Research on economic efficiency of coal mining driven by artificial intelligence

ZHAO Xin

doi:10.3969/j.issn.1002-9605.2025.12.039

Abstract：This article focuses on the coal mining sector.It conducts an in-depth analysis of the economic efficiency leap driven by Artificial Intelligence in this field from a cross-industry perspective,innovatively introducing the "technology-economy transmission"methodology,which fills the gap in cross-industry economic benefit analysis in the mining industry.The research first establishes the benchmark of AI's economic promotion effect in five typical industries,namely the electronics manufacturing industry,the construction industry,the agricultural Internet of Things,the logistics and warehousing industry,and the semiconductor industry.It then builds a model for converting the economic value of safety benefits,quantifying that for every 1％increase in safety efficiency in the coal mining industry,the economic value gain is 1.6 times that of the manufacturing industry.It calculates that the AI transformation cycle for the coal mining industry is 5 to 7 years,with an annualized return rate of approximately 20％,and each mine can achieve annual personnel cost savings of 5 million yuan and production capacity premium of 45 million yuan.At the same time,it predicts that the coal mining industry will reach a turning point of benefit explosion three years after AI investment,and the energy security strategy gives it a policy weight coefficient advantage of 75％.The study examined model biases and inferential limitations arising from factors such as underground conditions,fragmented data protocols,and coal price fluctuations,providing a cross-industry comparative methodology and toolkit for AI transformation in the coal mining sector.