A Theoretical framework for the adoption of artificial intelligence technologies in the construction industry.

Abstract

Despite the extensive research on the applications of Artificial Intelligence (AI) technologies in the construction industry, little attention has been given to the theoretical perspective on varying levels of AI adoption by the industry stakeholders. This research aims to address this gap by proposing a theoretical framework for understanding the adoption of AI technologies in the construction industry. The framework was developed through a review of literature, and it draws on four underpinning theories, namely: the Technology–Organisation–Environment (TOE) framework, the Technology Acceptance Model (TAM), the Innovation Diffusion Theory (IDT) and the Stakeholder Theory (SKT). The TOE framework and IDT shape the influencing factors at the macro-level, while the TAM captures the factors at the micro-level along with SKT for defining the relevant stakeholders of the AI adoption in the construction industry. By connecting individual, organisational, and industrial factors at macro- and micro-levels that impact AI adoptions in the industry, the framework provides a better understanding of the complex interplay of the respective factors in informing future research.