HRMARS - The construction industry is undergoing significant digital transformation, driven by the increasing adoption of advanced technologies such as artificial intelligence (AI)-powered cloud platforms to improve operational efficiency, workforce coordination, and project delivery. As construction projects become more complex and data-intensive, organizations are increasingly relying on AI-enabled cloud solutions to support real-time decision-making and enhance employee performance. However, despite this growing momentum, the successful adoption of such technologies remains inconsistent, largely due to variations in technological readiness and organizational preparedness. Addressing this gap, this conceptual paper proposes a framework that examines how key technological factors—namely technological complexity, system compatibility, and perceived relative advantage—influence employee job performance through AI-powered cloud platform adoption readiness. The framework conceptualizes adoption readiness as a mediating mechanism that explains how technological conditions translate into workplace performance outcomes. The novelty of this study lies in integrating technology adoption readiness with employee job performance within the construction context, thereby extending existing digital transformation and technology acceptance literature from a social science perspective. By focusing on employee-level performance implications, this paper contributes theoretically to the emerging discourse on AI-enabled work systems. It offers practical insights for construction firms, technology providers, and policymakers seeking to strengthen digital readiness and workforce effectiveness. Future empirical research is recommended to validate and refine the proposed framework across different organizational and industrial settings.
Qianglong et al. (Fri,) studied this question.