From Enhancing Individual to Team Capacities: Stakeholders’ Insights on Generative-AI and Digital-Twin Adoption in Surgery

Abstract

This paper distills insights from two three-hour workshops involving 34 multidisciplinary participants that explored the individual and collective applications of generative AI (GenAI) and digital twins (DTs) in surgery. Participants began by clarifying the meaning of GenAI and DTs in surgical contexts. GenAI was perceived as an individual aid to generate clinical notes, referral letters, and explanations to patients, while DTs were praised to render patient-specific anatomy, forecast trocar placement, and provide teams a live common operating-room view. Together the technologies create a layered data infrastructure that toggles between solo efficiency and collective sense-making. Participants highlighted adoption challenges such as ethical considerations, data accuracy, and infrastructural readiness. Design imperatives emerge for a nuanced integration of these technologies into surgical practices, such as modeling uncertainty, preserving clinical reasoning, and introducing tools through existing hospital systems, highlighting the essential role of human-computer interaction experts.