The role of Artificial Intelligence in disaster management: A systematic study of global research progress, collaborations, and thematic shifts

The intersection of artificial intelligence (AI) and disaster management has emerged as a critical and rapidly expanding research frontier, driven by the increasing complexity of global crises and the urgent need for technologically advanced solutions. This study aims to map and analyse the evolution, structure, and collaborative dynamics of scholarly output in this interdisciplinary domain through a comprehensive bibliometric analysis. Utilizing a dataset comprising 11,055 documents published between 2000 and 2024 and retrieved from Web of Science and Scopus. 

The study employs bibliometric tools to evaluate publication trends, authorship patterns, keyword distributions, and citation impact. Analytical tools Bibliometric (R) were used to extract and visualize co-authorship networks, thematic clusters, and keyword co-occurrence maps. The findings reveal a robust annual growth rate of 25.89%, reflecting the intensifying academic and practical interest in leveraging AI technologies such as machine learning, deep learning, natural language processing, and robotics for disaster risk reduction and emergency response. The average document age of 4.76 years indicates the field’s recency and dynamism, while an average of 13.64 citations per document indicates moderate scholarly influence. It identifies critical trends, gaps, and opportunities for future research, particularly in enhancing global collaboration and interdisciplinary approaches to disaster resilience and emergency preparedness.