Intellectual Property Rights In The Age Of Digital Platforms And Generative Artificial Intelligence: A Comparative Case Study Of Ownership, Enforcement, And Creative Control

Abstract

The rapid development of digital platforms and generative artificial intelligence has fundamentally altered the environment in which intellectual property is created, distributed, commercialised, and enforced. Traditional intellectual property frameworks were developed around comparatively identifiable relationships between creators, intermediaries, and consumers. Digital platforms have disrupted these relationships by enabling instantaneous global distribution, algorithmic recommendation, collaborative creation, automated reproduction, and machine-assisted generation of creative works. These developments have created significant opportunities for innovation while simultaneously generating difficult questions concerning ownership, authorship, infringement, licensing, contractual control, and access.

This article examines these challenges through a fictional comparative case-study framework involving three digital enterprises operating in the fields of online publishing, collaborative software development, and generative artificial intelligence. The first case examines alleged unauthorised reproduction of copyrighted publications by a digital content platform. The second considers ownership and licensing disputes arising from software developed through an international digital marketplace. The third examines authorship and commercial rights in AI-assisted visual design. In addition to the qualitative case analysis, the study presents fictional comparative data illustrating patterns of intellectual property disputes, platform responses, resolution mechanisms, and stakeholder perceptions.

The findings indicate that digital intellectual property disputes increasingly involve overlapping legal and commercial interests rather than isolated claims of infringement. Platform architecture, contractual design, technological safeguards, and algorithmic decision-making can materially influence the allocation of intellectual property rights. The study further suggests that conventional ownership-based approaches may be insufficient where creative production involves multiple human and technological contributors. A platform-sensitive governance framework based on transparent ownership, provenance, proportional enforcement, procedural fairness, and public-interest safeguards is consequently proposed.