AI capability, knowledge integration, and cognitive barriers: Innovation pathways for circular economy practices in construction

The transformative potential of artificial intelligence (AI) is prompting construction organizations to redefine the concept of progress. However, the transition from digital capability to a higher-level sense of innovation is not inevitable. This research delves into the effect of AI capability on innovation-driven circular economy (CE) practices, providing evidence that technological advances alone do not drive change without an enabling cognitive and organizational environment. We adopt the lens of sociotechnical systems (STS) theory to conceptualize knowledge integration as the mechanism by which AI capability leads to CE practice adoption and cognitive rigidity as the inhibitor that reduces the positive effect of knowledge integration. Structural equation modeling and moderated mediation tests are applied to a survey of 414 construction professionals. Results suggest that AI capability promotes new ways of working and CE practices indirectly through its influence on knowledge integration; however, this influence is attenuated when cognitive rigidity hampers knowledge integration. The research extends STS theory into a domain of innovation management by integrating its cognitive, technical, and organizational elements. Our findings offer practical implications for industry practitioners, suggesting that building CE capacity goes beyond adopting digital technology; it also involves fostering cognitive agility and robust knowledge exchange mechanisms to enable those technologies to translate into innovation.