Howard A.Reza N.Green P.L.Yin M.Duffy E.Mwandumba H.C.Gerada A.Hope W.Mahidol University2025-10-162025-10-162025-01-01Lancet Infectious Diseases (2025)14733099https://repository.li.mahidol.ac.th/handle/123456789/112614Antimicrobial resistance (AMR) is an intractable problem that has the potential to significantly limit advances in human health. Recently, the UN General Assembly (UNGA) High-Level Statement on AMR defined targets for addressing the impact of resistance on human, animal, and environmental health. For human health, the discovery and development of new antibiotics, antimicrobial stewardship programmes, antimicrobial surveillance, and infection control and prevention are all key areas. Artificial intelligence (AI) is ideally placed to help achieve the UNGA targets via its role in revealing patterns in data that are clinically indiscernible, and using that information to build clinical decision support systems. However, significant barriers remain in terms of necessary infrastructure, know-how, and the implementation of AI approaches. In this Series paper, we consider the potential applications of AI in combatting the AMR problem through drug discovery and development, antimicrobial stewardship, diagnostics, and surveillance, and their use in public health. We then discuss the technical, infrastructure, regulatory, ethical, and policy challenges that affect these domains.MedicineReviewSCOPUS10.1016/S1473-3099(25)00313-52-s2.0-1050181114171474445740972630