Artificial Intelligence as the Ultimate Operative Assistant

Abstract Artificial intelligence (AI) is poised to become transformational in many aspects of modern society and has attracted significant interest within the field of medicine. This review outlines the foundational components of modern AI such as including machine learning, deep learning, natural language processing, computer vision, and generative modeling, and examines their emerging applications within surgery. In the preoperative domain, AI-driven risk stratification models inform patient selection and resource allocation, while parallel advances in deep learning-enabled anatomic segmentation and three-dimensional reconstruction have the potential to streamline surgical planning by automating labor-intensive imaging workflows. Intraoperatively, maturing capabilities in phase recognition, anatomic identification, augmented reality overlay, and real-time decision support demonstrate the possibility for improved safety, workflow efficiency, and early recognition of surgical and physiologic challenges. And although the first fully autonomous AI-driven surgical robot in humans is likely still far off, the recent advances in robotic surgery suggest this may no longer be the purview of science fiction. For all its promise, significant challenges still persist for the robust implementation of AI into surgical workflows regarding data governance, algorithmic transparency, regulatory oversight, model generalizability, and, especially, many philosophical and ethical questions that remain unanswered.