Abstract Motivated by the historical use and increasing relevance of artificial intelligence (AI) in wildfire management, this study reviews the role of AI in wildfire management through a bibliometric study using a dataset of 1,985 peer-reviewed publications sourced from Scopus. The analysis identifies four thematic clusters: (1) geospatial and climatic analysis of wildfires using remote sensing and prediction, (2) technological and algorithmic advancements for wildfire detection and monitoring, (3) machine learning–driven wildfire prediction, risk assessment, and behavior modeling. Our findings show a multidisciplinary and application-oriented research field with increasing relevance due to climate change and escalating fire events. Based on our findings, we propose future research directions, including multimodal data integration, explainable AI, and real-time human-AI collaboration. This study contributes to a systematic understanding of current AI approaches in wildfire research and supports the development of a targeted research agenda for advancing technological and scientific responses to wildland fire challenges.
Karger et al. (Wed,) studied this question.