The impact of artificial intelligence on the quantity surveying profession in Sarawak, Malaysia

Purpose Artificial intelligence (AI) aids in enhancing construction efficiency, safety and cost management, but also possesses challenges such as workforce adaptation and potential redundancy for Quantity Surveyor (QS). Although the Malaysian government promoted digitalization since 2010, AI adoption in the construction sector remains slow compared to developed countries. Therefore, this study aims to: (1) identify the severity of the impacts of AI, (2) categorize the impacts of AI and (3) examine the relationship between combined impacts of AI and its adoption on the quantity surveying profession. Design/methodology/approach Questionnaire surveys were distributed to QSs via simple random sampling method. As a result, 77 valid responses were received. Descriptive statistics (e.g., mean, standard deviation) were used to identify the severity of AI’s impact on the quantity surveying profession. Factor analysis was used to categorize the impacts of AI on the quantity surveying profession. Partial least square-structural equation modeling (PLS-SEM) was used to determine the relationship between combined impacts of AI and its adoption among quantity surveying profession. Findings The results revealed that “maximize work efficiency to improve productivity” and “improve quantity take-off from drawings” were two most severe impacts of AI on the quantity surveying profession. The factor analysis’ results revealed 20 impacts were categorized into four components. The findings of PLS-SEM revealed that “adoption of skill and knowledge for communication and contractual issues” impacted most toward the adoption of AI among quantity surveying profession. Practical implications This study could assist QS in understanding the impacts of AI and hence the management for better procedures of incorporating AI into their practices to enhance efficiency of construction projects. Originality/value This study focused specifically on the impacts of AI on the quantity surveying profession solely by considering the relevant tasks that AI could perform for QSs. This is one of the first study adopting both factor analysis and PLS-SEM approaches in examining the impacts of AI on the quantity surveying profession. This study could add to the literature and benefit the quantity surveying profession.