Global AI Regulation Is Becoming the New Baseline for U.S. Legal Risk

The governance of artificial intelligence is rapidly being defined by international frameworks, creating compliance obligations that precede comprehensive U.S. domestic law. Treaties, global standards, and cross-border frameworks now shape documentation, oversight, and risk expectations for companies operating in multiple jurisdictions. As AI systems mature, international standards are establishing the default floor for U.S. legal compliance, creating obligations that reach firms, clients, and litigators even where domestic law remains unsettled.

A New Global Governance Layer

The most consequential development is the Council of Europe’s Framework Convention on Artificial Intelligence, adopted in May 2024 and opened for signature in Sept. 2024 as the first legally binding multilateral treaty on AI. The Convention requires signatories to implement safeguards that protect human rights, democratic principles, and the rule of law. Its text outlines obligations for transparency, documentation, and oversight that apply to developers and deployers regardless of where they are located. For U.S. companies providing systems in Europe, these requirements affect contracting, technical documentation, and accountability structures even without U.S. ratification.

Alongside the treaty, the European Union’s AI Act introduces one of the world’s most detailed regulatory regimes. The EU’s legislative record, accessible through the European Commission’s policy materials, shows how the Act’s risk tiers determine obligations for logging, record keeping, human oversight, and conformity assessments. These duties apply extraterritorially to providers offering AI systems within the EU. As a result, American developers, corporate counsel, and procurement teams already treat the Act’s requirements as binding business risk.

The Organisation for Economic Co-operation and Development’s AI Principles further define the international landscape. The OECD maintains the world’s most widely adopted AI governance norms, available through its AI Principles library. The complementary OECD Classification Framework builds on the principles by requiring organizations to explain system function, purpose, and context. These guidelines appear frequently in regulatory commentary and risk frameworks, including those adopted in the United States.

The United States presents a contrasting picture. While numerous AI bills have been introduced in Congress, comprehensive federal legislation has not advanced to enactment as of November 2025. Congressional efforts to address AI governance have remained stalled, with proposals ranging from baseline frameworks to attempts at preempting state regulation. In July 2025, the Senate voted 99-1 to reject a 10-year moratorium on state AI laws that had been included in budget reconciliation legislation. The proposal, which would have nullified existing state regulations in California, Colorado, and other jurisdictions, collapsed following bipartisan opposition from state attorneys general, governors, and civil rights organizations.

As of late 2025, renewed preemption efforts were being considered as potential amendments to the National Defense Authorization Act, though prospects remained uncertain. This federal vacuum has created a governance environment where international frameworks and state-level regulations fill the regulatory space. U.S. companies operating globally must align with the highest applicable standards regardless of domestic requirements, making international AI governance frameworks effectively binding through contractual and competitive pressure.

Other international initiatives add layers to the emerging architecture. The G7 Hiroshima AI Process, established in Oct. 2023, produced International Guiding Principles and a Code of Conduct for organizations developing advanced AI systems. These principles emphasize transparency reporting supported by robust documentation processes, including evaluation reports, information on security and safety risks, and technical documentation throughout the AI lifecycle. UNESCO’s Recommendation on the Ethics of AI outlines global principles for responsible development. ISO/IEC 42001:2023 introduces a management system standard for AI governance, described in detail on the ISO website. These frameworks differ in scope, but they reinforce a shared vision: AI systems require identifiable controls, traceability, and supervision.

How Global AI Rules Reach U.S. Law Firms

The reach of these frameworks does not depend on American legislation. Instead, their influence emerges through cross-border commerce. Multinational clients require vendors to meet the highest applicable standard in their compliance environment. In practice, this often means adopting documentation requirements shaped by the EU AI Act, procedural controls influenced by the Council of Europe Convention, and risk assessments aligned with OECD language.

Contract templates illustrate this change. Enterprise customers ask vendors for technical files and audit records that mirror European requirements. Procurement teams require version histories, model descriptions, and testing reports that satisfy expectations abroad. Law firms reviewing these contracts increasingly evaluate AI systems using the criteria found in international instruments.

