Abstract: In recent years, artificial intelligence (AI) has rapidly developed, and its advantages in dealing with high throughput and multi-dimensional data have been demonstrated, thus providing new opportunities in cancer prevention and control. Combining AI with radiology, pathology, electronic health records, and omics data may help investigate causes and risk factors of cancer more effectively to promote primary prevention, detect and diagnose cancer earlier to improve secondary prevention, and guide clinical medication and treatment by risk assessment and prognosis prediction to benefit tertiary prevention. Despite the promising advantages of AI technology, it still has challenges with respect to data integrity, availability, model robustness, generalizability, and interpretability of results, which limit its application in preventing tumors and controlling real-world scenarios. In this study, we reviewed the application of AI with respect to three-level cancer prevention to assess the latest advances and key challenges and explore future visions of integrating AI technology into cancer prevention and control.