Intelligent Agents in Disaster Risk Management: A Systematic Review of Advances and Challenges

Abstract

Artificial Intelligence (AI) has emerged as a trans formative technology in the domain of Disaster Risk Management (DRM), offering new possibilities for forecasting, preparedness, and rapid response in the face of increasingly frequent and complex natural disasters. This systematic literature review synthesizes the state-of-the-art advances in AI-driven intelligent agents applied to DRM, covering domains such as early warning systems, geospatial analysis, damage assessment, evacuation plan ning, and decision support. It critically examines the technolog ical innovations, implementation methods, and interdisciplinary approaches that have shaped the evolution of intelligent agent based solutions in disaster scenarios. Through the analysis of over 7,800 scientific publications indexed in Scopus, Web of Science, and OpenAlex between 2010 and 2025, the review identifies key patterns, application domains, and persistent gaps such as data scarcity, lack of model interpretability, and limited operational deployment. The study also addresses ethical concerns related to AI deployment in high-stakes environments and proposes a roadmap for future integration of intelligent agents with IoT, UAVs, and real-time decision infrastructures. The findings contribute to a deeper understanding of how AI and multi-agent systems can reinforce disaster resilience and inform sustainable and adaptive disaster management strategies at both global and local levels.