Evaluation of success factors of utilizing AI in digital transformation of health and safety management systems in modern construction projects

Abstract

In the construction industry, managing health and safety concerns is paramount to preventing accidents, injuries, and project delays. The integration of Artificial Intelligence (AI) into existing health and safety management systems holds the potential for significantly improving risk detection, mitigation, and overall management [1,2,3]. However, despite the evident benefits of AI in this domain, there remains a notable gap in the literature concerning the essential factors for successful implementation [4,5]. This study aims to address this gap by meticulously analyzing the key elements that contribute to the success of AI integration into the digital transformation of health and safety management systems within cutting-edge construction projects. Our methodology involved the identification of 25 factors, drawn from prior research and industry consensus. These factors were subjected to rigorous analysis, including Exploratory Factor Analysis (EFA) following a pilot survey with field experts and Structural Equation Modeling (SEM) using data obtained from a comprehensive questionnaire distributed among a representative sample of construction industry experts. The study's findings underscore the paramount importance of six critical constructs in determining the success of AI implementation in construction health and safety management systems: Adaptability, Operation, Management, Reliability, Integration, and Knowledge. These findings provide valuable insights for enhancing safety measures in the construction industry through AI-driven solutions.