Abstract: The artificial intelligence robotic surgical system, as a cutting-edge product of the intersection of intelligent surgery and biomedical engineering, is reshaping the technological paradigm of colorectal cancer treatment. The system significantly improves the accuracy, stability, and safety of surgery by integrating high-precision robotic arms, multimodal image recognition, real-time decision-making algorithms, and knowledge transfer learning mechanisms. It particularly demonstrates unique advantages in key operations such as lymph node dissection, anastomosis construction, and nerve protection in narrow pelvic cavities. Compared with traditional laparoscopic surgery, AI surgical robots can achieve sub millimeter level operational accuracy, real-time force feedback simulation, and personalized path planning, significantly reducing the risk of complications such as intraoperative bleeding, anastomotic leakage, and postoperative dysfunction. In recent years, with the rapid development of robot platforms and the deep integration of technologies such as 5G remote communication, digital twins, and reinforcement learning, colorectal cancer surgery is accelerating towards a new stage of high intelligence, individualization, and remote collaboration. However, in the process of clinical promotion, there are still key challenges such as missing tactile feedback, delayed multimodal data fusion, unclear regulatory pathways, and lack of medical engineering collaboration system. This article systematically reviews the development history, clinical application advantages, key technological bottlenecks, and future evolution directions of AI robot technology in colorectal cancer surgery. It focuses on exploring its core values in intelligent perception, intraoperative collaboration, remote surgery, and clinical transformation paths. The aim is to provide theoretical basis and practical reference for surgeons, engineering researchers, and health policy makers from an interdisciplinary perspective, and promote the high-quality clinical application of AI robot surgery systems from engineering innovation.