Published Paper Details:

Ayurveda, one of the oldest holistic medical sciences, is gaining renewed global relevance in the 21st century. However, its reliance on practitioner-dependent, subjective diagnostic methods has hindered its scalability and international acceptance. This review provides a chronological literature survey of Artificial Intelligence (AI) integration into Ayurveda, examining developments from conceptual frameworks to modern research automation. Beginning with pre-2015 feasibility studies and the emergence of Ayurgenomics, the paper traces the evolution of AI applications in Prakriti classification, Vikriti quantification, therapeutic personalization, and drug discovery. Further, it highlights emerging technologies such as Agent-Based AI Systems (AAIS) and predictive health analytics that promise to redefine Ayurveda as a global, data-driven science. Critical challenges--including data scarcity, model interpretability, and ethical governance--are also analyzed. The review concludes that the fusion of Ayurveda and AI, termed "Ayurveda Intelligence," represents not just modernization but a paradigm shift in healthcare delivery and research automation.