Artificial Intelligence and Antimicrobial Stewardship: From Clinical Decision Support to Public Health Action.
TL;DR
AI should be viewed as a decision-support tool that augments, rather than replaces, AMS expertise and when implemented responsibly within robust governance frameworks and aligned with AMS principles, AI can contribute meaningfully to improved antimicrobial use and AMR control.
Abstract
Background
Antimicrobial resistance (AMR) continues to threaten the effectiveness of modern medicine and poses major public health challenges worldwide. Antimicrobial stewardship (AMS) programmes are essential to mitigate inappropriate antimicrobial use but are often resource-intensive and difficult to sustain. Advances in artificial intelligence (AI) have generated interest in its potential to support stewardship activities across clinical, operational, and public health domains.
Objectives
To critically review the current and emerging roles of AI in AMS, and to examine its opportunities, limitations, and implications for clinical practice, public health, and health systems globally.
Methods
We conducted a narrative review of the literature on AI applications relevant to AMS, including diagnostic support, antimicrobial prescribing, behavioural and implementation science, infection prevention, surveillance, One Health approaches, drug discovery, and governance. Particular attention was paid to ethical considerations, human oversight, and applicability in low- and middle-income country (LMIC) settings.
Results
AI has demonstrated potential to enhance diagnostic precision, support clinical decision-making, optimise antimicrobial use, strengthen surveillance systems, and inform targeted stewardship interventions. However, challenges related to data quality, bias, interpretability, workflow integration, ethical governance, and equity remain significant. AI systems developed in high-income settings may not be directly transferable to LMICs without careful adaptation and local validation.
Conclusions
AI should be viewed as a decision-support tool that augments, rather than replaces, AMS expertise. When implemented responsibly within robust governance frameworks and aligned with AMS principles, AI can contribute meaningfully to improved antimicrobial use and AMR control. Sustained human leadership, equity-focused deployment, and health system strengthening remain essential.