Generative AI has gone from a curiosity to a cornerstone of digital content creation in barely three years. By early 2025, over 80% of enterprise marketing teams report using at least one generative AI tool for copywriting, image creation, or code generation (Salesforce State of Marketing, 2025). Tools like ChatGPT, Midjourney, DALL·E 3, Stable Diffusion, and GitHub Copilot are embedded in everyday workflows.

But with adoption comes a thorny question: Who owns what AI creates?

The legal world is scrambling to keep pace. Courts are handing down landmark decisions, legislators are passing new frameworks, and businesses are caught in the middle—often without clear guidance.

This article breaks down the current state of generative AI and copyright law as of 2025. We will look at key rulings, global regulatory frameworks, practical compliance strategies, and what it all means for companies that rely on digital content. At Lueur Externe, we help businesses across France and internationally navigate these intersections of technology and compliance every day—so let us walk you through it.

The Fundamental Question: Can AI Be an Author?

The Human Authorship Requirement

Copyright law, in virtually every major jurisdiction, was built on a simple premise: a human creates a work, and the law grants that human exclusive rights over it.

  • United States: The U.S. Copyright Office has repeatedly stated that copyright requires human authorship. Its March 2023 guidance—still in effect in 2025—specifies that works generated “by a machine without creative input or intervention from a human author” are not eligible for registration.
  • European Union: The Court of Justice of the EU (CJEU) has long held that copyright protects works that are the “author’s own intellectual creation,” which presupposes a human author.
  • United Kingdom: The UK is an outlier: Section 9(3) of the Copyright, Designs and Patents Act 1988 allows for copyright in “computer-generated” works, assigning authorship to “the person by whom the arrangements necessary for the creation of the work are undertaken.” However, even this provision is under review as of 2025.

What About AI-Assisted Works?

The nuance matters enormously. There is a spectrum:

ScenarioLikely Copyright Status (2025)
Human writes a novel entirely by handFully copyrightable
Human uses AI to brainstorm, then writes and edits substantiallyLikely copyrightable (human authorship dominant)
Human types a short prompt, AI generates an entire articleUnlikely copyrightable in most jurisdictions
AI autonomously generates an image with no human creative inputNot copyrightable (US, EU, most of Asia)
Human selects, arranges, and modifies AI outputs into a collagePotentially copyrightable (selection/arrangement)

The U.S. Copyright Office’s February 2025 update reinforced this sliding scale, noting that registration will be evaluated on a case-by-case basis, examining “the extent of human authorship” in each submitted work.

Landmark Cases Shaping 2025

Thaler v. Perlmutter (United States, 2023–2025)

Stephen Thaler attempted to register a visual artwork created by his AI system, DABUS, listing the AI as the author. The U.S. District Court for the District of Columbia ruled in August 2023 that human authorship is an essential requirement for copyright. Thaler’s appeal was denied in early 2024, and the Supreme Court declined to hear the case in 2025. The precedent stands firmly.

Kris Kashtanova’s graphic novel, Zarya of the Dawn, was created using Midjourney for illustrations and human-written text. The Copyright Office granted copyright to the text and the overall selection/arrangement of images—but denied copyright to the individual AI-generated images themselves. This remains the clearest example of the “partial protection” approach.

Getty Images v. Stability AI (UK / US, 2023–2025)

Getty Images sued Stability AI for allegedly using 12 million copyrighted photographs to train Stable Diffusion without permission. The case is still in litigation in 2025, but it has already forced the industry to reconsider training-data provenance. Several preliminary rulings have favored Getty’s right to proceed, signaling that training on copyrighted data without a license is a genuine legal vulnerability.

The New York Times v. OpenAI & Microsoft (US, 2024–2025)

The New York Times sued OpenAI and Microsoft, alleging that ChatGPT was trained on millions of NYT articles and can reproduce them nearly verbatim. OpenAI argues fair use. As of mid-2025, the case is in the discovery phase and is widely considered the most consequential copyright case of the decade. A ruling here could redefine the boundaries of fair use in the AI era.

Concord Music v. Anthropic (US, 2024–2025)

Music publishers sued Anthropic (maker of Claude) for reproducing copyrighted song lyrics in AI outputs. This case highlights that the copyright issue extends beyond images and text—any copyrightable medium fed into training data is potentially implicated.

Global Regulatory Landscape in 2025

The EU AI Act: Transparency Above All

The EU AI Act, which became fully enforceable in stages through 2024–2025, is the world’s most comprehensive AI regulation. For generative AI and copyright, the key provisions include:

  • Article 52 (Transparency): Providers of generative AI systems must disclose that content was AI-generated.
  • Article 28b (General-purpose AI models): Providers must publish sufficiently detailed summaries of training data used, respecting copyright law.
  • Recital 60e: Explicitly references the EU Copyright Directive (2019/790), stating that the text and data mining (TDM) exceptions do not override rights holders’ opt-out mechanisms.

