Artificial intelligence in trauma and emergency surgery: A quantitative study of perceived technology acceptance

Artificial Intelligence (AI) is a transformative technology capable of driving the United Nations Sustainable Development Goals (SDGs) implementation across various industries. It can play a crucial role in the healthcare sector, especially in highly specialized fields such as trauma and emergency surgery, where its potential to assist in clinical decision-making is gaining widespread recognition. When appropriately designed and governed, AI applications in surgery can contribute to SDG 3 by improving health outcomes and promoting well-being. Moreover, clearly defined accountability and responsibility frameworks for AI in healthcare support SDG 16 by enabling auditability, clarifying responsibility allocation, and fostering institutional trust through transparent governance mechanisms. Despite these opportunities, ethical and governance-related concerns remain central to AI adoption and significantly shape the attitudes of medical professionals, patients, technology providers, developers, and policymakers. This exploratory study investigates surgeons' perceptions regarding AI adoption through a framework informed by the Unified Theory of Acceptance and Use of Technology (UTAUT). While grounded in UTAUT, the study incorporates context-specific constructs that capture the unique challenges of surgical practice: performance expectancy, perceived diagnostic complexity, patient-centered communication orientation, responsible AI governance climate, and shared accountability perceptions. By examining how responsibility interacts with traditional UTAUT constructs, performance expectancy, effort expectancy, social influence, and facilitating conditions, this research offers a more context-sensitive understanding of AI adoption in high-stakes medical environments. Through a comprehensive survey endorsed by the World Society of Emergency Surgery (WSES), involving 624 physicians from 72 countries, we aim to highlight these concerns and propose a conceptual model that reconciles AI's technological advances with the ethical obligations to protect patients and ensure sustainable healthcare outcomes.