Critical success factors for implementing artificial intelligence in construction projects: A systematic review and social network analysis

Artificial intelligence (AI) is increasingly deployed to automate routine tasks, generate accurate insights from big data, and build predictive models to inform better decision-making in construction projects. However, AI deployment in construction projects constitutes a sociotechnical process, such that adopting solely a technical approach becomes inadequate. This study investigated the critical success factors for implementing AI in construction projects. It combined a systematic literature review, meta-analysis, and social network analysis to evaluate the scientific evidence on the critical success factors, and quantitatively reveal the underrepresented factors. The meta-analysis identified 38 critical success factors, ranked according to normalized scores and degree centralities. The study derived four dimensions of the critical success factors, including organizational, technological, stakeholder, and data success factors. The social network analysis quantitatively revealed the strengths and existing gaps in the reviewed studies and provide insights into factors that need further investigation.