AI-driven energy optimization systems for sustainable smart buildings

Buildings account for a significant portion of global energy consumption and carbon emissions. Traditional building management systems often rely on fixed operational schedules that fail to adapt to changing occupancy and environmental conditions. This study investigates the role of Artificial Intelligence (AI) in optimizing energy usage within smart buildings. A qualitative comparative analysis of conventional and AI-driven energy management approaches was conducted using existing literature. Additionally, a case study of commercial buildings in Delhi is presented to contextualize the findings. The results indicate that AI-based systems can improve energy efficiency through predictive control, occupancy-based automation, and real-time monitoring. A key insight from this study is that buildings with highly variable occupancy patterns may achieve the greatest energy savings from AI-driven optimization systems.