The construction industry is a multifaceted one that comprises numerous risks that can easily hamper the progress and viability of a particular project. Over the years, growing trends in artificial intelligence have proposed predictive analysis as a means of managing these risks. This study exclusively focuses on theories and concepts that explain the application of AI in risk analysis for construction projects. Based on the identified literature between 2014 and 2024, this study provides a structured and organized way of reviewing theories, concepts, and variables that are important in the implementation of AI in construction. Consistent with these discussions, this study provides a conceptual framework that explains the interrelated nature of the above-stated variables and fills the theoretical literature gap for future empirical research. To confirm the applicability of the proposed framework, the study outlines hypothesis formation and the creation of a questionnaire for the collection of empirical data.
Kuwaiti et al. (Sat,) studied this question.
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