Factors Influencing Artificial Intelligence Adoption among Employees in Malaysia’s Private Sector

The adoption of Artificial Intelligence (AI) in the private sector is increasingly transforming workplace practices, necessitating an understanding of the factors influencing its acceptance and usage among employees. This study explores the relationships between key determinants, performance expectancy, effort expectancy, social influence, and facilitating conditions and their impact on the actual use of AI, mediated by behavioral intention. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this study utilizes a quantitative approach to collect and analyze data from employees in Malaysia's private sector. The findings reveal that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence behavioral intention, which, in turn, mediates their effects on actual AI usage. Facilitating conditions also directly affect actual use, highlighting the importance of organizational support in fostering adoption. The study provides critical insights for private-sector organizations, policymakers, and practitioners aiming to enhance AI acceptance and integration in workplace environments. These results contribute to the existing literature by offering a holistic understanding of the factors driving AI adoption and use, with practical implications for improving workforce readiness and technological implementation strategies.