Abstract: In recent years, artificial intelligence (AI) technology has developed rapidly and is increasingly integrated into various fields of economy and society. It has become a new symbol of contemporary innovation and development. Intelligent disaster prevention and mitigation will become the future development trend and research hotspot. On the basis of reviewing the status and trend of (AI) development, this paper systematically sorts out the data basis and traditional technical methods of previous geological disaster risk prevention and control, analyzes the potential AI methods that may be used, and initially builds a an AI-based geological disaster risk prevention and control system. Research shows that AI technology provides a new technical approach for the prevention and control of geological disaster risks, but there are no mature technologies or solutions that can be copied or portable. The proposed intelligent disaster prevention and mitigation system includes three main parts:early identification, risk assessment, and risk prevention and control. The key point is early identification, while the key parameter for the fusion between traditional methods and AI technology is the probability of slope instability or the probability of derrs flow occurrence; According to the data, the early identification methods are summarized into six methods:image recognition, deformation recognition, displacement recognition, internal factor recognition, incentive identification and comprehensive recognition. This paper proposes a geological disaster risk prevention and control platform based on big data intelligent hybrid optimization from three levels:data layer, method layer and application layer. It is believed that the fusion between data-driven intelligent models and theoretically driven physical models is the trend of geological disaster risk prevention and control development.