As generative AI becomes more widespread in fashion, legal experts warn of mounting risks around copyright, trade secrets, and platform liability, prompting calls for stricter governance and innovative protections.
From safeguarding intellectual property to policing employees’ use of algorithms, the fashion industry is grappling with a rapidly shifting legal landscape as generative artificial intelligence becomes more capable and more pervasive. The issue took centre stage at the Assises Juridiques de la Mode, du Luxe et du Design in Paris on December 9, where lawyers, in‑house counsel and technologists warned that existing frameworks are struggling to keep pace. [1]
” In 2024, we submitted 2.5 million reports of counterfeit content to platforms,” said Nicolas, ’s director of online brand protection, describing how AI has made it increasingly easy to generate infringing content such as fake Advent calendars for group brands. Industry observers say the acceleration of automated content creation amplifies longstanding counterfeiting risks already associated with fast‑fashion platforms. Data and reporting from recent cases suggest that rapid, algorithm‑driven product cycles can both mask and multiply infringement at scale. [1][6][7]
In legal terms, questions now extend beyond classic copyright claims to the ownership of interactions with “intelligent agents” and the provenance of training data. Alexandre Menais, general counsel for the group, warned that “with an intelligent agent, the question arises of who owns that interaction”, and expressed concern that employees will test open models outside closed, approved systems , a practice that could leak protected designs and confidential know‑how. Similar litigation in other sectors underscores these risks: a proposed class action against design software firm Figma alleges users’ files were used without consent to train AI tools, raising trade secrets and data‑use claims rather than only copyright disputes. [1][2]
A central legal distinction highlighted at the conference is between closed AI systems , those trained on datasets cleared with rights‑holders , and open systems that rely on broad “text and data mining” exceptions. Christiane Féral‑Schuhl, a specialist lawyer and former president of the Conseil National des Barreaux, warned that open models can “swallow up all this ‘training data'” and that employees using them effectively share their creations with competitors. Across industries, major studio lawsuits against Midjourney and others have framed similar complaints as copyright or unfair appropriation, signalling that creators increasingly expect courts to police how models are trained and used. [1][3][5]
The contractual terms of AI suppliers also came under scrutiny. Féral‑Schuhl noted some vendors include clauses allowing a customer’s work to be used to “improve the service for all customers” , a provision that is highly problematic in a creative context, where such reuse should arguably be prohibited. Proposals discussed at the event included watermarking or “digital tattooing” of training data and robust information tagging that records date and provenance for AI‑generated outputs, measures that proponents say could rein in unauthorised reuse and help enforce takedown mechanisms. Content‑owners and regulators in media and entertainment have already pursued litigation and statutory approaches to similar problems. [1][3][5]
Technical advances are complicating enforcement and attribution. Frédéric Rose of IMKI, which builds bespoke generative AI for brands, said models are soon likely to draft patterns and technical execution files and already can suggest materials, fabric weights and stitching types , detail that both increases creative productivity and creates new vectors for copying. This level of precision makes counterfeits easier to spot in some cases, but also means an AI can assemble near‑exact reproductions of proprietary designs from diverse inputs. Observers caution that the same capabilities may enable faster infringement if governance is lax. [1][7]
Marketplaces and logistics platforms are entwined in the debate. Hugo Weber of Mirakl argued AI can make fulfilment algorithms exceptionally efficient, while urging caution about treating platforms as a single problem: “European, American and Chinese players all have different notions of responsibility,” he said. Enforcement perspectives vary: regulators are shifting from preventive oversight to litigation‑driven remedies, and platform liability remains a contentious cross‑jurisdictional issue as civil claims proliferate. [1][7]
High‑profile lawsuits highlight the legal battleground for fashion and adjacent creative industries. Beyond studio suits against image generators, fashion brands have pursued fast‑fashion retailers for copying designs , suits that sometimes allege AI played a role but often rest on classical infringement claims. Legal analysts expect more cases that blend copyright, trade‑secret and unfair‑competition theories, and point to the Figma action as an example where plaintiffs frame harms as misappropriation of customer data rather than only derivative works. The prospect of multi‑front litigation , against platforms, AI suppliers and internal actors , is prompting calls for clearer contractual protections, tighter internal governance and pan‑European regulatory coordination. [1][2][3][6]
Industry and legal advisers increasingly recommend a governance‑first approach: enforce human oversight, require disclosure of AI use, train staff in AI literacy, audit outputs for originality and preserve brand voice and technical secrecy. According to the original report from the Paris conference, defining “red lists” of iconic elements and building closed, rights‑cleared AIs are among practical steps brands can take now. Legal commentators add that while AI can amplify efficiency and creativity, unchecked use risks substantial reputational and financial harms , a balance that will shape litigation, contract practice and regulatory policy going forward. [1][4][2]
##Reference Map:
- [1] (FashionNetwork) – Paragraph 1, Paragraph 2, Paragraph 3, Paragraph 4, Paragraph 5, Paragraph 6, Paragraph 7, Paragraph 8, Paragraph 9
- [2] (Reuters) – Paragraph 3, Paragraph 8, Paragraph 9
- [3] (AP) – Paragraph 4, Paragraph 5, Paragraph 8
- [4] (Reuters) – Paragraph 9
- [5] (AP) – Paragraph 5, Paragraph 8
- [6] (Wikipedia/Shein summary) – Paragraph 2, Paragraph 8
- [7] (Time) – Paragraph 2, Paragraph 6, Paragraph 7
Source: Noah Wire Services
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The narrative was published on December 10, 2025, making it current. The report references events from December 9, 2025, indicating timely coverage. However, similar discussions have been reported in recent months, such as the Reuters article on December 3, 2025, discussing legal risks in the food and beverage industry related to AI-generated content. ([reuters.com](https://www.reuters.com/legal/litigation/branding-age-dupe-culture-legal-risks-trade-dress-enforcement-food-beverage-2025-12-03/?utm_source=openai)) Additionally, the New York Times filed a lawsuit against Perplexity for copyright infringement on December 5, 2025, highlighting ongoing legal challenges in the AI sector. ([axios.com](https://www.axios.com/2025/12/05/nyt-sues-perplexity-for-copyright-infringement?utm_source=openai)) These instances suggest that while the narrative is fresh, the topic has been under discussion for several months.
Quotes check
Score:
9
Notes:
The direct quotes from Nicolas Lambert and Alexandre Menais are unique to this report, with no exact matches found in earlier publications. This suggests the content is original or exclusive. However, the themes discussed align with broader industry concerns about AI’s impact on intellectual property, as seen in other recent articles.
Source reliability
Score:
7
Notes:
The narrative originates from FashionNetwork, a publication focused on the fashion industry. While it provides industry-specific insights, it may not have the same level of credibility as major news outlets. The report cites reputable sources, including Reuters and AP News, which adds credibility to the information presented.
Plausability check
Score:
8
Notes:
The claims about AI’s impact on the fashion industry’s intellectual property are plausible and align with ongoing discussions in the sector. The references to legal cases, such as the lawsuit against Midjourney by Disney and Universal, support the narrative’s credibility. ([apnews.com](https://apnews.com/article/722b1b892192e7e1628f7ae5da8cc427?utm_source=openai)) The language and tone are consistent with industry reports, and the inclusion of specific details adds to the narrative’s authenticity.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): MEDIUM
Summary:
The narrative is current and presents original quotes, suggesting exclusivity. While the source is industry-specific, it cites reputable outlets, enhancing credibility. The claims are plausible and supported by recent legal cases, though the topic has been under discussion for several months.
