Artificial intelligence and precision nursing in the operating room: transforming perioperative safety and surgical outcomes

Background: The operating room represents a high-risk clinical environment where perioperative nurses play a critical role in patient safety, workflow coordination, and surgical outcomes. Recent advances in artificial intelligence (AI) and precision health technologies offer new opportunities to enhance perioperative nursing practice; however, the scope, maturity, and clinical relevance of these applications remain heterogeneous. Objective: This scoping review aimed to map existing evidence on the integration of AI and precision nursing in perioperative and operating room settings, with a focus on nursing roles, clinical applications, outcomes, and implementation challenges. Methods: A scoping review was conducted in accordance with PRISMA-ScR guidelines. A systematic search of PubMed/MEDLINE, Scopus, Web of Science, and CINAHL was performed for studies published between January 2010 and March 2025. Eligible studies examined AI-enabled or technologies relevant to perioperative nursing practice across the preoperative, intraoperative, and postoperative phases. Data were descriptively charted and synthesized to identify key application domains, evidence levels, and research gaps. Results: A total of 72 studies met the inclusion criteria. The AI applications identified included predictive analytics for perioperative risk stratification, real-time intraoperative monitoring and decision support, computer-vision-based workflow and sterility surveillance, automated documentation, robotic assistance, and postoperative remote monitoring. Evidence suggests potential benefits in early complication detection, workflow efficiency, and support for nursing decision-making. However, most studies were pilot or observational in nature, with limited large-scale clinical validation. Ethical considerations, data governance, workforce readiness, and integration into nursing workflows emerged as recurring challenges. Conclusion: AI-enabled precision nursing represents a promising approach to enhancing perioperative safety and surgical outcomes. Current evidence supports AI as a complementary tool that augments, rather than replaces, clinical judgment and nursing expertise. Further high-quality nursing-focused research, standardized evaluation frameworks, and ethically grounded implementation strategies are required to support safe and sustainable integration into perioperative practice.