Impact of Closed-Loop Technology, Machine Learning, and Artificial Intelligence on Patient Safety and the Future of Anesthesia

Purpose of Review The purpose of the present narrative review is to look at the present and future impact of closed-loop technology, artificial intelligence (AI), and machine learning (ML) on anesthesia and patient safety. Recent Findings AI and ML are omnipresent and encountered daily without one’s awareness. More and more promising AI-guided tools are being developed to help anesthesiologists provide better patient care. Some of these applications are already at par or outperforming clinicians in concrete tasks, although significant work is still needed for their effective and safe integration into clinical practice. Additionally, major ethical and legal questions need to be addressed before such algorithms can become mainstream. Summary Despite the challenges ahead, the implementation of AI-driven technologies has significant potential to positively complement modern anesthesia care, and as such, significantly improve patient safety.