Sustainable architecture has become a crucial aspect of urban development, aiming to reduce environmental impact while enhancing efficiency, resilience, and livability. As urban populations grow and climate change accelerates, the need for innovative solutions in building design and construction has never been more pressing. Artificial intelligence (AI) and smart technologies have revolutionized the construction industry, introducing new approaches to optimizing energy consumption, material usage, and overall building performance. This paper explores the intersection of AI, technology, and sustainable architecture, focusing on key applications such as energy-efficient building designs, intelligent building management systems (BMS), and predictive analytics for sustainable urban planning. AI-driven solutions, including machine learning algorithms and real-time data analytics, enable adaptive energy systems that minimize waste and improve efficiency. The integration of Internet of Things (IoT) devices and smart sensors further enhances building sustainability by enabling automated climate control, occupancy-based lighting systems, and predictive maintenance strategies. The study examines case studies of AI implementation in green architecture, showcasing how cutting-edge technologies have been successfully leveraged to reduce carbon footprints, enhance resource efficiency, and create more adaptive urban environments. Furthermore, the paper discusses challenges such as data privacy concerns, high implementation costs, and the need for interdisciplinary collaboration between architects, engineers, and data scientists. By analyzing current trends and advancements, this paper provides insights into future directions in AI-powered sustainable architecture. The findings suggest that continued innovation in AI and smart technologies will play a pivotal role in driving the transition toward a greener, more efficient, and intelligent built environment.
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