Abstract

The rapid ascent of generative artificial intelligence (AI) systems has fundamentally disrupted the contours of copyright law. Tools capable of autonomously producing text, images, music, and code challenge traditional notions of authorship, originality, and ownership—concepts that form the core of intellectual property frameworks. This research critically explores the intersection of copyright law and generative AI, with a focus on evolving legal definitions, jurisdictional responses, and policy dilemmas. By tracing the historical evolution of copyright from its human-centric origins to the digital age, the paper establishes a foundation for analyzing the legal vacuum surrounding AI-generated content. It examines core legal challenges, including authorship attribution, liability for infringement, and the use of copyrighted material in AI training datasets. Case law developments from jurisdictions such as the United States, European Union, and India are analyzed to understand the current legal stance and the judiciary's resistance to non-human authorship claims. Particular attention is paid to the fair use doctrine and its applicability to the training of AI models using protected works. The research concludes by proposing a multifaceted reform agenda—incorporating sui generis protections, licensing mechanisms, attribution norms, and international harmonization—to ensure a balanced copyright regime that safeguards creators' rights without stifling technological progress. The study ultimately contends that the future of copyright law lies not in rejecting the rise of generative AI, but in reshaping the legal scaffolding to ensure it evolves responsibly and inclusively alongside innovation.

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