The Impact of Generative Artificial Intelligence on Copyright Law and Intellectual Property Protection

The rapid advancement of generative artificial intelligence (GAI) has precipitated a fundamental paradigm shift in intellectual property (IP) law, challenging established doctrines of authorship, ownership, and fair use. This comprehensive review examines the evolving legal landscape surrounding GAI through judicial interpretations, comparative regulatory frameworks, emerging IP frontiers, technical protection mechanisms, and market dynamics. The analysis reveals a critical bifurcation in legal treatment between the inputs stage where courts distinguish between lawfully acquired and pirated training data and the outputs stage, which raises complex questions about copyright eligibility for GAI-generated works. Landmark U.S. litigation, including Bartz v. Anthropic, Kadrey v. Meta, and The New York Times v. OpenAI, establishes that while transformative fair use may protect lawful data ingestion, unauthorized scraping from shadow libraries constitutes direct infringement, evidenced by substantial settlements. The Supreme Court's denial of certiorari in Thaler v. Perlmutter reaffirms human authorship as a constitutional prerequisite for copyright protection, though international jurisdictions demonstrate divergent approaches, from China's recognition of prompt-based creativity to the EU's comprehensive AI Act transparency mandates. Emerging challenges in Retrieval-Augmented Generation (RAG) systems, trademark dilution, and patent inventorship further complicate the regulatory environment. Technical solutions, including provenance standards (C2PA), forensic watermarking (SynthID), and adversarial tools (Glaze, Nightshade), offer complementary enforcement mechanisms. The accelerating transition from litigation to structured data licensing valued at tens of millions annually signals a market-driven resolution to the training data crisis. This review concludes that sustainable GAI development requires balancing technological scaling with robust creator compensation and legal protection.