In practice, this means that if a European publisher or photographer opts out of AI training (via robots.txt, metadata tags, or contractual terms), AI companies must respect that opt-out or face fines of up to €35 million or 7% of global turnover.

United States: Legislation in Motion

The U.S. has no comprehensive federal AI copyright law yet. However, several bills are advancing:

  • The AI Disclosure Act of 2024 (reintroduced in 2025): Requires clear labeling of AI-generated content.
  • The Generative AI Copyright Disclosure Act: Would require AI companies to submit training data records to the Copyright Office.
  • Executive Order 14110 (October 2023): Directed agencies to study AI and IP; reports submitted in 2024 recommended statutory updates, but Congress has yet to act conclusively.

The legal framework in the U.S. remains largely judge-made, with the cases above doing the heavy lifting.

China’s Approach: Pragmatic and Fast

China has been surprisingly proactive:

  • The Beijing Internet Court ruled in November 2023 that an AI-generated image could be copyrighted—if the human user made sufficient creative choices in prompting and selecting the output. This is more permissive than the U.S. or EU approach.
  • China’s Interim Measures for the Management of Generative AI Services (effective August 2023) require that training data respect intellectual property rights and that AI-generated content is clearly labeled.

Japan: The Training-Data Exception

Japan’s Copyright Act (Article 30-4) has one of the broadest exceptions for AI training: using copyrighted works for machine learning is generally permitted, even for commercial purposes, as long as the purpose is “not intended for human consumption of the expression.” This has made Japan a favored jurisdiction for AI training operations—but growing domestic criticism may lead to amendments in late 2025.

Practical Risk Matrix for Businesses

If you are using generative AI in your business—for marketing content, product descriptions, website copy, images, or code—here is a practical risk assessment:

ActivityRisk LevelKey Concern
Using AI to draft blog posts, then heavily editingLowMaintain records of human editing process
Publishing AI-generated images without modificationMedium–HighNo copyright protection; potential training-data infringement
Using AI-generated code in production softwareMediumLicense contamination (copyleft code in training data)
Fine-tuning an AI model on your own copyrighted dataLowYou hold the rights to the training data
Fine-tuning on scraped third-party contentHighLikely infringement unless you have licenses or a valid exception
Claiming copyright on purely AI-generated outputHighRegistration may be denied; legal challenges from third parties

Best Practices: Protecting Your Business in 2025

1. Implement a Human-in-the-Loop Workflow

The single most effective strategy is to ensure meaningful human creative involvement at every stage:

  • Draft detailed, creative prompts (not generic ones).
  • Select, curate, and arrange AI outputs deliberately.
  • Edit, revise, and transform the output substantially.
  • Document every step.

This positions your final work as a human-authored creation that used AI as a tool—similar to using Photoshop or a spell checker.

2. Audit Your AI Tools’ Training Data

Ask your AI providers:

  • What data was the model trained on?
  • Were licenses obtained for copyrighted material?
  • Does the tool offer an “opt-out” or “rights-cleared” dataset option?

Several providers now offer enterprise tiers with indemnification clauses (Adobe Firefly, Getty’s Generative AI, Shutterstock’s AI image generator). Paying for licensed AI tools is an investment in legal safety.

3. Label AI-Generated Content Appropriately

The EU AI Act requires it. Even where not yet legally mandated, transparent labeling:

  • Builds trust with your audience.
  • Reduces the risk of misleading consumers (a growing concern for regulators).
  • Prepares you for regulations that are clearly coming.

4. Use Technical Metadata

Embed provenance metadata in your AI-generated content. The C2PA (Coalition for Content Provenance and Authenticity) standard, backed by Adobe, Microsoft, and the BBC, provides a technical framework:

{
  "c2pa.claim": {
    "dc:title": "Product Image - Spring 2025 Campaign",
    "c2pa.actions": [
      {
        "action": "c2pa.created",
        "softwareAgent": "Adobe Firefly 3.0",
        "when": "2025-04-10T14:30:00Z"
      },
      {
        "action": "c2pa.edited",
        "softwareAgent": "Adobe Photoshop 26.1",
        "when": "2025-04-10T15:45:00Z",
        "description": "Manual color correction, background replacement, text overlay"
      }
    ],
    "c2pa.credential": {
      "author": "Jane Dupont, Marketing Team",
      "organization": "Your Company SAS"
    }
  }
}

This metadata creates a verifiable chain of custody that can support your copyright claims and demonstrate compliance.

