Artificial Intelligence in Hand Surgery and Microsurgery: Where Are We?

Artificial intelligence (AI) is an emergent and transformative force across all fields of medicine, including hand surgery and microsurgery. Its ability to enhance diagnostic accuracy, support surgical planning, and enable postoperative monitoring offers unique opportunities in a field where precision and safety are paramount. However, questions remain regarding real-world integration, validation, and ethical implications. Methods: We performed a narrative review of studies published between 2019 and 2025, retrieved from PubMed and Scopus, using predefined keywords related to AI and hand surgery. Inclusion criteria focused on human studies published in English with direct clinical or surgical relevance. Of the 71 articles initially identified, 26 were selected as most representative. These were categorized into five thematic axes: (1) general reviews, (2) microsurgery, (3) autonomous robotics, (4) surgical training and tracking, and (5) computer vision and functional assessment. Results: AI has shown measurable clinical impact in several domains. In fracture diagnosis, deep learning models achieved AUCs >0.93 and improved residents’ accuracy, especially in pediatric settings. In microsurgery, AI-assisted monitoring reached 98% accuracy in detecting early vascular compromise, while systematic reviews reinforced its potential for flap risk stratification. Robotic platforms demonstrated tremor filtration and submillimetric precision, though full autonomy remains out of reach. AI-enhanced training tools accelerated arthroscopy learning curves and fracture recognition among residents. Beyond the operating room, smartphone-based systems and wearable sensors enabled remote functional assessment and personalized rehabilitation strategies. Conclusions: AI is no longer a future concept but an active partner in diagnosis, microsurgical monitoring, surgical education, and rehabilitation in hand surgery. While its benefits are increasingly evident, translation into daily clinical practice requires multicenter validation, reduction of algorithmic bias, and cost-effectiveness analyses. Rather than replacing surgical expertise, AI should be embraced as a strategic collaborator, fostering a new era of precision, innovation, and patient-centered care.