Abstract: [Objective] The rapid development of artificial intelligence has reshaped the research paradigm of geosciences. Coal geology focuses on coal, coal seams, coal-bearing strata, coal basins, and coexisting and associated mineral resources in coal-bearing strata. These research objects exhibit highly complex material compositions, multiscale characteristics, and pronounced spatiotemporal variability. Consequently, the major research directions of coal geology, including coal petrology, coal geology, critical metals in coal-bearing strata, and coalbed methane exploration and development, are highly compatible with artificial intelligence.[Methods] Artificial intelligence is driving coal geology beyond traditional experience-based identification and local statistical analysis toward a new paradigm integrating multi-source data fusion, intelligent prediction, and mechanistic interpretation. It also provides new opportunities for discovering previously unrecognized geological phenomena.[Results] This paper systematically reviews recent advances in the application of artificial intelligence to the intelligent identification of coal macerals, intelligent prediction of coal quality, intelligent assessment of the occurrence modes and resource potential of critical metals in coal, and coalbed methane prediction. Artificial intelligence technologies have significantly improved the efficiency and accuracy of maceral image recognition, coal quality parameter prediction, identification of occurrence patterns of critical metals in coal, and comprehensive resource evaluation. However, several challenges remain, including the scarcity of high-quality datasets, limited cross-regional generalization capability, weak model interpretability, insufficient consistency with geological mechanisms, inadequate knowledge constraints, and limited implementation in engineering scenarios.[Conclusions] Future research should strengthen the construction of standardized large-scale databases, promote the deep integration of geological knowledge with data-driven models, develop interpretable and transferable intelligent models, and establish an intelligent research paradigm oriented toward major scientific questions in coal geology and the green and efficient development of coal-related resources.[Significance] This review highlights the transformative role of artificial intelligence in advancing coal geology from experience-driven analysis toward knowledge-guided intelligent research, providing methodological support for major scientific discovery and the green, efficient development of coal-related resources.