Abstract: This paper focuses on how artificial intelligence empowers green mining, combining market data, domestic and international policies, technology classifications, and their connection to global patent layouts for a systematic analysis. Firstly, it reviews global green mining market trends and points out that the Asia-Pacific region is the largest and fastest-growing market. Green mining policies of different countries are based on their local resources and environmental characteristics, forming differentiated regulatory models. The paper compares policies from six major mining countries: the United States, the United Kingdom, Australia, Canada, South Africa, and Saudi Arabia, and clarifies the three-stage evolution of China’s policies, analyzing the differences in governance logic among three key documents. It then proposes three types of green mining technology systems, including data collection, intelligent analysis, and interconnected integration, and identifies four application scenarios based on green technologies in the mining sector. Finally, based on the incoPat patent database, it carries out a bibliometric analysis, combining the patent lifecycle with national economic industry classifications, to examine trends in annual patent applications, countries, IPC classifications, and technology effectiveness. By analyzing R&D investment, fixed asset investment, and overseas investment, it highlights how artificial intelligence technologies supporting high-quality development of green mining are gradually permeating various aspects and stages of the mining industry.