Artificial Intelligence in Intellectual Property Rights: Opportunities and challenges for Traditional Medicine

ABSTRACT: As Traditional Medicine (TM) systems become increasingly digitized, the potential for Artificial Intelligence (AI)-driven mechanisms for Intellectual Property Rights (IPR) protection grows but so does its vulnerability to digital biopiracy. AI technologies such as natural language processing, machine learning, cheminformatics, and real-time surveillance are applied to prior art searches, semantic comparisons, and patent-landscape monitoring. India’s Traditional Knowledge Digital Library (TKDL) and the Indian Medicinal Plants, Phytochemistry And Therapeutics database (IMPPAT), China’s digitization of Traditional Chinese Medicine (TCM), and regional initiatives such as the Virtual Health Library (VHL) for TM exemplify both opportunities and risks of digital infrastructures. While AI enhances prior art validation, strengthens defensive IPR, and facilitates evidence-based drug discovery, it simultaneously exposes repositories to exploitation through bioinformatics-driven misappropriation. This commentary presents a balanced governance framework for AI in TM, emphasizing strong regulation, ethical oversight, and community consent.