Tehran University of Medical Sciences Archives of Anesthesiology and Critical Care 2423-5849 11 2 2024 11 12 218 223 Shahnam Sedigh Maroufi Department of Anesthesia, Faculty of Allied Medical Sciences, Iran University of Medical Sciences, Tehran, Iran. Maryam Sarkhosh Department of Anesthesia, Faculty of Allied Medical Sciences, Iran University of Medical Sciences, Tehran, Iran. Maryam Soleimani Movahed Education Development Center, Iran University of Medical Sciences, Tehran, Iran. Ali Behmanesh Education Development Center, Iran University of Medical Sciences, Tehran, Iran. Azar Ejmalian Department of Anesthesiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. 2024 06 08 2024 07 01 Artificial intelligence (AI) is increasingly being utilized in Post-Anesthesia Care Units (PACUs) to improve patient monitoring and care. This narrative review explores the current use of AI in PACUs and discusses the potential benefits and challenges associated with its implementation and highlights how AI technologies such as predictive analytics, machine learning algorithms, and robotics can enhance patient safety, reduce human error, and improve outcomes in the PACU setting. Overall, this narrative review provides insights into the evolving role of AI in PACUs and offers recommendations for future research and practice in this area. https://aacc.tums.ac.ir/index.php/aacc/article/view/1022