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Abstract
This study investigates the emerging risks associated with integrating Generative Artificial Intelligence (GenAI) into risk management (RM) within sustainable construction projects (SCPs). A four-stage methodology was adopted: (1) a systematic literature review to identify GenAI-related risk factors; (2) the development of a multi-criteria assessment model to establish evaluation criteria; (3) a structured survey involving 80 construction experts to assess the identified risks; and (4) the application of a fuzzy logic-based model to quantify and rank their significance. Thirty risk factors were identified and grouped into five categories: input quality, technological adaptability, ethical and governance, information integrity, and financial risks. Fuzzy analysis highlighted human error, data unavailability, insufficient training, data breaches, and lack of awareness as the most critical risk factors. The study presents a novel, fuzzy logic-based risk assessment framework tailored explicitly to GenAI adoption in sustainable construction, providing enhanced decision-making capabilities in uncertain environments. It provides actionable insights for project managers and policymakers to prioritise and mitigate key risks, while also supporting responsible GenAI implementation. As one of the first studies to systematically examine these risks, it advances the discourse on AI integration in the built environment. It presents a replicable model for future assessments, encouraging context-sensitive research and contributing to the broader digital transformation of sustainable construction.
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