BIBLIOMETRIC ANALYSIS AND CRITICAL REVIEW OF THE ARTIFICIAL INTELLIGENCE ADOPTION FACTORS IN CONSULTING QUANTITY SURVEYING FIRMS

AI adoption will help Malaysian construction organisations, including Consulting Quantity Surveying (CQS) firms, cope with challenges and increase productivity. However, AI adoption by CQS firms faces adoption issues in Malaysia. Existing AI adoption studies discuss barriers in developed countries. Applying these studies' results in developing countries such as Malaysia is inappropriate, as construction industry practices and properties differ. Also, there is limited attention to factors affecting AI adoption. Existing studies on AI adoption in Malaysia are limited, and the stages of AI adoption have not been rigorously studied. The first objective of the study is to explore and categorise the factors of AI adoption and provide in-depth insights into the different AI adoption stages. The second objective is to identify 62 factors that affect the four stages of AI adoption and group them into four clusters. This study applied Systematic Literature Review (SLR) to identify and classify factor clusters based on the Diffusion of Innovation Theory and Technology Organisation Environment (TOE). The identified cluster of factors can be useful to decision-makers for conducting analyses of AI adoption stages and for formulating adoption strategies, by providing facts and observations within organisations. The review observes that factors affecting AI adoption stages vary across regions, due to governmental pressure, cultural differences, practices, and demographics.