The evolution of sustainable building governance: Comparative insights from global energy code systems and their forecasting by agentic AI system

This study proposes a novel Sustainable Building Governance Index (SBGI) integrated with an advanced Agentic AI-Based Forecasting Framework to evaluate and predict the future evolution of global sustainable building governance systems. The framework combines multidimensional governance indicators including building energy codes, HVAC governance, lighting efficiency, retrofit readiness, climate adaptation, envelope performance, and compliance mechanisms into a unified sustainability intelligence platform. Statistical validation confirmed strong framework reliability with a Cronbach Alpha value of 0.89, PCA variance explanation of 81%, and forecasting accuracy of 92%. The proposed Agentic AI model outperformed conventional machine learning approaches including XGBoost, Random Forest, LSTM, and ARIMA. Forecasting results indicate that global SBGI values will increase from 0.58 in 2024–0.91 by 2050, while net-zero readiness rises from 0.39 to 0.94. The study further predicts a 57% reduction in building-sector carbon emissions by 2050 through intelligent governance systems, retrofit integration, smart HVAC optimization, and AI-driven sustainability planning. The framework provides a next-generation intelligent governance platform for supporting climate-resilient and carbon-neutral urban transitions.