5. Establish Internal AI Governance Policies

Every company using generative AI should have a written policy covering:

  • Approved tools and use cases.
  • Prohibited uses (e.g., generating content that impersonates real people).
  • Documentation requirements.
  • Review and approval workflows.
  • Disclosure standards.

At Lueur Externe, we work with clients to integrate these governance frameworks directly into their digital workflows, ensuring that AI-powered content creation is both efficient and legally sound.

The Training Data Debate: Fair Use vs. Licensing

The most heated legal battle in 2025 is not about AI outputs—it is about inputs. Specifically: is it legal to train AI models on copyrighted content?

The Fair Use Argument (Primarily U.S.)

AI companies argue that training is transformative use—the model does not copy individual works but learns statistical patterns. They cite Google v. Oracle (2021), where the Supreme Court found that Google’s use of Java APIs was fair use because it was transformative.

Counter-arguments:

  • AI training involves making full copies of copyrighted works, even if temporarily.
  • AI outputs can sometimes closely resemble specific training examples (the NYT case demonstrated near-verbatim reproduction).
  • The commercial impact on rights holders is significant: if AI can generate images in the style of a specific photographer, that photographer loses licensing revenue.

The EU’s Opt-Out Framework

The EU Copyright Directive (Article 4) allows TDM for commercial purposes unless the rights holder has expressly opted out. This is more structured than the U.S. fair use analysis and gives creators a concrete mechanism to control how their work is used.

In 2025, major European publishers, photography agencies, and music labels have deployed opt-out mechanisms at scale. AI companies operating in Europe must implement systems to respect these opt-outs—or face enforcement.

The Licensing Model Emerges

Increasingly, the market is resolving what the law has not yet settled:

  • Associated Press licensed its archive to OpenAI.
  • Axel Springer (Bild, Politico) signed a licensing deal with OpenAI.
  • Shutterstock and Getty built their own AI tools trained exclusively on licensed content.
  • Reddit, Tumblr, and WordPress.com have signed data-licensing agreements with AI companies.

This suggests the long-term solution may be a licensing ecosystem rather than outright prohibition or blanket fair use.

What This Means for SEO and Digital Content Strategy

For businesses focused on digital visibility—our core expertise at Lueur Externe—the copyright landscape around generative AI has direct implications:

  • Google’s stance on AI content: Google has clarified that AI-generated content is not inherently penalized, but it must meet E-E-A-T standards (Experience, Expertise, Authoritativeness, Trustworthiness). Content that is substantially human-reviewed and enhanced performs better.
  • Duplicate and thin content risk: If you rely on AI to produce generic content without editing, you risk producing material that is statistically similar to thousands of other AI-generated pages—hurting your rankings.
  • Copyright as a competitive moat: Original, human-authored (or human-augmented) content that you can legally protect gives you a competitive advantage. Purely AI-generated content that anyone can reproduce offers no such advantage.
  • Schema markup and provenance signals: Implementing C2PA metadata and AI disclosure may become ranking signals or trust signals in the near future.

Looking Ahead: What to Expect in Late 2025 and Beyond

Several developments will shape the rest of 2025:

  1. The NYT v. OpenAI ruling could come by late 2025 or early 2026 and will likely set the U.S. standard for AI training and fair use.
  2. EU AI Act enforcement will ramp up, with the first fines expected by Q4 2025.
  3. The U.S. Copyright Office is expected to release updated registration guidance specifically addressing AI-assisted works.
  4. WIPO (World Intellectual Property Organization) is convening global consultations on an international treaty framework for AI and IP—though any treaty is years away.
  5. Technical standards for content provenance (C2PA, watermarking) will become more widespread, potentially becoming de facto requirements for platforms.

The intersection of generative AI and copyright law in 2025 is complex, fast-moving, and full of unresolved questions. But the direction is clear:

  • Human authorship still matters. Use AI as a powerful tool, not a replacement for creative judgment.
  • Transparency is non-negotiable. Label AI-generated content, document your process, and choose tools with clear data provenance.
  • Compliance is a competitive advantage. Businesses that get this right build trust with their audiences and protect their content assets.
  • The law is catching up. What is a gray area today may be a bright-line rule tomorrow. Prepare now.

Whether you are building an e-commerce platform, managing a content-heavy website, or deploying AI-powered tools across your digital ecosystem, having a partner who understands both the technology and the regulatory landscape is essential.

Lueur Externe, with over two decades of experience in web development, SEO, and emerging technologies, helps businesses across the Alpes-Maritimes and beyond integrate AI responsibly, stay compliant, and maximize their digital performance. Ready to future-proof your digital strategy? Get in touch with our team today.