ANI v OpenAI: First Indian AI-Training Copyright Ruling
Delhi High Court's Landmark Interim Order of 24 July 2026 and What It Means for the Future of Copyright Law in IndiaTable of Contents
- 1. Introduction: India's First Major AI-Copyright Battle
- 2. Background of the Dispute
- 3. Four Critical Issues Framed by the Court
- 4. Jurisdiction: Can Indian Courts Hear This Case?
- 5. The Training and Storage Claim
- 6. The Output and Reproduction Claim
- 7. Fair Dealing Under Section 52(1)(a): The Heart of the Ruling
- 8. The Six Intervenors and Two Amici Curiae
- 9. Balance of Convenience: Why the Injunction Was Denied
- 10. Implications for India's AI and Copyright Ecosystem
- 11. Global Comparison: How Other Jurisdictions Are Handling AI Copyright
- 12. Conclusion: A Watershed Moment, Not the Final Word
1. Introduction: India's First Major AI-Copyright Battle
In the rapidly evolving intersection of artificial intelligence and intellectual property law, India has now etched its name into the global judicial ledger with a decision that legal scholars, technology companies, and content creators will study for decades to come. On 24 July 2026, the Delhi High Court delivered its first substantive interim ruling in ANI Media Pvt. Ltd. v. OpenAI OpCo LLC (CS(COMM) 1028/2024), a case that has been described as India's first significant judicial pronouncement on the legality of using copyrighted material to train large language models (LLMs).
The case, which unfolded over 32 individual hearings before Justice Amit Bansal, attracted unprecedented attention from stakeholders across the digital content ecosystem. What began as a seemingly straightforward copyright infringement claim by one of India's largest news agencies against the world's most prominent AI company has now ballooned into a precedent-setting examination of how India's Copyright Act, 1957 — a statute enacted long before the birth of generative AI — must adapt to the realities of machine learning, tokenization, and retrieval-augmented generation.
The Delhi High Court's 135-page interim order refused ANI's request for an interim injunction, holding that OpenAI's use of ANI's copyrighted news content to train ChatGPT models falls under the "fair dealing" exception under Section 52(1)(a)(i) of the Copyright Act, 1957, at least at the prima facie stage. While the main suit continues to be heard on merits, this interim determination has already sent shockwaves through the legal and technology communities, raising profound questions about the future of content ownership in the age of artificial intelligence.
2. Background of the Dispute
2.1 Who Are the Parties?
ANI Media Pvt. Ltd. (Asian News International) is one of India's leading multimedia news agencies, operating over 100 bureaus across India and the globe. Its portfolio includes edited news feeds, customized television programmes, audio bytes for radio stations, live webcasting, streamed multimedia content, and comprehensive news wire services for newspapers, magazines, and digital platforms. ANI's content represents decades of journalistic investment, editorial judgment, and financial resources.
OpenAI OpCo LLC is the California-based artificial intelligence research and deployment company behind ChatGPT, one of the world's most widely used generative AI platforms. OpenAI's LLMs are trained on vast corpora of text data sourced from the internet, including news articles, books, websites, and other publicly available written content.
2.2 The Genesis of the Lawsuit
The lawsuit was filed on 19 November 2024 before the Delhi High Court. ANI alleged that OpenAI had systematically scraped, stored, and used ANI's copyrighted news reports, interviews, and multimedia content without authorization to train the LLMs underlying ChatGPT. The news agency contended that this unauthorized use constituted a clear violation of its exclusive rights under the Copyright Act, 1957.
ANI's grievances extended beyond mere training data usage. The news agency also claimed that ChatGPT had, on multiple occasions, generated responses that falsely attributed fabricated news stories to ANI, thereby damaging the agency's reputation and contributing to the spread of misinformation in the digital sphere. This dual-pronged attack — encompassing both the input (training) and output (generation) phases of AI operation — made the case particularly complex and legally significant.
In October 2024, even before filing the lawsuit, ANI had attempted to block its domain (www.aninews.in) from being used for OpenAI's training by requesting exclusion from web crawlers. OpenAI subsequently confirmed that it had blocklisted ANI's domain from future training and retrieval-augmented generation (RAG) processes. However, this voluntary step did not resolve the underlying legal dispute, and ANI proceeded with its suit seeking both interim and permanent injunctive relief.
