The Wikimedia Foundation, the nonprofit behind Wikipedia, has filed an amicus brief in major US AI copyright litigation involving publishers, OpenAI and Microsoft. Its position is not fully aligned with either side: Wikimedia argues that courts should distinguish between training large language models on copyrighted content and outputting copyrighted material to users. The organisation says an overly broad ruling could have wider consequences for the open web and for the development of useful AI tools.

What happened

According to reporting by The Verge, Wikimedia submitted a friend-of-the-court brief in a set of closely watched copyright cases, including litigation brought by publishers such as The New York Times against OpenAI and Microsoft. Wikimedia’s argument is that legal analysis should not treat every stage of generative AI systems in the same way.

In practical terms, the foundation is asking courts to separate two issues:

• Model training: whether AI developers can use copyrighted material to train large language models.
• Model outputs: whether chatbots reproduce or closely imitate protected works in ways that may infringe copyright.

Wikimedia warns that a black-and-white ruling could create unintended consequences. In its view, a decision that is too restrictive on training could limit the development of AI tools that support knowledge work and online collaboration. On the other hand, a decision that is too permissive on outputs could weaken protections for publishers and other rights holders.

Why it matters for European businesses

Although these are US court cases, they matter beyond the United States because they could influence how AI vendors build products, how content owners negotiate licences, and how businesses assess legal risk when deploying generative AI tools.

For European companies, the issue is especially relevant in three areas:

• AI adoption: many SMEs and digital teams use or plan to use LLM-based tools for search, customer support, content drafting, coding and workflow automation. Court rulings that affect training practices or output restrictions could change product capabilities, pricing or licensing models.
• Content and publishing: businesses that produce proprietary content, including media, research, product data and marketing materials, are watching how courts treat the use of copyrighted material in AI systems.
• Open web visibility: if legal pressure changes how AI companies access, train on or cite web content, there may be downstream effects on how websites gain visibility, referral traffic and attribution in AI-driven search and answer engines.

This does not create a new legal obligation for European businesses by itself. However, it is an important signal in a broader global debate over how copyright law should apply to generative AI.

Who may be affected

• SMEs adopting AI tools: especially businesses using third-party LLM services for internal productivity, customer service or marketing workflows.
• Publishers and content-led businesses: companies whose value depends on original written, visual or structured content.
• E-commerce companies: retailers using AI to generate product descriptions, support content, search assistance or merchandising workflows.
• Digital and IT teams: teams assessing procurement, risk and governance for AI systems embedded into business processes.
• Agencies and marketing teams: firms relying on generative AI for copy, summarisation, campaign production or SEO-related workflows.

What companies should consider

While the litigation is still evolving, European businesses can already take practical steps:

• Review supplier terms: check what AI vendors say about training data, output safeguards, indemnities and intellectual property risk.
• Separate use cases: distinguish between low-risk internal assistance and higher-risk public-facing outputs such as published copy, reports or customer answers.
• Maintain human review: where AI-generated content could resemble third-party material, add editorial or legal review before publication.
• Protect proprietary content: consider how your own website, documentation or data may be accessed, reused or licensed in an AI ecosystem.
• Track legal and platform changes: outcomes in major copyright cases may influence product features, output controls, training disclosures and future licensing negotiations.

For European business leaders, the key issue is not only whether AI models can be trained on online content, but how future court decisions may reshape the balance between innovation, copyright protection and the economics of the open web.