Artificial intelligence (AI) is playing an increasingly important role in developing cancer occurrence risk models. AI model can analyze vast amounts of data to identify patterns and correlations that may not be immediately apparent to clinicians, which can reduce overdiagnosis, timely identify risk factors, and lower incidence and mortality rates. This mini-review presented three specific articles that demonstrate the development process and application effectiveness of AI-based cancer occurrence risk models, providing inspiration and reference for future developments. These research allows for more accurate predictions of cancer risk based on a variety of factors such as imaging results, blood test result, etc. By identifying individuals at high risk for developing cancer, preventative measures can be taken to reduce their likelihood of developing the disease. Additionally, AI can help reduce overdiagnosis by distinguishing between benign and malignant conditions with greater accuracy. Overall, the use of AI in developing cancer risk models has the potential to greatly improve our ability to prevent and treat cancers.