2.3 The Remedies Sought
ANI's prayer before the Court was comprehensive:
| Remedy Sought | Description |
|---|---|
| Interim Injunction | Restraining OpenAI from storing, publishing, reproducing, or in any manner using ANI's copyrighted works, including through ChatGPT models |
| Disable Access | Directing OpenAI to disable ChatGPT's access to ANI's published works anywhere on the internet |
| Permanent Injunction | Permanent restraint on unauthorized use of ANI's content for AI training or output generation |
| Damages | Monetary compensation for alleged copyright infringement and reputational harm |
3. Four Critical Issues Framed by the Court
Given the novel and complex nature of the dispute, the Delhi High Court carefully framed four distinct issues for adjudication. These issues would become the analytical framework not only for this case but potentially for all future AI-copyright litigation in India:
| Issue No. | Legal Question | Core Concern |
|---|---|---|
| Issue 1 | Whether the storage of ANI's data for training ChatGPT amounts to copyright infringement | The "input" or training phase — does copying and storing content for machine learning violate the reproduction right under Section 14(a)(i)? |
| Issue 2 | Whether ChatGPT's responses reproducing ANI's data amount to copyright infringement | The "output" or generation phase — do AI-generated responses that echo source material constitute unauthorized reproduction or communication to the public? |
| Issue 3 | Whether OpenAI's use qualifies as "fair dealing" under Section 52 of the Copyright Act, 1957 | The defense — can AI training be characterized as "private or personal use, including research" under India's fair dealing framework? |
| Issue 4 | Whether Indian courts have jurisdiction considering OpenAI's servers are located in the United States | Extraterritoriality — does the location of training servers defeat Indian judicial jurisdiction? |
These four issues encapsulate the fundamental tension between traditional copyright doctrine and emergent AI technology. The Court recognized that the Copyright Act, 1957 was enacted in an era when "copying" meant physical reproduction, and "communication to the public" meant broadcast or performance. The statute never contemplated a world where machines could ingest billions of copyrighted works, extract statistical patterns, and generate novel (yet sometimes eerily familiar) text outputs.
4. Jurisdiction: Can Indian Courts Hear This Case?
OpenAI's first line of defense was jurisdictional. The company argued that the Delhi High Court's Commercial Division lacked jurisdiction on multiple grounds. First, OpenAI contended that the suit combined multiple causes of action, some of which fell outside the definition of "commercial disputes" under the Commercial Courts Act, 2015. Second, and more fundamentally, OpenAI argued that because its training operations and server infrastructure were located entirely in the United States, Indian copyright law could not be applied extraterritorially.
The Court's ruling on this issue was unequivocal and carries profound implications for the global AI industry. The Delhi High Court held, on a prima facie basis, that Indian courts do have territorial jurisdiction under both Section 62(2) of the Copyright Act and Section 20 of the Code of Civil Procedure, 1908. The reasoning was multi-layered:
First, ANI's registered and principal office is located in New Delhi, establishing a clear territorial nexus. Second, OpenAI actively targets Indian subscribers, collects subscription fees from Indian users, and makes ChatGPT services commercially available within India's jurisdiction. The alleged infringing outputs are generated for and accessible to users within India. Third, and most importantly, the Court rejected the argument that the location of training servers in the United States, by itself, defeats jurisdiction.
The Court reasoned that the storage of ANI's works on US servers is merely the "terminal step" in a chain of events that begins with access to and transmission of copyrighted works from India. Severing that chain to look only at the final link would create a dangerous loophole, allowing infringers to evade Indian copyright law simply by routing their operations offshore. This "substantial connection" test aligns with modern principles of internet jurisdiction and rejects the formalistic server-location test that technology companies have historically relied upon.
5. The Training and Storage Claim
The first substantive issue before the Court concerned whether OpenAI's acts of scraping, storing, tokenizing, and vectorizing ANI's news articles for training purposes constituted copyright infringement. ANI characterized these technical steps as acts of reproduction and adaptation in electronic form, arguing that converting text into machine-readable formats did not take the use outside copyright law — it merely changed the form in which the copyrighted work was copied or processed.
