Antimicrobial resistance (AMR) poses a formidable threat to public health in India, requiring a multidimensional response that bridges policy, innovation, and intersectoral collaborations. The rapid emergence and spread of multidrug-resistant pathogens driven by the misuse of antimicrobials in human health, animal health, agriculture, and environmental settings has rendered many existing therapies obsolete, leaving the population vulnerable to untreatable infections. To examine the multifactorial drivers of AMR in India, review current national and state-level policies, and explore the potential role of Artificial Intelligence (AI) in AMR surveillance, prevention, and control. This review synthesizes evidence from published literature, reports, and policy documents. It analyses AMR determinants across human, animal, and environmental sectors, evaluates policy frameworks such as India's National Action Plan, and State Action Plans to combat AMR. Key AMR drivers include antibiotic misuse, inadequate regulation, over-the-counter availability, pharmaceutical and hospital wastewater contamination, and gaps in infection prevention. India has come up with national and six state level action plans for AMR containment. The measures include stewardship programs, laboratory network strengthening, spreading awareness and intersectoral coordination. The role of AI in strengthening AMR surveillance and clinical decision-making by integrating complex, high-dimensional data for predictive modeling has been explored. While India has made significant policy and surveillance advances, enforcement gaps, limited awareness, and fragmented data hinder progress. Strengthening governance, expanding One Health surveillance, integrating AI, and embedding AMR strategies into universal health coverage are critical to mitigating AMR's health and economic burden.