International rules also shape litigation. Plaintiffs cite foreign standards to argue that a defendant failed to take reasonable precautions. If a company’s foreign operations require detailed logging or documentation, American courts may treat those safeguards as evidence of an industry norm. Scholars and practitioners warn that international standards can influence arguments about foreseeability, negligence, or product defect when similar principles appear in U.S. frameworks like the NIST AI Risk Management Framework.

Executive Order 14110 accelerates this interaction. Federal agencies implementing the order frequently reference documentation and transparency practices similar to those described in OECD principles and European law. As agencies issue guidance, their expectations align with international frameworks, reinforcing a unified governance layer for system oversight.

Documentation Requirements Converge Globally

The most significant convergence involves documentation. The EU AI Act requires providers of high-risk systems to preserve logs that show how models were trained, tested, and supervised. The Act’s records must include dataset summaries, human oversight points, and post-deployment monitoring. The OECD classification framework similarly emphasizes contextual explanations and operational transparency. The G7 Hiroshima AI Process builds on these expectations by requiring transparency reports that enable users to interpret system outputs, supported by documentation of datasets, processes, and decisions made during development.

ISO/IEC 42001 extends these expectations by treating documentation as a core component of organizational governance. The standard requires organizations to maintain continuous system inventories, risk assessments, and review cycles. These structures echo requirements found in European law and recommended by the OECD, creating a shared foundation for AI management.

In the United States, the National Institute of Standards and Technology aligns with these expectations through its AI Risk Management Framework. The Framework emphasizes traceability and documentation of inputs, outputs, evaluations, and human interventions. These provisions map cleanly onto European and international requirements, enabling organizations to maintain a single documentation structure for global use.

In practice, organizations use documentation to demonstrate accountability. When clients or regulators request information about AI workflows, technical files and logs provide objective evidence of model behavior, review, and deployment. This focus on data provenance reflects a broader recognition that trust in AI systems depends on the ability to reconstruct how they functioned at each stage of use.

Privacy Frameworks Intersect with AI Governance

Privacy rules add complexity to international AI governance. The European Data Protection Board published Opinion 28/2024 in Dec. 2024, providing detailed guidance on applying GDPR to AI model development and deployment. The opinion addresses when AI models can be considered anonymous, how legitimate interest applies as a legal basis for processing personal data, and the consequences of unlawful data processing during model training. The EDPB emphasizes that claims of anonymity require robust documentation, including Data Protection Impact Assessments, technical safeguards, and contextual risk assessments.

Cross-border data transfers require encryption, minimization, and contractual protections. The European Union Agency for Fundamental Rights has documented fundamental rights challenges arising from AI use, warning that documentation must not expose personal data without safeguards. These constraints require careful design of record-keeping systems to maintain integrity while protecting privacy.

Managing Cross-Border AI Compliance

Multinational clients face overlapping obligations. Companies that operate in Europe must classify systems according to the EU Act’s risk tiers. Those working in Council of Europe states must meet human rights safeguards outlined in the Convention. Organizations in OECD member states adopt classification frameworks that require contextual analysis. ISO standards add further expectations for governance structure.

U.S. legal departments respond by building cross-border compliance maps. They maintain system inventories, perform risk assessments, and review vendor practices using criteria from multiple jurisdictions. Law firms advising these clients evaluate technical documentation with reference to foreign rules, ensuring that records meet the expectations of both domestic and international regulators.

These adjustments reflect professional responsibility requirements. Model Rule 1.1 obligates lawyers to maintain competence with the technology they use, including an understanding of client exposure influenced by international rules. Model Rule 5.3 requires supervision of technology providers, which in practice includes ensuring that tools used in legal work comply with global documentation and oversight norms.

U.S. State-Level Developments Create Additional Complexity

State legislatures are developing AI regulations that intersect with international frameworks. California’s SB 53, the Transparency in Frontier Artificial Intelligence Act, signed into law in September 2025 and effective January 2026, regulates frontier AI developers by requiring transparency disclosures, whistleblower protections, and reporting of critical safety incidents involving catastrophic risks. Colorado’s AI Act, delayed until June 2026, regulates high-risk AI systems in employment, housing, credit, education, and healthcare. Illinois amended its Human Rights Act in Aug. 2024 to prohibit employers from using AI in employment decisions, effective Jan. 2026.

