Evaluation of the Efficiency of Artificial Intelligence in Transforming Anesthesia Practice and Perioperative Management

Artificial Intelligence (AI) has emerged as a transformative force in modern anesthesiology and perioperative medicine, offering enhanced precision, efficiency, and patient safety. This study evaluates the efficiency of AI applications in anesthesia and perioperative management, emphasizing machine learning (ML) algorithms, predictive analytics, and real-time monitoring systems. By integrating evidence from recent literature, the research highlights how AI-driven innovations have revolutionized clinical decision-making, patient risk stratification, and postoperative recovery outcomes. Despite promising advancements, challenges such as data integrity, algorithmic transparency, and ethical considerations persist, underscoring the need for standardized frameworks and interdisciplinary collaboration for sustainable AI adoption in anesthesia practice. The study conclude that it must be rigorously evaluated in terms of clinical outcomes, workflow integration, and cost-effectiveness, while also accounting for ethical, legal, and professional implications. It also recommended that AI algorithms must be interpretable and transparent to maintain accountability in critical care environments. Ethical frameworks should guide data usage, privacy protection, and bias mitigation in perioperative decision-making.