EU AI Act Demands Informed, Disclosure-Aware Patent Strategies

The EU has created the world’s first sweeping legal framework for AI by adopting the Artificial Intelligence Act. This ambitious blueprint will ripple far beyond its borders and do more than set rules. It will reshape how companies build, deploy, and protect innovation in the AI age.

While adopted in 2024, guidelines specifying the practical implementations of the AI Act are still being developed, and major provisions of the AI Act won’t come into effect until August 2026. For example, the prohibitions on “unacceptable risk” AI systems only took effect in February 2025.

The requirements for governance, model transparency/notification, began in August 2025. General applicability of most of the AI Act including obligations for “high-risk” AI systems begin in August 2026. Obligations for high-risk AI systems that are part of safety components in regulated products become applicable in August 2027.

By introducing a tiered, risk-based regime, the law bans certain AI practices outright, layers strict obligations on high-risk systems, and establishes unprecedented oversight for general-purpose AI and foundation models, especially those with systemic impact. Its reach is global—any company placing AI into the EU market must comply and its penalties are steep.

For businesses and their counsel, compliance isn’t optional. It’s now the price of entry into one of the world’s largest markets, and it will influence how innovation is documented, safeguarded, and patented.

It’s important to understand the AI Act’s most consequential provisions for patent strategy, particularly how regulatory documentation duties intersect with data provenance, inventorship disputes, trade secret versus patent trade-offs, claim drafting under new compliance constraints, and geo-strategic filing decisions.

The AI Act distinguishes between four key categories of AI systems:

• Minimal-risk systems (AI-enabled video games, spam filters)
• Limited-risk systems (chatbots interacting with users)
• High-risk systems (AI in health care, education, employment, infrastructure, biometric identification)
• General purpose and foundation models

While minimal and limited risk systems carry only modest obligations, the regulation of high-risk and general-purpose/foundation models forms the core of the AI Act and presents the most significant patent implications.

Before entering the market, high-risk systems must clear a conformity assessment and provide detailed technical documentation that includes:

• System description and intended purpose
• System architecture, algorithms, and datasets used
• Risk management, testing, and validation protocols
• Transparency and human oversight measures

The key takeaway is coordination. The AI Act requires companies to disclose technical details such as algorithms, datasets, and testing protocols that may mirror what would appear in a patent filing. If these details are provided to regulators before a patent application is filed, they may be treated as public disclosures that jeopardize novelty and erode valuable rights.

Providers of general purpose AI and foundation models must prepare dataset summaries. These models posing systemic risk are further obligated to include risk evaluation, testing, and analysis. Such requirements force disclosure of training data provenance and model characteristics, with patent implications.

Patent Strategy Implications

The obligations under the AI Act inadvertently may create public disclosures that can be used as prior art. The solution is proactive alignment. Patent and compliance teams must work in tandem to ensure filings are sequenced and consistent.

Patent applications should precede or accompany regulatory submissions, and compliance documentation should be reviewed against the company’s broader IP strategy. Managed correctly, the same materials can satisfy regulatory obligations while preserving, and even strengthening, patent protection.

General purpose AI model providers must provide mandatory data summaries of training data. This creates patent strategy challenges including:

• Freedom-to-operate risks and valuation. Disclosures may reveal reliance on unlicensed or copyrighted data, inviting litigation, weakening patent value and rights, and weakening portfolio valuation.
• Published datasets. These methodologies may themselves become prior art, undermining future filings. Patent filings therefore must precede disclosure.

Although the EU AI Act is a European regulation, its documentation requirements have direct implications for global patent practice. Under US law, only natural persons can be named as inventors, making the ability to separate human contributions from AI assistance critical.

The AI Act’s recordkeeping obligations (such as requiring providers of high-risk systems to maintain detailed technical files, training data records, deployment logs, and oversight measures) create a structured evidentiary trail.

Properly managed, these records can help distinguish human inventive contributions from AI-assisted outputs, providing valuable support for defending inventorship and reinforcing patent validity in a contested landscape.

Documentation and dataset summaries may further reduce the viability of trade secret protection. Both the EU Trade Secrets Directive and US law require that information be kept confidential through reasonable protective measures.

By mandating disclosures, the AI Act can erode this confidentiality, making secrecy harder to sustain in practice. This shift alters the calculus for IP strategy. In some cases, patenting may become the safer path, as certain technologies no longer can be reliably safeguarded as trade secrets.

Patent counsel therefore should consider filing patents on protectable technologies that can’t be maintained under trade secrets.

The AI Act’s core compliance mechanism for high-risk AI systems is a conformity assessment in which providers demonstrate their AI systems meet the AI Act’s requirements. This assessment ties legality of systems to the specific system configuration described in documentation requirements.

This complicates claim drafting. While applicants often harmonize claims across jurisdictions, US claims may not align with certifiable EU products. As a result, narrower claims may be needed in the EU, aligned with EU-certified products, while broader claims can be pursued for US markets.

Strategic Considerations

The AI Act introduces unique risks for US companies’ patent portfolios with exposure to the EU market. Strategically, it’s prudent for companies to incorporate the following actions to ensure compliance with the AI Act’s regulatory obligations to build strong and enforceable patent portfolios:

• Integrate patent counsel into compliance planning
• Prioritize early filing in Europe to preserve rights before disclosure requirements
• Consider mixed protection models: patent where disclosure is mandatory, trade secret where secrecy can be preserved
• Draft dual claim sets to reflect EU-constrained and US-flexible configurations
• Audit existing portfolios for EU exposure. Identify patents or applications that may intersect with AI Act compliance requirements to pre-empt conflicts

The AI Act does more than regulate—it reshapes the infrastructure of innovation protection. In the post-AI Act environment, patent strategy must be regulatory-informed, jurisdictionally sensitive, and disclosure-aware.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law, Bloomberg Tax, and Bloomberg Government, or its owners.

Author Information

Lestin L. Kenton, Jr. is a director at Sterne Kessler specializing in IP portfolio development and monetization.

Roozbeh Gorgin is counsel in Sterne Kessler’s electrical practice group.

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