Laparoscopic surgery is an important branch of minimally invasive surgery. Due to its advantages of less trauma, faster postoperative recovery and fewer complications, it has been widely used in abdominal tumor surgery in various surgical subspecialties such as hepatobiliary, pancreatic and gastrointestinal surgery. However, laparoscopic surgery also faces limitations such as reliance on two-dimensional vision, increased operational complexity, and high requirements for surgeons′ experience, and its accuracy and safety still need to be improved. Recently, with its powerful data processing, image recognition and automatic decision-making capabilities, artificial intelligence (AI) has developed rapidly in cross-disciplinary applications in medicine, promoting the development of laparoscopic surgery toward precision and intelligence. In this review, we summarize the current applications of AI in laparoscopic abdominal tumor surgery, including preoperative evaluation and planning, intraoperative localization, prediction of postoperative complications, and postoperative rehabilitation. We also analyze the existing challenges in the application of these technologies, including data bias, model interpretability and ethical issues. Furthermore, from the clinical perspective of the hepatobiliary surgery subspecialty, we discuss the future technological development trends and clinical translation prospects in this field. This review aims to provide a reference for promoting the interdisciplinary integration of artificial intelligence and laparoscopic surgery and improving the level of surgical diagnosis and treatment.