AI-assisted decision-making and dynamic trust in lean construction: synergy mechanisms and insights

Purpose This research investigates the influence of AI-assisted decision-making on dynamic trust in lean construction organizations. It examines how AI enhances collaboration efficiency, information transparency and trust stability in complex project environments. The moderating effects of decision chain length and the mediating roles of risk preference and task transfer resilience are also analyzed to provide actionable insights for trust management. Design/methodology/approach Using a survey of 293 lean construction professionals, structural equation modeling (SEM) was applied to assess the relationships among AI-assisted decision-making, dynamic trust, risk preference, task transfer resilience and decision chain length. The sample reflects diverse project types and organizational contexts. Findings AI-assisted decision-making significantly improves dynamic trust. Risk preference and task transfer resilience mediate this relationship, while decision chain length moderates the effects. Shorter decision chains amplify the mediating roles of risk preference and task transfer resilience, while longer chains reduce these effects. Notably, as decision chain length increases, the influence of task transfer resilience on dynamic trust weakens compared to risk preference. Originality/value This research bridges gaps in understanding the mechanisms linking AI and dynamic trust in lean construction. By integrating decision chain length and mediating factors, it offers a novel framework for optimizing trust dynamics and collaboration through AI. These findings provide critical insights for advancing lean construction practices in the era of intelligent technologies.