Nursing leadership and performance metrics in artificial intelligence integrated gastrointestinal surgical care: A narrative review

Artificial intelligence (AI) is increasingly being integrated into gastrointestinal and complex surgical care, yet its practical impact on nursing work remains insufficiently defined.This narrative review examines how nursing leadership can support the safe use of AI across perioperative pathways and how its effects can be evaluated through measurable nursing-sensitive outcomes.Literature was identified through PubMed, Scopus, and Web of Science, with emphasis on peer-reviewed studies, systematic reviews, guidelines, consensus statements, and implementation frameworks relevant to gastrointestinal surgery, perioperative nursing, clinical decision support, and AI.The review focuses on preoperative assessment, intraoperative coordination, postoperative surveillance, and discharge planning in high-acuity surgical settings.Particular attention is given to workflow efficiency, response times, early recognition of complications, risk-stratified care, documentation quality, interdisciplinary communication, cognitive workload, and patient safety.The proposed framework is intended as a practical, non-validated structure for future evaluation rather than as an established measurement instrument.Its use will require prospective validation and adaptation to local staffing, digital infrastructure, resources, and clinical workflows.AI should therefore be judged not only by predictive performance, but by whether it helps nurses recognize risk earlier, communicate concerns clearly, and deliver safer perioperative care.