<![CDATA[Antimicrobial resistance (AMR) is a growing global health threat. Artificial Intelligence (AI) offers innovative approaches to the detection, prediction, and management of resistance through advanced data analysis. This study aims to map the research landscape of AI utilisation in AMR for the period 2015–2025 through bibliometric analysis. A search on PubMed (4 September 2025) yielded 2,078 documents (1996–2025), and after applying year restrictions, 2,009 articles were analysed. The total output of countries reached 11,943 publications, with China (5,570), the United States (2,896), and India (755) as the main contributors. Four thematic clusters were identified: machine learning, bacterial resistance, deep learning, and antimicrobial stewardship. The results showed a sharp increase in publications until 2025, with the journals Antibiotics, Frontiers in Microbiology, and Scientific Reports dominating. The study confirmed the important role of AI in supporting resistance detection and precision medicine, but challenges such as data limitations, algorithmic bias, and global research inequality still require attention.]]>
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