Artificial intelligence in perioperative medicine: navigating the temporogram of integration (a perspective)

The integration of artificial intelligence (AI) into perioperative medicine signals a paradigm shift with the potential to transform clinical workflows, support anesthetic decision-making, and affect public health. As a scholarly perspective, this article discusses how AI’s transition from a theoretical concept to a practical tool in the operating room introduces both unprecedented opportunities and profound risks. These include new forms of error, moral ambiguities, data system complexities, and medico-legal uncertainty. To structure this complexity, we introduce a temporogram—a conceptual, chronological map of the key stages and domains involved in integrating AI into perioperative care. We outline this trajectory beginning with knowledge acquisition, where digital fluency and electronic health record (EHR) readiness are paramount. We address the critical need for human oversight to counteract algorithmic drift and the absence of an AI “moral compass.” Financial and implementation considerations encompass capital costs, data lag, and productivity impacts. In the intraoperative setting, AI-enabled decision support could help reduce selected errors, but introduces risks of blind trust and decision fatigue. Furthermore, we discuss how AI-driven risk stratification may support personalized anesthetic management, provided that training data is inclusive, and how these efficiencies might translate to public health advancements. Integrating AI into perioperative medicine is a dynamic, multi-step process. Our temporogram offers a forward-looking roadmap for institutional preparedness and governance. Realizing AI’s potential—while acknowledging the irreplaceable value of human empathy, lived clinical experience, and ethical oversight—requires intentional leadership and continuous validation.