OpenAI's response was technically nuanced. The company maintained that ChatGPT does not store or reproduce training data once training is complete. Any copying during the training phase, it argued, was merely an intermediate and non-expressive step in teaching the model statistical relationships, linguistic patterns, and contextual associations. OpenAI emphasized that copyright protects original expression, not facts, ideas, news events, grammar, syntax, or language patterns — all of which are the raw material of journalistic content.
The Court's interim analysis of this issue was closely intertwined with its fair dealing analysis (discussed below), because the Court ultimately held that even if the training storage constituted prima facie reproduction, it was protected by Section 52(1)(a). However, the Court made several important observations along the way:
The Court noted that ANI's content was freely accessible on its website without a paywall, and OpenAI scraped only publicly available content. The Court also acknowledged the technical reality that LLMs do not store training data in natural language or tokenized form in a manner that makes the original works retrievable by end users. The training data is internal to the model's architecture and is never communicated to the public in its original or transformed state.
6. The Output and Reproduction Claim
ANI's second major claim concerned the outputs generated by ChatGPT. The news agency presented various articles and screenshots of ChatGPT prompts and responses as evidence that the AI model was reproducing, paraphrasing, or substantially copying ANI's interviews and news reports. ANI argued that this was not merely a case of using underlying facts, but of appropriating the form and substance of its protected expression.
The Court rejected the output claim at the interim stage on several distinct and legally significant grounds:
6.1 The Training Cut-Off Problem
The Court found that all ANI articles relied upon as evidence of reproduction were published in August or September 2024, after the training cut-off dates of GPT-4 (April 2022) and GPT-4o (April 2024). Accordingly, those specific articles could not have been part of the training data. Therefore, the claim of memorization and regurgitation of those works could not be sustained at the interim stage. This evidentiary gap was fatal to ANI's output claim.
6.2 No Substantial Similarity
The Court conducted its own analysis of the examples provided by ANI and found that ChatGPT's responses were not substantially similar to ANI's articles when compared in their entirety. The Court confirmed the fundamental copyright principle that public availability of news content does not nullify copyright, but also emphasized that the fact-expression dichotomy means copyright in news articles protects the specific expression, not the underlying facts. The threshold for establishing substantial similarity in the expression of factual news content is accordingly higher than for creative works such as song lyrics or fictional narratives.
6.3 The Nature of LLM Functioning
The Court accepted the technical explanation that LLMs generate responses based on statistical patterns rather than by retrieving and reproducing stored text. The Court found that "the contention of ANI that OpenAI permanently stores the training data in order to memorize and regurgitate ANI's works cannot be accepted" at the prima facie stage. The Court considered that outputs reflecting recent ANI articles were more likely connected to live retrieval or RAG-type functionality, an aspect not specifically pleaded as the foundation of ANI's copyright claim.
7. Fair Dealing Under Section 52(1)(a): The Heart of the Ruling
The most consequential aspect of the Delhi High Court's interim order is its analysis of fair dealing under Section 52(1)(a) of the Copyright Act, 1957. This provision states that "fair dealing" with any work (other than a computer programme) for the purposes of (i) private or personal use, including research; (ii) criticism or review; or (iii) reporting of current events shall not constitute infringement.
The Court applied a rigorous two-step test to determine whether OpenAI's storage of ANI's works satisfied Section 52(1)(a), and in doing so, crafted what may become the definitive Indian framework for analyzing AI training under copyright law.
7.1 Step One: The Purpose Test
The first question was whether AI model training falls within the enumerated purposes of Section 52(1)(a)(i) — "private or personal use, including research." This question generated intense debate between the parties and among the intervenors.
ANI's Position: ANI argued that a commercial AI developer like OpenAI, operating on a subscription-based model and using content for commercial purposes, cannot invoke a defense of "private or personal use." ANI contended that the research exception cannot be invoked where the predominant purpose is commercial, and that the mere fact that content is publicly accessible does not amount to a license for unrestricted use.
OpenAI's Position: OpenAI argued for a "liberal construction" of Section 52, submitting that AI training constitutes research and private use, and that there is no statutory restriction limiting such research to non-commercial contexts. OpenAI emphasized that the legislature deliberately used the word "non-commercial" in other sub-sections of Section 52 (such as Sections 52(1)(ad), (k)(ii), (l), (n), and (o)) but conspicuously omitted such a limitation from Section 52(1)(a)(i). This legislative choice, OpenAI argued, must be given effect.
