Impact of Generative AI on Copyright and Creativity: A Legal Analysis with Special Reference to India

Abstract

Generative artificial intelligence has moved copyright debates beyond ordinary copying and distribution into questions of training data, machine-authored outputs, market substitution and the future of human creativity. This paper examines how Indian copyright law can respond to AI systems that ingest protected works and generate text, images, music, code and audiovisual material. It argues that India should neither treat every act of machine learning as infringement nor treat every use of protected works for training as automatically lawful. The Copyright Act, 1957, Indian originality doctrine and fair dealing principles provide a foundation, but they require AI-specific application. The paper proposes a human-centred and market-sensitive framework based on disclosure of AI use, protection only for human creative contribution, liability for substantially similar outputs, calibrated licensing for commercial training datasets, preservation of research exceptions, and coordination with personality-rights and platform-governance rules.

Introduction

It explains that AI training involves copying and processing large datasets of copyrighted material, while outputs may range from entirely original works to closely derivative ones. This creates three legal issues: the legality of using copyrighted works for training, whether AI-generated outputs can be copyrighted, and the economic impact on creative markets. The paper argues for a balanced Indian legal approach that avoids both unrestricted AI training and overly strict bans, instead favoring disclosure rules, human authorship requirements, and licensing or compensation where appropriate.

Under Indian copyright law, protection applies to original expression—not ideas or styles—and includes rights over reproduction and adaptation. Section 2(d)(vi) recognizes computer-generated works by assigning authorship to the person who causes the work to be created, but this framework is insufficient for modern AI systems. Courts, especially through the Eastern Book Company v. D.B. Modak ruling, emphasize that copyright requires skill and creativity, meaning mere AI prompt use should not automatically confer authorship unless there is meaningful human input.

The text also highlights ongoing debates about whether AI training qualifies as fair dealing, noting that large-scale commercial training does not clearly fit existing exceptions. Comparative legal examples, such as U.S. copyright guidance and cases like Thomson Reuters v. Ross Intelligence, show increasing concern about market substitution when AI systems replicate or replace original works. Indian cases like ANI Media v. OpenAI further illustrate emerging legal disputes around AI training and output misuse.

Conclusion

Generative AI does not make copyright obsolete. It tests whether copyright can remain faithful to its purpose in a new technological environment. Indian law should protect human creativity, encourage innovation and prevent unfair appropriation of expressive labour. The Copyright Act, 1957 already supplies important starting points: originality, authorship, economic rights, fair dealing and remedies. But those tools need AI-specific interpretation. The most workable Indian approach is human-centred and market-sensitive. AI-assisted works should be protected only to the extent of human creative contribution. AI outputs that reproduce protected expression should be treated as infringing regardless of the machine\'s role. Training should be assessed by purpose, scale, commerciality, market effect, availability of licences and safeguards. This balance would allow India to support technological progress while respecting the labour of writers, artists, journalists, musicians, performers and other creators.

References

[1] Ryan Abbott, The Reasonable Robot: Artificial Intelligence and the Law (Cambridge Univ. Press 2020). [2] Research Handbook on Intellectual Property and Artificial Intelligence (Ryan Abbott ed., Edward Elgar Publishing 2022). [3] Lawrence Lessig, Free Culture: How Big Media Uses Technology and the Law to Lock Down Culture and Control Creativity (Penguin Press 2004). [4] Jane C. Ginsburg & Luke Ali Budiardjo, Authors and Machines, 34 Berkeley Tech. L.J. 343 (2019). [5] Pamela Samuelson, Generative AI Meets Copyright, 381 Science 158 (2023). [6] Annemarie Bridy, Coding Creativity: Copyright and the Artificially Intelligent Author, 5 Stan. Tech. L. Rev. 1 (2012). [7] Shlomit Yanisky-Ravid & Luis Antonio Velez-Hernandez, Copyrightability of Artworks Produced by Creative Robots and Originality: The Formality-Objective Model, 19 Minn. J.L. Sci. & Tech. 1 (2018). [8] Andres Guadamuz, A Scanner Darkly: Copyright Liability and Exceptions in Artificial Intelligence Inputs and Outputs, 73 GRUR Int’l 111 (2024). [9] Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley & Percy Liang, Foundation Models and Fair Use, 24 J. Mach. Learning Rsch. 1 (2023). [10] U.S. Copyright Office, Copyright and Artificial Intelligence, Part 2: Copyrightability (2025).

Copyright

Copyright © 2026 Ms. Vijaishree Tiwari, Dr. Nilesh Verma. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.