These state laws often mirror elements of international frameworks. California’s retention requirements align with documentation expectations in the EU AI Act. Colorado’s high-risk classification system reflects OECD and EU approaches. As state regulations proliferate, organizations find that compliance with international standards provides a foundation for meeting diverse state requirements.

AI Supply Chain Risk Becomes Central Compliance Challenge

Supply chain governance has emerged as a critical dimension of AI compliance in 2025. Article 10 of the EU AI Act imposes obligations on deployers to verify that high-risk AI systems from third-party providers meet regulatory requirements. The NIST AI Risk Management Framework similarly treats supply chain considerations as integral to governance, requiring organizations to document and manage risks from third-party software, hardware, and data throughout the AI lifecycle.

For legal practice, this translates into heightened due diligence requirements. Law firms evaluating AI tools for e-discovery, research, or document review must obtain technical documentation from vendors demonstrating compliance with international standards. Procurement contracts increasingly require vendors to maintain logs, audit trails, and technical files consistent with EU AI Act requirements, even for tools deployed exclusively in the United States. Corporate clients face similar obligations when assessing AI systems used by contractors, consultants, or business process outsourcers. The supply chain compliance cascade means that downstream liability can attach when vendors fail to meet documentation or oversight standards, creating exposure for organizations that cannot demonstrate appropriate vendor assessment processes. This dynamic places particular pressure on legal departments to build internal competencies for evaluating AI vendor claims and ensuring that contractual provisions allocate supply chain risk appropriately.

Implications for Litigation and Evidence

International governance affects litigation in two ways. First, technical documentation created for foreign compliance appears in American discovery. Logs, evaluation reports, and dataset summaries generated for EU or ISO requirements often become core evidence in disputes involving model reliability, algorithmic bias, or system failure. These materials answer questions that U.S. law does not always require developers to document.

Second, international standards shape arguments about reasonableness. If a global framework defines certain safeguards as expected practice, litigants may argue that failure to adopt them represents negligence. Courts evaluating expert testimony sometimes consider international guidance, especially when it aligns with NIST frameworks or executive branch policy statements.

Policy research from institutions such as Stanford University’s Human-Centered AI initiative and the Carnegie Endowment for International Peace documents how global rules influence operational controls. Studies published through Stanford’s policy library describe how documentation and oversight become integral to system reliability. The Carnegie Endowment’s Technology and International Affairs program analyzes AI governance in the context of international security and geopolitical competition. These analyses contribute to the interpretive environment in which courts assess AI evidence.

Corporate Governance and Professional Risk

Corporate governance reflects the global shift most clearly. Boards adopt risk frameworks aligned with ISO/IEC 42001 to demonstrate oversight of high-impact AI systems. Internal controls rely on documentation, review cycles, and model inventories similar to those used in Europe. For organizations operating internationally, harmonizing these structures reduces exposure to regulatory and contractual risk.

Professional liability insurers factor these developments into their underwriting. Insurers evaluate whether organizations maintain logs, track model versions, and supervise automated tools according to globally recognized frameworks. Organizations that follow international documentation practices often have an easier path to demonstrating diligence during coverage evaluations.

Toward Interoperability

The convergence between international and domestic frameworks creates a path toward interoperability. Because global standards emphasize traceability, transparency, and oversight, organizations can design systems that satisfy multiple regimes with a single set of controls. This alignment benefits multinational clients that seek a unified approach to compliance across markets.

Legal practice increasingly follows this model. Firms advise clients to build governance processes that meet or exceed international expectations. Vendor assessments incorporate technical file requirements that resemble European standards. Lawyers evaluating AI tools for internal use consider whether systems offer documentation sufficient for cross-border audits. As these practices mature, global AI governance becomes the de facto baseline for American legal risk.