The Court's Holding: The Court agreed with OpenAI's textual analysis. It held that commercial use does not bar the fair dealing defense under Section 52(1)(a)(i). The Court noted that the Act expressly adds "non-commercial" limitations in other sub-sections but not in this one, and this deliberate legislative omission must be respected. The Court also made a critical distinction between "private" and "personal" use: while personal use may relate to an individual, private use could extend to activity within a closed corporate environment. Since ANI's material was used internally in the training process and was not itself made available to the public, the use could qualify as private.
7.2 Step Two: The Fairness Test
Having satisfied the purpose test, the Court proceeded to evaluate whether the use was "fair" by drawing on principles from Indian and international jurisprudence. The Court formulated three fairness factors specifically applicable to AI training:
| Fairness Factor | Analysis | Finding |
|---|---|---|
| Factor 1: Nature and Extent of Use | OpenAI has not been shown to use ANI's works for any purpose other than training its LLMs. The training data is never communicated to the public in natural language or tokenized form. | Use is limited to internal training; no public dissemination of original works |
| Factor 2: Market Substitution | ChatGPT's functions (content creation, research assistance, translation, summarization) are fundamentally different from ANI's business of news syndication. No evidence of ANI losing subscribers, advertising revenue, or other demonstrable market harm. | No market substitution or demonstrated commercial harm to ANI |
| Factor 3: Public Interest in AI Development | The Court recognized substantial societal benefits of trained LLMs in healthcare, education, financial services, agriculture, and accessibility. Requiring individual licenses from every copyright holder would be economically unviable and would stifle development of Indian LLMs. | Public interest strongly favors allowing AI training on available data |
7.3 The Public Interest Dimension
Perhaps the most controversial aspect of the ruling is the Court's explicit introduction of a "public interest" consideration into the fair dealing analysis. The Court took cognizance of NITI Aayog's position on AI-inclusive development and the broader societal benefits of generative AI technologies. The Court warned that requiring AI developers to obtain individual licenses from every copyright holder would create an economically unviable licensing landscape and would particularly harm domestic AI startups in early-stage development.
This public interest factor has drawn criticism from some legal commentators who argue that it introduces an overly flexible and potentially unbounded dimension to fair dealing analysis that is inconsistent with traditional copyright jurisprudence. Critics contend that while public interest is a legitimate consideration in copyright policy, using it as a direct factor in fair dealing assessment risks eviscerating the rights of content creators under the guise of technological progress.
However, defenders of the ruling argue that the Court's approach represents a necessary "updating construction" of existing statutory provisions in light of technological realities that Parliament could not have contemplated in 1957. The Court itself acknowledged that legislative gaps exist and that Parliament must ultimately address the specific question of AI training through dedicated legislation.
8. The Six Intervenors and Two Amici Curiae
Recognizing the precedent-setting nature of the case, the Delhi High Court permitted six organizations to intervene in the proceedings, reflecting the broad spectrum of stakeholders affected by the outcome. The Court also appointed two distinguished Amici Curiae to assist with the complex technical and legal issues:
| Intervenor/Amicus | Side | Interest Represented |
|---|---|---|
| Digital News Publishers Association (DNPA) | Supporting ANI | Major Indian news outlets; warned that unlicensed scraping threatens journalism's survival |
| Indian Music Industry (IMI) | Supporting ANI | Music creators and publishers concerned about AI training on copyrighted musical works |
| Federation of Indian Publishers (FIP) | Supporting ANI | Book and periodical publishers; argued that "even storing an infringing copy for a transient moment amounts to infringement" |
| Broadband India Forum | Supporting OpenAI | Technology and internet service providers advocating for balanced AI regulation |
| Flux Labs | Supporting OpenAI | Indian AI startup; argued that extracting non-expressive elements for training should not count as infringement |
| Indian Governance and Policy Project (IGPP) | Supporting OpenAI | Independent think-tank offering views on broader policy implications of AI and copyright |
| Mr. Adarsh Ramanujan, Advocate | Amicus Curiae | Practicing lawyer in IPR and copyright law appointed to assist the Court |
| Dr. Arul George Scaria, NLSIU | Amicus Curiae | Professor of Law at National Law School of India University; academic expert in copyright and technology law |
The diversity of intervenors underscores how the ANI v. OpenAI case transcends a simple bilateral dispute. It implicates the entire creative economy — from news agencies and music labels to book publishers and AI startups. The DNPA's counsel issued a stark warning during arguments: "Physical newspapers are disappearing, digital news will disappear, and only ChatGPT will remain." This apocalyptic framing captured the existential anxiety felt by many content creators facing the generative AI revolution.
