ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE DISASTER MANAGEMENT: BRIDGING TECHNOLOGY, POLICY, AND COMMUNITY RESILIENCE

Abstract

Artificial intelligence (AI) emerged as an important technological solution for improving sustainable disaster management through enhanced prediction, emergency response, policy coordination, and community resilience. This study examined the role of artificial intelligence in bridging technology, policy, and community resilience within disaster management systems. The research investigated how AI-driven technologies improved disaster preparedness, emergency response efficiency, and sustainable recovery planning. A quantitative research design was adopted, and data were collected from a sample of 350 respondents including disaster management professionals, policymakers, humanitarian workers, technology experts, and community representatives. Statistical analysis was conducted using descriptive statistics, reliability analysis, correlation analysis, and multiple regression analysis through SPSS software. The findings revealed that artificial intelligence significantly influenced sustainable disaster management (β = 0.73, p < 0.001), while community resilience demonstrated the strongest impact on disaster management outcomes (β = 0.77, p < 0.001). Policy integration also showed a significant positive effect (β = 0.69, p < 0.001). The model summary reported an R² value of 0.709, indicating that 70.9% of the variation in sustainable disaster management was explained by artificial intelligence, policy integration, and community resilience. The study concluded that AI technologies strengthened disaster resilience through predictive analytics, intelligent communication systems, and collaborative governance frameworks. The findings emphasized the importance of ethical governance, digital infrastructure, and community participation in developing sustainable and adaptive disaster management systems.