Enhancing the technological and procedural components of calamities and disaster research stands out as an important and pivotal process within disaster management. The application of artificial intelligence (AI) presents a spectrum of applications, including but not limited to tracking as well as mapping, geospatial evaluation, remote sensing methods, drone technology, robotics, network and telecom services, machine learning, analysis of accident hotspots, smart city planning, transport and route planning, and environmental impact evaluation. These technology-based facets signify communal change and bear profound implications for studying societal responses to disasters. Researchers have adeptly employed diverse methodologies and techniques, adopting disciplinary, multidisciplinary, and interdisciplinary approaches to investigate hazards and disasters. Researchers have integrated both qualitative data and quantitative data collection and analysis strategies. This research offers an outline of AI’s applications in disaster prevention and management across its phases, emphasizing AI’s integral role in expediting and refining responses throughout all disaster management stages. The integration of geographic information system (GIS) as well as remote sensing (RS) into disaster management fosters situational awareness, enhanced planning, analysis, and recovery efforts. RS and GIS are widely acknowledged as pivotal tools in disaster management support. The visualization capability, imagery based on satellite, and AI-driven analyses can facilitate swift governmental decision-making in the case of natural disasters.