To investigate the current status, hotspots, and frontiers of big data and artificial intelligence research in the field of geology, this study conducts literature screening of relevant research publications between 2000-2022 using China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) core databases. A total of 3600 Chinese and 1803 English articles are collected, and community structure analysis software CiteSpace is used for visual analysis of cooperation authors, research countries/institutions, keyword clustering, and keyword spatiotemporal distribution maps. Furthermore, a stochastic frontier analysis correction is conducted on publications by international top-tier geoscience journals (comprehensive impact factor ≥10) between 2021-2022. The global cumulative publication volume in this research field had surged in the past decade, led by Asian countries represented by China and European/American countries represented by the United States, with China and the United States showing no significant differences, and the betweenness centrality measures generally higher for European/American countries than for Asian countries. In China, research collaborations were mostly among domestic institutions and relatively rare with foreign research institutions, whilst the opposite was true in foreign countries. The research hotspots in this field were geological disaster prevention and control, earthquake interpretation, petroleum and natural gas exploration, and solid mineral resource prediction using machine learning and knowledge graphs. Research frontiers included significant geological events during Earth’s evolution, global climate change, polar and marine geology, digital geological modeling and quantitative analysis, earthquake prediction, and accurate assessment of geological disaster susceptibility by means of deep learning, integrated learning, and intelligent platform.