Artificial Intelligence-Enabled Ayurveda: Integrating Ancient Wisdom with Modern Data ScienceArtificial intelligence has moved, in the span of a few short years, from an experimental curiosity to a force actively reshaping how healthcare is delivered, taught, and researched. Ayurveda, one of the world's oldest continuously practised systems of medicine, now stands at a compelling crossroads with this technology. This volume brings together scholars, clinicians, and educators who are asking a shared question from different vantage points: how can the classical wisdom embedded in Prakriti, Vikriti, Agni, Srotas, and centuries of clinical reasoning be understood, structured, and strengthened through computational tools without losing what makes it distinct? The chapters that follow reflect the breadth of this inquiry. Readers will find discussions of digital health platforms and smart Ayurveda clinics, AI-enabled teaching and learning, the digitisation and mining of classical texts, competency-based educational transformation, and the application of AI in clinical research. Later chapters turn to pharmacology and Dravyaguna in the computational age, methodological applications for literature review, and the ethical and regulatory questions that any responsible integration of AI into traditional medicine must confront. What unites these contributions is not a single technical approach but a shared conviction: that digital transformation in Ayurveda should be undertaken thoughtfully, with attention to semantic interoperability, clinical validity, governance, and the wellbeing of patients, rather than as a superficial overlay of modern tools onto an ancient system. Several chapters propose phased frameworks and practical roadmaps precisely because the editors believe this transition deserves careful, evidence-informed implementation rather than haste. We are grateful to the contributing authors for the depth and care evident in their work, and we hope this collection serves students, clinicians, researchers, and policymakers alike as both a reference and an invitation to further inquiry. The conversation between ancient wisdom and modern data science is only beginning, and this book is offered as one contribution to that ongoing dialogue. |
