One of the most disaster-prone countries globally, experiences frequent natural calamities, including typhoons, earthquakes, and floods is the Philippines. This study explores the role of AI in enhancing disaster prediction, risk management, and mitigation in the Philippines. Using a qualitative research approach, semi-structured interviews were conducted between June 2023 and March 2024 with key stakeholders, including disaster management officials, meteorologists, and researchers. The findings highlight how AI technologies, particularly machine learning and neural networks, have significantly improved disaster forecasts by processing extensive datasets from meteorological, seismic, and geographical sources. AI-driven models are enhancing the accuracy of predictions for typhoons, earthquakes, and flood risks, contributing to more effective early warning systems and timely evacuation protocols. Despite these advancements, challenges remain, including limitations in infrastructure, budget constraints, and data quality, which hinder the full adoption of AI in disaster risk management (DRM). Nevertheless, the study identifies substantial opportunities for further development, emphasiz
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