Surgeon-in-the-Loop AI Systems in Robotic Surgery: Enhancing Precision, Efficiency, and Personalisation – A Short Narrative Review

Surgeon-in-the-loop AI systems represent a significant advancement in robotic surgery by integrating artificial intelligence (AI) to enhance human capabilities while maintaining surgeon oversight. This narrative review summarises recent literature from 2023 to 2025 on their applications in general robotic surgery, focusing on areas such as reinforcement learning, image recognition, and real-time decision support. A thorough search of databases, including PubMed, Scopus, and Web of Science, identified key studies demonstrating improvements in precision, efficiency, and personalisation. The findings demonstrate AI's capacity to tailor its approach to a surgeon's preferences, offer intraoperative guidance, and minimise errors through the use of advanced imaging techniques. However, challenges remain, including data privacy concerns, algorithmic bias, and regulatory hurdles. Looking ahead, there is a need to balance the autonomy of these systems with ethical safeguards, as well as efforts to expand access to such technologies. This review highlights the potential of surgeon-in-the-loop AI systems to revolutionise surgery and calls for interdisciplinary collaboration to address existing limitations. Keywords: Artificial intelligence, robotic surgery, surgeon-in-the-loop, reinforcement learning, image recognition, ethical challenges, precision medicine