Abstract

Artificial intelligence (AI) is rapidly transforming digital healthcare, particularly in diagnostic systems such as radiology and clinical decision support. However, this progress has exposed significant gaps in existing intellectual property (IP) and regulatory frameworks, which were not designed for AI-driven innovation. This paper examines key challenges including inventorship, data ownership, algorithmic transparency, and regulatory fragmentation. A comparative analysis of global legal frameworks, such as the EU AI Act (2024), Council of Europe AI Convention (2024), and US FDA Software as a Medical Device (SaMD) guidelines is presented, along with selected judicial case studies that highlight evolving approaches to accountability in AI-assisted diagnostics. In addition, statistical trends from the past six years are analysed to demonstrate the rapid growth and adoption of AI in healthcare. The paper further explores future developments, including explainable AI and autonomous diagnostic systems, and emphasizes the need for harmonized global IP policies. It concludes that adaptive regulatory frameworks are essential to ensure both innovation and equitable access in AI-driven healthcare.

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