Abstract: Artificial intelligence technologies are driving rapid development in multiple research field, becoming a significant force in transforming mineral resources research paradigms, including mineral exploration and mineralization laws. Therefore, systematically analyzing global national and China’s provincial publication and collaboration network characteristics in the AI for Science applied on the mineral resources researches helps to grasp development trends in this domain, promote international scientific and technological cooperation, and advance the deep integration of artificial intelligence with mineral resources research. This paper innovatively proposes a search formula for AI for Science papers based on the Web of Science database, analyzes global publication volume evolution trends and distribution among major countries, further constructs collaboration networks from the perspective of co-authored publications, and analyzes national co-publication volumes, bilateral collaboration patterns, and collaboration roles. Finally, it examines publication distribution across Chinese provinces, international collaboration patterns, and industry-university-research cooperation. Research findings reveal: ①AI for Science applied on mineral resources research shows rapid growth momentum, with China, the United States, and the United Kingdom as the main publishing countries. ②The global collaboration network exhibits a “strong center, multiple nodes’’ structure, with China and the United States as the primary collaborating countries demonstrating different collaboration strategies. ③China is undergoing a transition from “international leverage” to “domestic autonomy” with deep industry-university-research integration becoming a new engine driving innovation, marking China’s scientific and technological innovation system’s gradual evolution from “following” to “parallel advancement” and even “leading” in certain directions.