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Artificial intelligence now writes music, produces images, drafts text, and generates software code. What the law should make of these outputs has divided courts, registries, and policymakers around the world. A recent decision from the Indian Copyright Office has now added an important voice to that conversation. Writing in an expert commentary, Professor Ryan Abbott, Professor of Law and Health Sciences at the University of Surrey, explains that the office has ruled a work generated through algorithmic or computational processes can still meet the legal test for originality and qualify for copyright protection. The decision is the first of its kind in India and carries significance well beyond its borders.
For anyone who creates with AI tools, invests in them, or advises others on intellectual property, the case rewards close attention. Have questions about how the ruling might affect your own work? Share your thoughts in the comments below, or explore our related articles on artificial intelligence and intellectual property for further reading.
The central question in copyright law has always been whether a work is original. When a human writes a novel or paints a picture, originality is generally assumed to flow from the author’s skill and judgment. When an algorithm produces something similar, many registries and courts have struggled to say whether the result deserves protection at all. Some argue that because no human mind shaped each line or brushstroke, the output cannot be original.
The Indian Copyright Office has now pushed back against that assumption. As Professor Abbott notes, the Registrar rejected the argument that a work created using AI must inherently lack originality. The decision found that the work’s final form was not predetermined, that it did not reproduce an existing work, and that it contained the minimum degree of expressive creativity required for copyright protection. In plain terms: the use of AI does not, by itself, make a work unoriginal.
This matters for three reasons. First, it establishes a precedent in one of the world’s largest creative and technology markets. Second, it aligns India with jurisdictions such as the United Kingdom that have long made room for computer-generated works. Third, it shifts the debate away from a blunt question – “was AI involved?” – and toward the more useful questions of how the work was produced and whether it displays the creativity copyright law is designed to reward.
The decision arose from an application involving DABUS, short for Device for the Autonomous Bootstrapping of Unified Sentience, an AI system created by Dr Stephen Thaler. DABUS has become one of the best-known test cases for machine creativity worldwide, appearing in patent and copyright proceedings across multiple countries.
In this instance, the application listed DABUS itself as the author of the work. That choice proved decisive, though perhaps not in the way the applicants expected. Professor Abbott, who has advised Dr Thaler, explained that the proposal was instead to name Dr Thaler – the person who created, owned, and used DABUS – as the author, while making clear that the work was AI-generated. The registry rejected the application on the narrower procedural ground that an AI system cannot be named as an author, rather than on the substantive question of whether the work itself deserved protection.
The distinction matters. The Indian Copyright Office did not say that AI-generated works are unprotectable. It said that this particular application identified the wrong author. An appeal is now planned to seek recognition of Dr Thaler as the author and producer of the work.
India’s Copyright Act is notable in that it explicitly recognises “computer-generated” works. Where there is no traditional human author, the law allows the person who caused the work to be created to be treated as its author. This provision was drafted long before modern generative AI, but it gives Indian law a ready-made framework for the current wave of machine-assisted creativity.
Under this approach, the question is not whether a human wrote every line, but who caused the work to come into existence. A developer who builds and directs an AI system, or a user who prompts and curates its output, may stand in the position the statute describes. The recent ruling signals that the Registrar is willing to apply this framework to genuine AI-generated content rather than reading it out of existence.
Professor Abbott highlights that India’s approach is similar to the position under UK copyright law. The UK’s Copyright, Designs and Patents Act 1988 contains a comparable provision for computer-generated works: where there is no human author, the author is taken to be the person by whom the arrangements necessary for the creation of the work were undertaken.
For businesses and creators operating internationally, this creates a meaningful convergence. The UK and India, two major economies with deep creative and technology sectors, both offer a statutory route to protecting works produced without a traditional human author. By contrast, other jurisdictions – the United States among them – have taken a stricter line by insisting on human authorship as a prerequisite for registration. The result is a fragmented global picture in which the same AI-generated work may be protected in London and New Delhi but face obstacles elsewhere.
That fragmentation makes decisions like India’s all the more influential. As Professor Abbott observes, the outcome of the planned appeal could provide much-needed clarity on how existing copyright laws apply to AI-generated content and shape the international debate over authorship, originality, and artificial intelligence.
The heart of the ruling lies in its treatment of originality. The Registrar examined the work and made three findings worth noting for anyone following developments in originality and copyright:
Together, these findings reframe the originality test in the age of AI. The focus moves from the identity of the creator to the character of the work itself. If an output is not predetermined, not copied, and minimally creative, the method of its production – algorithmic or otherwise – does not disqualify it from protection.
For artists, writers, musicians, and developers experimenting with generative tools, the decision offers reassurance that AI-assisted output is not automatically in the public domain. It also underscores the importance of process: keeping records of how a work was produced, what inputs shaped it, and how the final form was selected could become valuable evidence in any future dispute over originality.
It is easy to misread headlines about this case as a rejection of AI copyright. The opposite is closer to the truth. The application failed because it named the AI system as the author, an approach the law does not permit. The substantive question – whether a work generated by DABUS can qualify for protection with a human applicant properly identified – remains live and will be tested on appeal.
For practitioners, the lesson is practical: applications involving AI-generated works should identify a qualifying human or legal person as author under the applicable statutory framework, while transparently disclosing the role of the AI system. Precision in the paperwork, not the technology itself, determined this outcome.
The appeal will ask the Indian authorities to recognise Dr Thaler as the author and producer of the work created by DABUS. Its outcome could settle how the computer-generated works provision is applied in practice: who qualifies as the person who “caused” a work to be created, what disclosure of AI involvement is required, and how originality should be assessed when an algorithm performs much of the expressive work.
The decision will also resonate internationally. Legal systems are watching one another as they confront AI-generated works, and a clear statement from India – particularly one grounded in existing statutory text rather than new legislation – could influence registries and courts elsewhere. Anyone tracking authorship and AI news should treat the appeal as a milestone case.
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Whatever the eventual outcome of the appeal, organisations working with generative AI can act now to protect their interests:
Debates like this one sit at the crossroads of law, technology, and health sciences – the fields Professor Ryan Abbott examines in his research at the University of Surrey. For students and professionals who want to engage with these questions in depth, studying intellectual property law at an institution actively shaping the debate offers a distinct advantage. Explore the University of Surrey’s law programmes to learn how its teaching and research connect with real-world developments in AI and innovation.
The Indian Copyright Office’s ruling marks a turning point in the treatment of AI-generated works. By holding that algorithmic creation does not defeat originality, and by grounding that conclusion in a statute that already accommodates computer-generated works, India has offered a workable template for other jurisdictions weighing similar questions. The procedural rejection of the DABUS application, and the appeal that follows, will determine the final shape of those rules.
For creators and businesses, the message is straightforward: AI-assisted work may well be protectable, but strategy and careful process matter as much as the technology itself. Considering how these developments apply to your own portfolio? Schedule a free consultation with an intellectual property adviser to review your position, and share this article with colleagues who follow copyright and AI policy.