9. Balance of Convenience: Why the Injunction Was Denied
Even if ANI had established a prima facie case of infringement, the Court would still have needed to evaluate the balance of convenience and the question of irreparable harm before granting an interim injunction. On this front, the Court found multiple factors weighing strongly against injunctive relief:
Quantifiable Harm: The Court noted that ANI's claim is quantifiable in monetary terms. ANI itself had offered to license its content to OpenAI for USD 7.5 million, demonstrating that any loss suffered could be compensated financially through damages rather than injunction.
Voluntary Cessation: OpenAI had already voluntarily blocked ANI's website from its web crawlers for both training and RAG purposes, mitigating the risk of ongoing harm.
US Legal Obligations: An injunction requiring OpenAI to delete training data would potentially contradict United States legal obligations to preserve such data, creating a conflict of laws situation.
User Harm: A blanket injunction would harm millions of ChatGPT users in India and impede the development of domestic LLMs, causing broader public interest harm.
Technical Self-Help: ANI has the technical ability to block web crawlers from its website through robots.txt and other standard mechanisms but has not done so, undermining its claim of irreparable harm.
10. Implications for India's AI and Copyright Ecosystem
The Delhi High Court's interim ruling in ANI v. OpenAI is not the final word on AI and copyright in India — the main suit remains pending on merits, and an appeal to the Supreme Court is widely anticipated. Nevertheless, the decision has already reshaped the legal landscape in several important ways:
10.1 For AI Developers
The ruling provides a degree of legal certainty, at least at the interim stage, that training LLMs on publicly available copyrighted content is prima facie protected under India's fair dealing framework. This is likely to encourage continued AI development and investment in India, particularly for domestic startups that lack the resources to negotiate individual licenses with millions of copyright holders. However, developers should note that the ruling is conditional and fact-specific — it applies to publicly available content, internal training use, and models that do not substantially reproduce source material in outputs.
10.2 For Content Creators
The decision represents a setback for content creators seeking to control how their works are used in AI training. News agencies, publishers, and other content producers may need to rely more heavily on technical measures (robots.txt, crawler blocking) and contractual licensing rather than injunctive copyright remedies. The ruling also suggests that Indian courts may be receptive to arguments that AI training serves public interest, making it harder for individual creators to block such use through litigation.
10.3 For Indian Policymakers
The Court explicitly noted that Parliament must address legislative gaps through dedicated legislation on AI training. This judicial nudge may accelerate the ongoing policy debate about whether India should introduce a specific AI training exception, similar to the text and data mining exceptions adopted in the European Union and other jurisdictions. The Copyright Act, 1957 was not designed for the age of generative AI, and the Court's "updating construction" of existing provisions is a temporary judicial solution, not a permanent legislative fix.
10.4 The Question of "Public Interest" in Fair Dealing
The Court's introduction of a free-wheeling "public interest" consideration into fair dealing analysis is perhaps the most doctrinally significant aspect of the ruling. While public interest has always been a background consideration in copyright law, making it an explicit factor in the fairness test represents a notable expansion of judicial discretion. If this approach is affirmed by higher courts, it could transform fair dealing from a relatively predictable defense into a more flexible, policy-driven doctrine — for better or worse.
