How ready are we to use artificial intelligence in our fight against antimicrobial resistance? An ESGAID and EAAS perspective
AI offers unprecedented opportunities across the continuum of our efforts to counteract AMR, yet its adoption faces substantial hurdles. Some central challenges include the balance between model accuracy and explainability, the lack of widespread digital access, quality and transparency of training datasets, and usability for clinicians. Progress will depend on multidisciplinary collaboration, robust regulatory oversight, and the development of training programs equipping future healthcare professionals with AI-aware reasoning skills. Ultimately, AI should not replace but rather augment human reasoning in the fight against AMR, aligning innovation with ethical principles to ensure safer, more equitable AI-enhanced antibiotic prescribing and antimicrobial stewardship.
Authors
- Bruno Silvester Lopes (ORCID: https://orcid.org/0000-0002-1476-2108)
- Valentijn A. Schweitzer (ORCID: https://orcid.org/0000-0001-9640-7291)
- Holger Rohde
- Alejandro Guerrero-López (ORCID: https://orcid.org/0000-0001-8869-3363)
- C García-Vidal
- Alberto Rizzo (ORCID: https://orcid.org/0000-0001-5999-006X)
- Ermira Tartari (ORCID: https://orcid.org/0000-0002-9791-644X)
- AbdulAziz Ascandari
- Zahra Sadeghi (ORCID: https://orcid.org/0000-0002-1360-7499)
- Ekaterina Lyutsova (ORCID: https://orcid.org/0000-0001-7692-3934)
- Antonio Gallardo-Pizarro
- Rafi Ahmad
- Fatih Mehmet Akilli
- David W. Eyre
- Daniele Roberto Giacobbe
- Ruslan Rakhimov
- Eva Torres-Sangiao
- on behalf of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group on Artificial Intelligence and Digitalisation (ESGAID) and the ESCMID Antimicrobial Resistance (AMR) Action Subcommittee (EAAS)
Institutions
- ActionAid (US)
- Medical University of Varna (BG)
- Universität Hamburg (DE)
- University of Malta (MT)
- University of Zurich (CH)
- University Medical Center Utrecht (NL)
- National Institute for Health and Care Research (GB)
- University of Oxford (GB)
- Centre for Arctic Gas Hydrate, Environment and Climate (NO)
- University Medical Center Hamburg-Eppendorf (DE)
- Tashkent State University of Law (UZ)
- Hospital Clínic de Barcelona (ES)
- University of Inland Norway (NO)
- The Polytechnic University of Japan (JP)
- Azienda Ospedaliera S.Maria (IT)
- Université Mohammed VI Polytechnique (MA)
- Oxford University Hospitals NHS Trust (GB)
- ASST Fatebenefratelli Sacco (IT)
- Instituto de Investigación Biomédica de A Coruña (ES)
- Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES)
- Tashkent Pediatric Medical Institute (UZ)
- Artificial Intelligence in Medicine (Canada) (CA)
- Complejo Hospitalario Universitario de Ferrol (ES)
- Tashkent State University of Economics (UZ)
- Tehran University of Medical Sciences (IR)
- Universitat de Barcelona (ES)
- UiT The Arctic University of Norway (NO)
- University of Genoa (IT)
- Teesside University (GB)
Publication Details
- Journal
- Expert Review of Anti-infective Therapy
- Published
- 2026-01-02
- DOI
- https://doi.org/10.1080/14787210.2026.2625382
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 17.70