Artificial Intelligence in Sustainable Housing

The increasing urgency of environmental sustainability has propelled the construction sector toward eco-friendly housing solutions. Concurrently, artificial intelligence is emerging as a transformative force across industries, including architecture, engineering, and construction. This systematic review examines the current landscape of AI applications in eco-friendly housing, synthesizing findings from over 30 peer-reviewed studies published between 2016 and 2025. The review categorizes AI use cases into design optimization, energy efficiency modeling, smart material selection, and life cycle assessment. It critically evaluates the methodological robustness of existing research and identifies prevailing challenges, such as data scarcity, model interpretability, and integration with legacy systems. Findings suggest that AI can significantly enhance energy performance predictions, reduce construction waste, and enable adaptive, user-centered housing designs. However, limitations in transparency and generalizability persist, particularly in real-world deployment contexts. The review concludes by proposing a research agenda that emphasizes interdisciplinary collaboration, open data practices, and the development of interpretable, domain-specific AI models.