From Sensing to Transforming: An AI-Enabled Capability Framework for Circular Construction and Demolition Waste Management

Abstract

Artificial intelligence (AI) and AI-enabled digital technologies are increasingly proposed as enablers of circularity in construction and demolition (C&D) waste management, yet existing reviews are organised around technology and lifecycle stage and rarely examine the organisational conditions under which technically capable applications move from pilot to sustained practice. This review addresses that gap through a PRISMA 2020-guided systematic review of 217 recent Scopus records (2022–2026), interpreted through dynamic capabilities theory, diffusion of innovation theory, and the circular economy value-retention hierarchy. Abstract-level coding of capability enablers, AI mechanism clusters, and circularity outcomes is triangulated with latent Dirichlet allocation topic modelling, bibliographic coupling, co-citation and keyword co-occurrence analyses, and statistical tests of association. The central finding concerns where research attention has concentrated: digital infrastructure and AI/machine learning technical capability appear in 64–67% of studies, whereas governance and human/organisational capability appear in only 13–18%, and traceability/material security is the least-examined outcome (11.1%). These patterns describe the published literature rather than organisational practice. They are integrated into a four-layer framework that separates observed associations from theoretical inferences, and into six propositions for organisational-level testing. Substantive policy instruments appear in only 4.1% of studies, so the policy implications are presented as exploratory.