Abstract: In order to thoroughly explore the current application status and development trends of artificial intelligence (AI) technology in the mining field and promote the process of intelligent mine construction, this paper presents a systematic review of the application of AI within the integrated framework of “sensing、communication、computing and control” in mines. The aim is to comprehensively organize the research achievements in this field and provide references for subsequent research and practice. The literature review and comprehensive analysis methods are adopted to extensively collect and deeply analyze relevant research results both domestically and internationally. Firstly, an overview of the basic connotation and scope of AI is provided to clarify the technological foundation of the study. Subsequently, the specific applications of AI in the mining field are elaborated in detail from four key dimensions: intelligent perception, intelligent communication, intelligent decision-making, and intelligent control. In terms of intelligent perception, it covers the perception of miners' vital signs and locations, equipment status, and environmental conditions. Intelligent communication involves intelligent voice technology as well as network slice traffic prediction in 5G bearer networks. Intelligent decision-making encompasses multiple levels, including production scheduling and optimization decisions, safety monitoring and emergency decision-making. Intelligent control focuses on the intelligent control of mine production processes, mine safety linkage and emergency response, etc. The research indicates that the application of AI in various aspects of mining has achieved remarkable results, effectively enhancing the safety, efficiency, and intelligence level of mine production. However, there are still some deficiencies in current research, such as the need to strengthen the coordination among different links, the lack of unified computing power and data center support, and the imperfect synergistic application of large models and professional model algorithms. AI has broad application prospects in mines. In the future, efforts should be made to strengthen the construction of unified computing power and data centers and promote the coordinated development of large models and professional model algorithms, so as to further enhance the level of mine intelligence and provide strong support for the sustainable development of the mining industry.