Hepatocellular carcinoma (HCC) is one of the malignant tumors with high incidence and mortality rates worldwide, which poses severe threat to human health. In recent years, the application of artificial intelligence (AI) and multimodal imaging technology in the diagnosis and treatment of HCC has made remarkable progress. AI technologies, especially deep learning and traditional machine learning methods, have been applied in imaging big data analysis, which show high diagnostic accuracy and treatment decision support capability in early screening, staging and personalized treatment of HCC. Meantime, multimodal imaging technologies (such as CT, MRI, PET-CT, etc.) can improve the diagnostic efficiency and surgical safety in preoperative evaluation, surgical planning and intraoperative navigation. In this article, the latest progress in AI-based multimodal imaging in the diagnosis and treatment of HCC was reviewed, and its potential value and challenges in clinical practice were illustrated. In the future, with further optimization of AI model and the deepening of MDT, AI and multimodal imaging technology are expected to provide more precise treatment regimens and better prognostic evaluation for HCC patients.