Disaster Risk Management and AI: A Grounded Theory Approach to Epidemic Response

Over the past few years, there has been a growing interest in utilizing artificial intelligence in disaster risk management (DRM), particularly in epidemic response. This study employs a grounded theory methodology to explore expert perspectives on AI’s applications, opportunities, and challenges in managing disasters, with a focus on epidemic outbreaks. AI-driven predictive analytics, real-time decision support, and resource optimization have enhanced disaster preparedness and response, but challenges such as data quality, algorithmic bias, governance frameworks, and ethical concerns remain significant. 63 experts from different backgrounds participated in our study. The findings revealed the necessity of integrating AI within regulatory structures, addressing interoperability issues, and fostering interdisciplinary collaboration to maximize its effectiveness. A theoretical model is developed, synthesizing AI applications across functional layers to provide a structured understanding of its role in DRM. The study concludes that while AI can revolutionize disaster preparedness, its success depends on balancing technological advancements with ethical considerations and governance structures. Future research should explore innovations that enhance AI’s reliability, transparency, and public trust, ensuring its responsible deployment in DRM.