A guidance framework for enhancing the performance of AI application in construction cost management

Purpose This research aims to develop a comprehensive guidance framework for the application of artificial intelligence (AI) in construction cost management by investigating the factors affecting and formulating future directions for AI adoption based on the Technology-Organization-Environment (TOE) framework. Design/methodology/approach A mixed-methods approach was employed, combining quantitative analysis based on survey data from 539 professionals in construction cost management and qualitative insights derived from a focus group discussion with 10 respondents. The quantitative data were analyzed using Structural Equation Modeling (SEM), while thematic analysis was applied to the discussion data to capture industry-specific perspectives. Findings Quantitative analysis indicates that organization, technology and environment dimensions all significantly influence the performance of AI applications in construction cost management. The environment dimension was found to be the most influential, while qualitative interviews highlighted the key future direction for enhancing the performance of AI applications according to the critical factors tested by SEM. Originality/value The TOE framework is applied to offer a comprehensive understanding of AI applications in the construction industry. It is one of the first studies to combine both quantitative and qualitative data to explore the critical factors, barriers and enablers of AI in cost management within the construction sector.