Artificial intelligence and antimicrobial stewardship: From clinical decision support to public health action-On behalf of APUA
Abstract
BACKGROUND: Antimicrobial resistance 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 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 low- and middle-income countries 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 antimicrobial resistance control. Sustained human leadership, equity-focused deployment, and health system strengthening remain essential.
Related
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- Impact of Pharmacist-Involved Antimicrobial Stewardship Interventions on Clinical and Process Outcomes in Multidrug-Resistant Organism Infections: A Systematic Review and Meta-Analysis.
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- Whether, or under what conditions? A configurational approach to AI-supported antimicrobial stewardship in sub-Saharan Africa
- Mapping antimicrobial stewardship principles in HIV positive patients in sub-Saharan Africa: a systematic scoping review protocol
BibTeX
@article{ghafur2026artificial,
title = {{Artificial intelligence and antimicrobial stewardship: From clinical decision support to public health action-On behalf of APUA}},
author = {Abdul Ghafur and Miki Nagao and Souha S. Kanj and Salam Abbara and Pierre Tattevin and Mariette Awad and Maya Dagher and Linus K Ndegwa and Gathai Mundia and Jeroen Schouten and Huong T L Vu and Gabriel Levy-Hara and Maneesh Paul Satyaseela and Mamoon A Aldeyab and Raksha K Bhat and Nitin Bansal and Heiman F.L. Wertheim},
journal = {Journal of Global Antimicrobial Resistance},
year = {2026},
month = sep,
doi = {10.1016/j.jgar.2026.08.003},
url = {https://hal.science/hal-05772030v1},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Artificial intelligence and antimicrobial stewardship: From clinical decision support to public health action-On behalf of APUA
AU - Abdul Ghafur
AU - Miki Nagao
AU - Souha S. Kanj
AU - Salam Abbara
AU - Pierre Tattevin
AU - Mariette Awad
AU - Maya Dagher
AU - Linus K Ndegwa
AU - Gathai Mundia
AU - Jeroen Schouten
AU - Huong T L Vu
AU - Gabriel Levy-Hara
AU - Maneesh Paul Satyaseela
AU - Mamoon A Aldeyab
AU - Raksha K Bhat
AU - Nitin Bansal
AU - Heiman F.L. Wertheim
PY - 2026
DA - 2026/09/30
JO - Journal of Global Antimicrobial Resistance
DO - 10.1016/j.jgar.2026.08.003
UR - https://hal.science/hal-05772030v1
AB - BACKGROUND: Antimicrobial resistance 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 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 low- and middle-income countries 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 antimicrobial resistance control. Sustained human leadership, equity-focused deployment, and health system strengthening remain essential.
SN - 2213-7165
SN - 2213-7173
ER -