Robotic surgical systems integrated with artificial intelligence (AI) algorithms, as a frontier product at the intersection of intelligent surgery and biomedical engineering, are reshaping the technological paradigm of colorectal cancer treatment. These systems incorporate high-precision robotic arms, multimodal image recognition, real-time decision-making algorithms, and knowledge transfer learning mechanisms, demonstrating advantages in critical procedures such as lymphadenectomy, anastomotic construction, and nerve preservation within the confined pelvic cavity. Compared with conventional laparoscopic surgery, AI-integrated robotic systems can achieve an operating precision of 0.5-1.0 mm, an intraoperative lymph node recognition accuracy of 98.7%, and a 15%-20% increase in the number of lymph nodes dissected. The incidence of anastomotic leakage decreases by approximately 2-3 percentage points (from 5.4% to 1.9% ), while mean intraoperative blood loss is reduced by 50-80 mL, significantly lower than the 90-120 mL typically observed in laparoscopic procedures. In recent years, driven by the rapid evolution of robotic platforms and the deep integration of technologies such as 5G remote communication, digital twins, and reinforcement learning, colorectal cancer robotic surgery systems are progressing toward higher levels of intelligence, individualization, and remote collaboration. Nevertheless, key challenges remain in clinical implementation, including the lack of tactile feedback, delays in multimodal data fusion, unclear regulatory pathways, and insufficient medical-engineering collaborative frameworks. This review systematically summarizes the developmental trajectory, clinical advantages, core technical bottlenecks, and future directions of AI-integrated robotic systems in colorectal surgery, with particular emphasis on their value in intelligent perception, intraoperative coordination, remote surgery, and clinical translation pathways. The aim is to provide interdisciplinary theoretical foundations and practical references for surgeons, engineering researchers, and healthcare policymakers.