AI-Supported Climate Migration Planning: Equity, Social Protection, and Community Adaptation in High-Risk Regions

Abstract

Climate-induced migration has become one of the biggest social, environmental, and governance challenges in high-risk areas. In response to the impacts of rising temperatures, floods, droughts, sea-level rise, food insecurity, and livelihood disruption, vulnerable communities are having to move—at least temporarily, or even permanently. In this paper, AI's role in assisting climate migration planning through the enhancement of risk forecasting, determining the most vulnerable communities, bolstering social protection frameworks, and assisting with community-based adaptations is explored. From a practical perspective, the study emphasizes the contribution of AI-powered tools like geospatial mapping, machine learning-based models, early-warning systems, vulnerability indexes, and predictive displacement analysis to support government and humanitarian decision-making. The results highlight the potential of AI to enhance climate migration planning by identifying vulnerable households, predicting migration trends, prioritizing resources, and enabling tailored policy interventions. The paper also highlights the importance of equitable and transparent AI planning, data protection, and community engagement. If there is no inclusive governance, AI systems can deepen inequities, marginalize or misclassify vulnerable households or favor populations that are not socially invisible but are technically visible. The paper argues that the use of AI should not be a substitute for planning rooted in the principles of social justice and adaptive governance but rather a decision-support tool in these frameworks. Planning for climate migration needs to combine technological innovations, social protection, local knowledge, participatory adaptation, and rights-based policy design.