Application of Artificial Intelligence in Circularity Assessment of Building Waste Materials: A Comprehensive Review of Recent Advances and Future Directions

Artificial intelligence (AI) offers significant potential to transform the construction sector, which remains one of the largest global sources of resource depletion, waste generation, and greenhouse gas emissions. This study aims to present a comprehensive state-of-the-art review of how AI contributes to circular economy strategies in building waste management and resource optimisation. It uses both a systematic literature review and critical analysis to consolidate current knowledge, identify research gaps, and propose future research directions. It further offers the first focused synthesis linking AI methods specifically to circularity assessment in building waste materials. The review analyses key AI techniques, including data mining, predictive modelling, deep learning, and optimisation, and evaluates their applications in material classification, lifecycle assessment, waste prediction, and decision support. It also examines data sources, modelling platforms, and circular materials. Findings reveal AI’s transformative role in enabling closed-loop construction systems, enhancing resource recovery, and advancing sustainable design practices. The study concludes by identifying critical research challenges and synthesising future research directions to support the transition towards resource-efficient, low-carbon, and circular built environments.