $200,000; and
  • a civil penalty for each day of continued violation between $2,000 and $40,000.
 

California CCPA Draft Regulations

Overview: On July 24, 2025, the California Privacy Protection Agency (CCPA) board voted 5-0 to finalize Draft Regulations to the California Consumer Privacy Act (CCPA). The CPPA sent the rulemaking package to the Office of Administrative Law, which has 30 days to approve the regulations. For a deeper dive on the CCPA Draft Regulations, please see our post here. Key Provisions:
  • Automated-decisionmaking (ADMT): Businesses must inform consumers with a pre-use notice and provide opt-out rights when AI or automated tools influence “significant decisions,” including those about employment, education, housing, healthcare, financial or lending services, and similar areas.
  • Risk Assessments: Organizations engaging in high-risk data processing (such as the decisions covered in ADMT, above) must conduct risk assessments before beginning processing, and must update them regularly, including within 45 days of any material change of the system. For more information about conducting an AI Risk Assessment, you can check out our post here.
  • Cybersecurity Audits: Businesses meeting certain thresholds must undergo annual, evidence-based audits carried out by a “qualified, objective, independent professional.” The audits must rely on specific evidence (as opposed to assertions by the business management), and all information related to the audit should be kept for a minimum of five years after completion.
Key Dates & Enforcement: Compliance with these Draft Regulations will be required once they are approved by the Office of Administrative Law. The deadlines include:
  • ADMT Regulations: January 1, 2027
  • Privacy Risk Assessments: December 31, 2027
  • Cybersecurity Audits:
    • For businesses with $100+ million in annual gross revenue: April 1, 2028.
    • For businesses between $50 million and $100 million in annual gross revenue: April 1, 2029.
    • For businesses with less than $50 million in annual gross revenue: April 1, 2030.

Other Laws to Consider

Along with the more far-reaching laws provided above, there are additional laws that businesses may want to consider when building, implementing, or otherwise engaging with AI tools or systems.
  • Utah’s Artificial Intelligence Policy Act
    • Effective as of May 2024, this Act mandates certain disclosures when businesses use generative AI to interact with consumers. This applies specifically to “regulated professions,” where the provider shall make the disclosure prominently, regardless of whether it is obvious the person is interacting with an AI system or not.
  • New York City’s Local Law 144 (and other AI employment regulations)
    • Signed in 2021, this law applies to employers and employment agencies in New York City that use “automated employment decision tools” to screen candidates or employees. It requires that an independent bias audit be conducted within one year of using the AI tools. For more information on AI in employment, see our article on AI In the Workplace: Legal Considerations for Leadership Teams.
  • California’s AI Transparency Law (SB 942)
    • Effective January 1, 2026, this law applies to “covered providers” – those offering generative AI systems with over 1 million monthly users in California. These providers must provide: 1) a free, public AI detection tool; and 2) certain disclosures as a label or embedded within their content.
  • California’s Data Transparency Law (AB 2013)
    • Effective January 1, 2026, developers of generative AI systems must post a disclosure on their website including documentation used to train the AI system. This documentation includes high-level summary of datasets used in the development of the AI system – the sources or owners of the datasets, how they further the purpose of the AI system, the number of datapoints in the datasets, and more.

Key Takeaway

As lawmakers race to keep up with the breakneck speed of AI implementation, guidance is quickly becoming enforcement. While specific requirements between these laws vary, the common thread is clear: covered entities are expected to understand, document, and justify their AI systems’ design, data, and impact. Additionally, organizations utilizing AI should consider building responsible AI governance into their operations. By incorporating these governance processes into everyday systems and – similar to those for privacy and cybersecurity – organizations may proactively protect against legal, ethical and operational risk when implementing AI.
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Upcoming Webinar: The EU AI Act: How Will It Affect Your Business?

On Thursday, December 12, 2024 at 11am ET, DataCamp will host a live webinar titled “The EU AI Act: How Will It Affect Your Business?” The speakers are Dan Nechita, Lead Technical Negotiator for the EU AI Act on behalf of the European Parliament, and Lily Li, Data Privacy, Cybersecurity & AI Lawyer and Founder of Metaverse Law. They will cover AI governance and risk management requirements under the EU AI Act and new US AI law. Attendees will:
  • Learn about the scope and requirements of the EU AI Act and other AI legislation.
  • Understand the risk classification system and the requirements for AI literacy.
  • Learn how to comply with regulations and the consequences of non-compliance.
  Join us for this informational webinar by registering at the DataCamp website using this hyperlink.