The surgical treatment of hepatocellular carcinoma (HCC) is undergoing a profound paradigm shift from traditional empirical models to digital and intelligent precision medicine. While minimally invasive liver resection (MILR) is widely accepted, it still faces challenges in complex vascular anatomy and depth perception. The participation of artificial intelligence (AI) technology will have a significant impact on perioperative management in MILR. In the preoperative phase, deep learning enables rapid quantitative reconstruction of vascular and biliary structures, combined with radiomics and explainable AI models to predict future liver remnant and the risk of post-hepatectomy liver failure. During the intraoperative phase, navigation technology has evolved from "static calibration" to "intelligent adaptive registration." Notably, the robotic "Brain-Eye-Hand" collaborative system and instrument deocclusion technology have significantly enhanced the precision of resecting tumors in complex locations. Postoperatively, AI promotes the transition from passive follow-up to active real-time monitoring. Despite existing bottlenecks in deformation compensation accuracy and algorithmic generalizability, the AI-driven "data-driven" paradigm will lead minimally invasive surgery into a new era of seamless, full-process intelligence.