Abstract: Gallbladder cancer is a highly aggressive malignancy of the biliary system, often diagnosed at the advanced stage due to its insidious early symptoms, leading to poor overall progno-sis. In recent years, the rapid advancement of artificial intelligence (AI) technologies and their inte-gration into medicine have opened new avenues for the early diagnosis and precision treatment of gallbladder cancer. Currently, AI incorporating deep learning algorithm has significantly improved diagnostic sensitivity and specificity in ultrasound, computed tomography, and pathological analysis. However, clinical translation of AI models remains limited by challenges such as insufficient annota-ted data and limited model interpretability. Future research should focus on establishing multi-center data‑sharing mechanisms, developing interpretability tools, and optimizing multimodal data integration strategies, thereby promoting the transformation of AI technologies from an auxiliary diagnostic tool to a core component of clinical decision‑making.