Artificial intelligence in ultrasound-guided regional anesthesia: bridging the gap between potential and practice: a narrative review

Abstract

Ultrasound-guided regional anesthesia (UGRA) offers substantial benefits in perioperative pain management; however, it remains underutilized because of technical complexity and training demands. Assistive artificial intelligence (AI) has emerged as a promising solution to support UGRA by enhancing anatomical recognition, procedural accuracy, and user confidence. This narrative review outlines the AI development pipeline for nerve visualization, describes available commercial tools, and summarizes clinical evidence. Although these technologies have the potential to democratize UGRA and reduce interoperator variability, limitations remain, including data bias, narrow anatomical coverage, and lack of outcome-based validation. Future efforts should focus on standardized evaluation, clinician-centered design, and rigorous clinical trials to ensure safe and effective integration of AI into UGRA practice.