Integrating IoT and AI for Sustainable Energy-Efficient Smart Building: Potential, Barriers and Strategic Pathways

The global drive toward sustainability and energy efficiency has accelerated the development of smart buildings integrating the Internet of Things (IoT) and Artificial Intelligence (AI). These technologies optimise energy use, enhance occupant comfort, and advance building management systems. This study examines the integration of IoT and AI in energy-efficient smart buildings, emphasising applications and challenges. A qualitative methodology, combining systematic literature review, case study analysis, and systems analysis, underpins the research. Findings indicate that IoT enables smart metering, real-time energy monitoring, automated lighting and HVAC, occupancy-based energy optimisation, and renewable energy integration. AI complements these functions through predictive maintenance, energy forecasting, demand-side management, intelligent climate control, indoor air quality automation, and behaviour-driven analytics. Together, they reduce carbon emissions, lower operational costs, and improve occupant well-being. However, challenges remain, including data security and privacy risks, interoperability gaps, scalability and cost constraints, and retrofitting difficulties. To address these, the paper proposes a systems thinking-enabled conceptual framework structured around three pillars: adopting IoT and AI as enabling technologies, overcoming integration barriers, and identifying application areas that advance sustainability in smart buildings. This framework supports strategic decision-making toward net-zero and resilient building design.