Practical Integration for Legal Teams

Implementation begins with inventory. Legal teams identify where AI is used across research, drafting, discovery, and compliance. Each use case requires documentation showing the model version, inputs, outputs, and human review. These steps align with traceability goals described in both NIST and European frameworks.

Vendor review follows. Firms evaluate whether external providers maintain logs, audit trails, and technical files. Corporate clients increasingly require contractual assurances that vendors can produce documentation consistent with global standards. Law firms integrate these requirements into their procurement workflows to avoid downstream exposure.

Continuous oversight completes the process. Legal teams monitor updates from international bodies, including changes in the EU Act’s enforcement priorities, revisions to OECD guidance, and new ISO controls. This ongoing tracking ensures that organizations maintain alignment with evolving global expectations.

Limits and Friction Points

International governance does not resolve every issue. The EU AI Act’s documentation requirements can impose significant burdens on smaller organizations. The Council of Europe Convention’s human rights safeguards require interpretation to translate into operational controls. ISO management cycles demand staffing and investment.

Privacy rules add complexity. The EDPB has warned that documentation must balance accountability with data protection, requiring organizations to implement technical safeguards that prevent the extraction of personal data from AI models. Cross-border data transfers require encryption, minimization, and contractual protections. These constraints require careful design of record-keeping systems to maintain integrity while protecting privacy.

What’s Next for Legal Practice

International frameworks will continue to influence U.S. legal practice as global rules mature and enforcement expands. Documentation requirements will increase as regulators implement the EU AI Act and as Council of Europe member states operationalize the Convention. Corporate governance models will converge on ISO-style systems. Legal practitioners will rely on international standards to evaluate risk, prepare evidence, and advise clients.

For American lawyers, the shift is less about adopting foreign law than about aligning with a global consensus on transparency, traceability, and oversight. The frameworks emerging today form a common language for trust. In a profession built on proof, that language is becoming essential.

Sources

• California Legislative Information: SB-53 Artificial intelligence models: large developers (Sept. 29, 2025)
• Carnegie Endowment for International Peace: Artificial Intelligence (2025)
• Colorado General Assembly: SB24-205 Consumer Protections for Artificial Intelligence (2024)
• Council of Europe: Framework Convention on Artificial Intelligence (2024)
• European Commission: European Approach to Artificial Intelligence (2025)
• European Data Protection Board: Opinion 28/2024 on AI Models and Personal Data (Dec. 17, 2024)
• European Union Agency for Fundamental Rights: Artificial Intelligence and Big Data (2025)
• G7 Leaders’ Statement on the Hiroshima AI Process (Oct. 30, 2023)
• Greenberg Traurig: Colorado Delays Comprehensive AI Law With Further Changes Anticipated (Sept. 2025)
• International Association of Privacy Professionals: Global AI Legislation Tracker (2025)
• ISO/IEC 42001:2023 Artificial Intelligence Management System Standard (2023)
• Jones Day: Illinois Becomes Second State to Pass Broad Legislation on the Use of AI in Employment Decisions (Oct. 29, 2024)
• Law Commission of England and Wales: Digital Assets Project (2024)
• National Institute of Standards and Technology: AI Risk Management Framework 1.0 (Jan. 2023)
• Organisation for Economic Co-operation and Development: Framework for the Classification of AI Systems (2022)
• Organisation for Economic Co-operation and Development: AI Principles (2019, updated 2024)
• Stanford University Human-Centered Artificial Intelligence: Policy Library (2025)
• UNESCO: Recommendation on the Ethics of Artificial Intelligence (2021)
• White & Case: AI Watch Global Regulatory Tracker (2025)
• White House: Executive Order 14110 on Safe, Secure, and Trustworthy AI (Oct. 30, 2023)

This article was prepared for educational and informational purposes only. It does not constitute legal advice and should not be relied upon as such. All regulations and sources cited are publicly available through official publications and reputable outlets. Readers should consult professional counsel for specific legal or compliance questions related to AI use.

See also: From Transparency to Proof: How Global Standards Are Redefining Legal AI Accountability