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11. Global Comparison: How Other Jurisdictions Are Handling AI Copyright
The ANI v. OpenAI case does not exist in a vacuum. Courts and legislatures around the world are grappling with identical questions, and the Delhi High Court's ruling both draws from and diverges from international approaches:
| Jurisdiction | Approach to AI Training | Key Case/Development |
|---|---|---|
| United States | Fair use doctrine; transformative use analysis. Courts have generally been receptive to fair use defenses for training, citing cases like Authors Guild v. Google and Andy Warhol Foundation v. Goldsmith. | Multiple pending cases including NYT v. OpenAI and Andersen v. Stability AI; no final appellate ruling yet on LLM training. |
| European Union | Directive 2019/790 introduces explicit text and data mining (TDM) exceptions for research purposes, with opt-out rights for rights holders for commercial TDM. | EU AI Act (2024) imposes transparency obligations on AI developers regarding training data. |
| United Kingdom | Section 29A of the Copyright, Designs and Patents Act 1988 permits TDM for any purpose, but rights holders can contract out of the exception. | Getty Images v. Stability AI (pending) — alleging unauthorized use of images for training. |
| Japan | Article 30-4 of the Copyright Act permits information analysis (including machine learning) regardless of purpose, unless the use "unreasonably prejudices the interests of the copyright owner." | One of the most AI-developer-friendly regimes globally. |
| India | No specific AI training exception. Delhi High Court applied general fair dealing under Section 52(1)(a) to find prima facie protection for training use. | ANI Media v. OpenAI (2026) — first significant ruling; interim order only; main suit pending. |
The global trend suggests a spectrum of approaches, from the permissive Japanese model to the more rights-holder-oriented EU opt-out framework. India's position, as articulated by the Delhi High Court, leans toward permissiveness at the interim stage but leaves room for legislative intervention. The Court's reliance on fair dealing rather than a specific TDM exception means that Indian AI developers currently operate under greater judicial uncertainty than their counterparts in Japan or the EU, where statutory clarity exists.
12. Conclusion: A Watershed Moment, Not the Final Word
The Delhi High Court's interim order of 24 July 2026 in ANI Media Pvt. Ltd. v. OpenAI OpCo LLC is undeniably a watershed moment in Indian intellectual property law. It is the first time an Indian court has grappled in depth with the legality of using copyrighted material to train large language models, and its ruling that such use is prima facie protected by fair dealing under Section 52(1)(a) of the Copyright Act, 1957 will influence litigation strategy, business models, and legislative agendas for years to come.
Yet it is crucial to remember what this decision is and what it is not. It is an interim order refusing injunctive relief at the prima facie stage. It does not finally adjudicate whether OpenAI's training practices constitute copyright infringement. It does not establish a permanent fair dealing precedent that will automatically apply to all AI training cases. And it explicitly invites Parliament to fill the legislative gaps that the Court has identified through its "updating construction" of a 68-year-old statute.
The case also leaves several profound questions unanswered. What happens when AI models are trained on paywalled or subscription-only content? What is the legal status of outputs that do substantially reproduce copyrighted expression? How should Indian courts treat AI training by domestic startups versus multinational corporations? And how should the "public interest" factor in fair dealing be bounded to prevent it from swallowing the rights of individual creators?
These questions will likely be addressed in the full trial on merits, and potentially by the Supreme Court of India if the case reaches there — as many legal commentators expect it will. The Supreme Court may ultimately have the opportunity to settle one of the most important doctrinal questions in Indian copyright law: what are the precise factors that should go into determining "fair dealing" in the age of artificial intelligence?
For now, the message from the Delhi High Court is clear: India's copyright law, as it currently stands, does not prohibit the use of publicly available copyrighted content for AI model training at the interim stage. Whether that remains the law after full trial, appellate review, and legislative intervention is a story that is only beginning to unfold. One thing, however, is certain — the ANI v. OpenAI case has secured its place in the annals of Indian legal history as the moment when India's judiciary first confronted the awesome challenge of regulating artificial intelligence within the framework of copyright law.
"The law must adapt to technology, but technology must also respect the law. The balance between innovation and creation is not a zero-sum game — it is a constitutional imperative that demands careful, nuanced adjudication." — Paraphrased from the spirit of the Delhi High Court's observations.
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Disclaimer: This article is for educational and informational purposes only and does not constitute legal advice. The analysis is based on the interim order dated 24 July 2026 as reported and publicly available. The final adjudication on merits remains pending before the Delhi High Court. Readers are advised to consult qualified legal professionals for specific cases.
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