Download PDFOpen PDF in browserA Critical Review and Metadata-Driven Analysis of Artificial Intelligence (AI) Applications in the Construction Industry across Project Lifecycles10 pages•Published: June 2, 2026AbstractDespite a growing body of research on AI in construction, most studies remain limited in scope, concentrating on specific tools, tasks, or individual project phases. This fragmentation hinders a comprehensive understanding of AI’s role throughout the entire project lifecycle. This study addresses this gap through a systematic literature review of research published between 2010 and 2024, using the PRISMA methodology. A metadata-driven analysis was conducted to facilitate deeper pattern recognition and gain a holistic understanding of AI implementation across lifecycle phases, examined through the lens of AI techniques, functional roles, key business processes supported, and AI tools/models. The findings suggest that AI is increasingly applied in the planning, design, and construction phases, while it remains underrepresented during project conception, closeout, and post-construction phases. Machine Learning (ML) dominates as the underlying AI technique, with optimization as the top functional role and risk management as the key supported business process. This study contributes to the body of knowledge by offering metadata-supported evidence and practical value for both academics and practitioners, highlighting not only what has been achieved so far but also where future efforts should be directed to promote more connected and intelligent project delivery.Keyphrases: artificial intelligence, benchmark, mapping, metadata, project lifecycle In: Wesley Collins, Anthony Perrenoud and John Posillico (editors). Proceedings of Associated Schools of Construction 62nd Annual International Conference, vol 7, pages 634-643.
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