Future-Ready Anaesthesia: Negotiating the Intersection of Smart Technology, AI, and Clinical Decision Support

Abstract

Key Points • Artificial intelligence (AI) is increasingly integrated into perioperative and critical care medicine • AI should be viewed as a form of augmented intelligence that complements, rather than replaces, clinician expertise. • Current applications span the entire perioperative continuum, includingpreoperative risk stratification, intraoperative haedmodynamic prediction, automated drug delivery and critical care analytics. • Despite promising results, AI systems require rigorous external validation, ongoing monitoring and careful assessment of generalizability across different patient populations. • Challenges include algorithm bias, AI hallucinations, alert fatigure, workflow integration, cybersecurity concerns and medico legal uncertainty • Most regulatory authorities continue to emphasise that AI systems should function as decision support tools, rather than autonomous decision makers. • In Malaysia, cost remains one of the most significant challenges in the implementation of AI systems. • Education and research represent two areas in which AI may profoundly reshape the future of anesthesiology • Future-ready anaesthetist will require competencies in AI literacy, data interpretation and critical appraisal to ensure safe and effective implementation