A recent U.S. ruling on AI and copyright redefines fair use, with major implications for cross-border tech and USMCA compliance.
The recent U.S. court ruling in favor of Anthropic in a closely watched AI copyright lawsuit delivered more than a procedural win—it marked a potential recalibration of the fair use doctrine with wide-reaching implications for cross-border businesses under the USMCA. The decision came just days after a similar courtroom victory for Meta, which also prevailed against authors who alleged that the company had misused their works to train its language models (Kadrey v. Meta Platforms Inc.).
For North American executives in technology, media, and data-intensive industries—especially those navigating operations along the U.S.–Mexico border—the ruling introduces both momentum and ambiguity over how AI models may lawfully train on proprietary data across jurisdictions.
How Courts Are Interpreting Transformative Use in AI Training
At the heart of the dispute is the concept of “transformative use”. In defending itself against claims that it used pirated books to train its Claude language model, Anthropic argued that its use of the material served a fundamentally different purpose: not to replicate or display the works, but to construct a system that maps statistical relationships across language. In effect, the content functioned as a “back-end step” in building a generative tool—much like Google’s creation of a searchable book database, which the Second Circuit deemed fair use in 2015.
That argument proved compelling to a California federal judge, who dismissed several claims. Anthropic is now seeking summary judgment to resolve the case entirely. The ruling sketches a subtle but significant boundary: when copyrighted material is used to train transformative systems—without directly exposing that material to end users—fair use may well apply, even when the content was copied wholesale.
Meta’s Parallel Win — But With a Caveat
In a separate but related case, Meta also secured dismissal—though Judge Vince Chhabria emphasized that the ruling turned on the plaintiffs’ failure to build a compelling legal record, not on any affirmation of Meta’s training practices. By contrast, the judge in the Anthropic case engaged more substantively with the fair use doctrine.
The reverberations of these two cases will not end at the U.S. border.
Cross-Border Legal Exposure Under USMCA
For cross-border operators within the USMCA, the ruling complicates an already unsettled legal terrain. The Agreement’s intellectual property chapter (Chapter 20) obligates all three countries to uphold copyright protections that evolve alongside technology. Yet national interpretations of “fair use”—or its equivalents—differ sharply. Mexico’s more restrictive uso justo doctrine does not function as a general defense under the Ley Federal del Derecho de Autor, but instead allows only narrow exceptions for specific uses such as education or research. Canada’s fair dealing regime, while more expansive than Mexico’s, still diverges from U.S. jurisprudence on transformative use.
This legal divergence poses serious operational challenges for North American AI developers and platform owners. A data set deemed lawful in San Francisco may become a liability in Monterrey or Toronto. AI models trained in the U.S. but deployed commercially in Mexico could trigger IP claims under Mexican law—especially if the training data includes copyrighted material obtained without license. From an investor’s perspective, such exposure may be neither insurable nor indemnifiable.
Sectors Most Vulnerable to Cross-Border AI IP Risk
- Software & Cloud Services: U.S.-based LLMs integrated into enterprise applications in Mexico or Canada may face legal scrutiny over the provenance of their training data—even when the software is cloud-hosted and not locally installed.
- Publishing & Media: Cross-border content creators and distributors must now assess whether U.S.-based AI tools used in content generation comply with more stringent foreign copyright laws.
- Mexican publishers licensing books or scripts to U.S. partners may need to contractually limit their use in AI training pipelines. The Authors Guild has called for clear contract terms to prevent unauthorized model training.
- Advanced Manufacturing & R&D: AI tools like Claude are increasingly used to accelerate product development across sectors such as automotive and biotech. Intellectual property generated with such tools—particularly when transferred across USMCA borders—may invite legal challenges tied to the model’s training origins.
Stakeholders and Policy Movers to Watch
- U.S. AI firms like Anthropic, Meta, and OpenAI, which lead deployment but face increasing legal scrutiny abroad.
- Mexican regulators such as INDAUTOR and INEGI, who may seek stricter oversight of AI systems trained on copyrighted content.
- Canadian lawmakers, already advancing national AI legislation, which could further diverge from U.S. interpretations of fair use.
- Multinational corporations with distributed operations, who must now revise compliance protocols and AI contract clauses to manage jurisdictional risk.
Emerging Compliance Challenges for Generative AI
- No harmonized fair use standard under USMCA
- Jurisdictional inconsistencies in enforcing digital piracy laws
- Fragmentation of case law across U.S. federal districts
Opportunities in Rights-Based Licensing and Transparency
Yet opportunities remain. Companies that implement rigorous, transparent data sourcing protocols will gain first-mover credibility in international AI markets. Cross-border licensing models designed specifically for machine learning could open new revenue streams for rights holders. And the Anthropic decision offers legal breathing room for AI startups seeking to challenge incumbent platforms without incurring prohibitive licensing costs—at least within the United States, for now.
Looking Ahead: USMCA Review and Strategic Positioning
For North American executives managing cross-border legal exposure, the ruling is a double-edged sword. It affirms the United States as a relatively permissive environment for AI innovation, while highlighting the urgent need for deeper treaty alignment, robust compliance frameworks, and contractual vigilance. With the USMCA scheduled for joint review in 2026, stakeholders should prepare now for a high-stakes debate on digital trade and IP sovereignty.
Frequently Asked Questions (FAQs)
1. What does the Anthropic copyright ruling mean for AI developers?
It affirms that training an AI model using copyrighted material may qualify as fair use if the use is transformative and doesn’t expose the material to end users.
2. How does fair use differ between the U.S., Mexico, and Canada?
The U.S. has a broad fair use doctrine, while Mexico follows a more restrictive uso justo standard, and Canada employs fair dealing, which includes specific, narrow exceptions.
3. Are AI models trained on pirated content legal under U.S. law?
Not necessarily. While transformative use may offer protection, sourcing from illegal sites—as alleged in the Anthropic case—could still violate copyright law.
4. Will these rulings impact the upcoming USMCA review in 2026?
Very likely. IP stakeholders may push for more explicit digital and AI-related provisions to harmonize standards across borders.
5. What should multinational companies do to reduce legal risk?
Review AI procurement contracts, strengthen data sourcing disclosures, and adapt cross-border compliance strategies.
6. Can copyrighted content be used without permission for AI training?
Sometimes. If the use is deemed transformative and non-expressive, it may qualify as fair use in the U.S.—but this is not guaranteed in Canada or Mexico.
7. What role do regulators like INDAUTOR and INEGI play?
They may propose stricter rules around AI content usage in Mexico and enforce compliance with local copyright norms.
8. Are there licensing models being developed for AI training?
Yes. Organizations and consortia are exploring rights-based licensing systems tailored to AI and machine learning.
9. What are the legal risks for startups deploying U.S.-trained models in Mexico?
Startups risk IP claims, enforcement actions, or reputational damage if their models used unlicensed copyrighted materials.