Autonomous Colorectal Surgery: Current Technologies, Clinical Applications, and Future Directions

INTRODUCTION: Colorectal surgery is technically demanding, with outcomes dependent on surgeon skill alongside patient physiology and disease state. With the burden of colorectal disease expected to increase, the variability in surgeon performance will inevitably impact a growing number of patients. Robotic technologies offer potential solutions, but they remain fully teleoperated, with no currently deployed fully autonomous surgical systems. This review examines the current state, limitations, and translational prospects of autonomous colorectal surgery. METHODS: We conducted a narrative review of English-language literature on surgical autonomy and elective colorectal surgery from inception to July 2026, searching PubMed, Scopus, and Web of Science. Findings were synthesized thematically. RESULTS: Autonomy in colorectal surgery is limited to isolated tasks rather than integrated across whole procedures. Clinically deployed systems remain confined to assistive and task-level functions, requiring the surgeon to manually initiate every tissue-manipulating action. The Smart Tissue Autonomous Robot has demonstrated supervised, conditional autonomy for intestinal anastomosis in phantom and porcine models. These demonstrations required fluorescent markers or prepared operative fields, substantially increased operative time, and have not been extended to humans in any colorectal application. As current validation of such systems remains fragmented, we propose autonomy-specific reporting measures describing system performance, safety, procedural integration, and human-robot interaction. CONCLUSIONS: Autonomous colorectal surgery remains at an early stage, with Smart Tissue Autonomous Robot demonstrating supervised soft-tissue autonomy in controlled settings. Translation is limited by the difficulty of modeling deformable tissue and complex pelvic anatomy, as well as by the absence of validation standards. Progress will depend on incremental, supervised integration, autonomy-specific reporting, and continued human oversight.