How ready are we to use artificial intelligence in our fight against antimicrobial resistance?: An ESGAID and EAAS perspective

Abstract

INTRODUCTION: Antimicrobial resistance (AMR) remains one of the greatest threats to global health, requiring innovative approaches to antibiotic discovery, surveillance, diagnosis, and prescribing. In recent years, artificial intelligence (AI) has increasingly been applied across these domains, with the dual aim of accelerating research and strengthening antimicrobial stewardship. AREAS COVERED: This perspective summarizes current advances and challenges in applying AI for tackling AMR. We examine the role of AI in antibiotic discovery, laboratory surveillance, diagnosis of resistant infections, and clinical decision support systems. Finally, we address the ethical and regulatory landscape, data transparency, and liability concerns. EXPERT OPINION: 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.