IRCI Article ID: IRCI-AR-0000003202

Generative Artificial Intelligence and Intellectual Property Rights: A Comparative Analysis of Copyright, Patents and Trade Secrets

Journal: Trends in Intellectual Property Research

Publication: 2026-08-04 · Vol. 4 No. 3 · pp. 27–33

DOI: 10.69971/tipr.4.3.2026.138

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Abstract

The unprecedented development of generative artificial intelligence (GenAI) has fundamentally transformed the global intellectual property (IP) landscape. Unlike previous technological innovations, modern large language models (LLMs) and multimodal AI systems are capable of autonomously generating literary works, software code, music, images, inventions and commercially valuable information that increasingly resemble products of human creativity. These developments challenge traditional concepts of authorship, inventorship, ownership and confidentiality, requiring legislators and courts to reconsider long-established legal doctrines. This article examines the evolving relationship between artificial intelligence and intellectual property rights through a comparative legal analysis of copyright, patent law and trade secret protection. Particular attention is devoted to the regulatory approaches adopted by the European Union, the United States, the United Kingdom, China, Japan and Singapore. The research evaluates recent legislative initiatives, judicial decisions and policy documents adopted between 2024 and 2026, including the implementation of the European Union AI Act, developments within the World Intellectual Property Organization (WIPO), the OECD and leading national intellectual property offices. The paper argues that contemporary intellectual property systems are experiencing a transition from human-centred protection towards hybrid governance models that increasingly recognize the role of AI-assisted creativity while preserving human responsibility. The article proposes a balanced regulatory framework that distinguishes between AI-generated and AI-assisted outputs, strengthens transparency obligations concerning training data, enhances protection of confidential business information and promotes international harmonization of intellectual property rules in the era of generative AI.

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Authors

Begaim Mukhitovna Kaibyldaeva

Affiliation: Central Asian Association for Artificial Intelligence (AICA), IT-Park, Tashkent, Uzbekistan

Anna Vladimirovna Ubaydullaeva

Affiliation: Tashkent State University of Law

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