Abstract
Artificial intelligence has emerged as one of the most transformative technologies in modern anesthesiology and critical care medicine. Rapid advances in machine learning, deep learning, computer vision, natural language processing, and predictive analytics have enabled AI to support clinical decision-making throughout the perioperative and intensive care continuum. AI-based systems are increasingly used for preoperative risk stratification, difficult airway prediction, ultrasound-guided regional anesthesia, automated anesthetic drug delivery, depth of anesthesia monitoring, hemodynamic optimization, early sepsis detection, mechanical ventilation management, and prediction of intensive care unit mortality. These technologies improve diagnostic accuracy, facilitate individualized treatment strategies, reduce human error, and optimize resource utilization while enhancing patient safety. Despite these advances, significant challenges remain regarding algorithm transparency, external validation, data quality, cybersecurity, legal liability, and ethical implementation. Future developments integrating explainable artificial intelligence, multimodal data analysis, digital twins, federated learning, and precision medicine are expected to transform perioperative and critical care practice. This review summarizes current evidence regarding AI applications in anesthesiology and intensive care, discusses existing limitations, and highlights future perspectives for safe and effective clinical implementation.