The integration of artificial intelligence (AI) in energy-efficient facade technologies is revolutionizing sustainable building design by enhancing thermal regulation, daylight optimization and energy savings. This study evaluates the performance of AI-driven adaptive glazing and smart window systems in optimizing building energy efficiency while maintaining occupant comfort. A comparative analysis of AI-enabled facade technologies demonstrates that AI-powered dynamic glazing reduces HVAC energy consumption by up to 45%, minimizes glare discomfort by 60% and improves thermal comfort by 20% compared to traditional facade systems. A machine learning-based predictive model, employing artificial neural networks (ANN), achieved 93% accuracy in forecasting facade adjustments, optimizing cooling loads by 40–50%. Despite high awareness levels among architects (80%) and commercial managers (85%), adoption rates remain moderate due to high upfront costs and unclear return on investment (ROI). Findings suggest that policy-driven incentives and financing models can accelerate market adoption. By meeting the needs of users and benefiting from technologies, AI incorporated facade systems can serve as a viable development path to sustainability in cities. Architects, developers and policymakers can benefit critically from scrutinizing the findings of this study when they are to design energy efficient, climate-responsive building envelopes.