This article focuses on green exploration, the core orientation of sustainable development in the mining industry, and analyzes the necessity of researching the AI + geological big data mineral exploration model. The current traditional exploration mode is difficult to adapt to green development due to its high resource consumption, strong environmental interference and limited target area prediction accuracy. However, the integration of AI and geological big data provides a new path for the collaboration of “efficient mineral exploration and ecological protection”. The research takes the optimal model of exploration target areas as the entry point, constructs the model framework, clarifies the processing flow of multi-source geological data and the implementation process of machine learning algorithms, and at the same time discovers problems such as significant data barriers, low domestic production rate of core technologies, insufficient disciplinary integration, lack of industrial collaboration, and lagging policy standards. In response to the above issues, this paper proposes five countermeasures: building a unified national geological data sharing platform, strengthening independent research and development of core software and hardware technologies, promoting the deep integration of geology and AI, integrating resources from industry, academia and research to establish an industrial innovation consortium, and optimizing the approval of classified data and formulating model evaluation standards. The research results can provide support for the selection of exploration target areas under green constraints, facilitate the industrialization of models, and offer guarantees for China’s new round of strategic actions for mineral exploration breakthroughs and the green development of the mining industry.