Underground mining faces unprecedented challenges requiring real-time information access at opera-tional and strategic levels. Digitalization of mining processes and systematic implementation of arti-ficial intelligence are fundamentally reshaping the industry's operational paradigm. Modern AI-driven solutions enable comprehensive real-time monitoring of equipment utilization and technical condi-tion, transforming both tactical decision-making and long-term strategic planning. The integration of artificial intelligence with digital twins opens unprecedented opportunities for optimizing resource management and predicting technological outcomes with 85-95% accuracy. Contemporary mining demands intelligent tools that transcend historical data analysis, supporting dynamic management through automated reporting, predictive equipment reliability assessment, and continuous workplace condition monitoring. This paper synthesizes a decade of implementation projects and scientific re-search, presenting practical examples of AI applications across the mining value chain - from explora-tion and planning through production, transport, mineral processing, and metallurgical operations. The paper address key challenges in implementing AI across diverse operational scales, identify suc-cess factors, and provide recommendations for mining enterprises seeking to realize the transforma-tive potential of artificial intelligence in underground operations.
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