AI-Based Decision Support Systems for Sustainable Development Policy and Planning

The growing complexity of sustainable development challenges requires policy systems capable of integrating diverse data sources, anticipating long-term impacts, and supporting evidence-based decision-making across sectors. Artificial Intelligence based Decision Support Systems offer a transformative approach to sustainable development policy and planning by combining predictive analytics, optimization modeling, and real-time data integration within adaptive governance frameworks. This paper conceptualizes the architecture and functional dimensions of AI-enabled decision support systems tailored to sustainable development objectives, examining their capacity to enhance policy design, resource allocation, risk forecasting, and cross-sectoral coordination. Drawing on interdisciplinary scholarship in artificial intelligence, public policy and sustainability studies, the study proposes an integrated framework that aligns AI capabilities with Sustainable Development Goal monitoring and implementation processes. It further evaluates governance, ethical and institutional considerations that shape responsible deployment, including transparency, fairness, data privacy, and digital capacity constraints. The analysis argues that AI-based decision support systems function not merely as technical tools but as enabling infrastructures that strengthen institutional intelligence and policy responsiveness. When implemented within accountable and inclusive governance structures, such systems hold significant potential to improve the effectiveness, efficiency, and equity of sustainable development planning.