ARTIFICIAL INTELLIGENCE ADOPTION ACROSS EMPLOYMENT SECTORS: A COMPARATIVE STUDY

Abstract

Artificial intelligence has become a central component in organizational operations due to its rapid technological advancement. The increasing demand for digital competencies in the workplace has made artificial intelligence become more significant in Industrial Revolution (IR) 4.0. This study aimed to examine the differences in artificial intelligence adoption across employment sector among UiTM sports graduates.  A quantitative cross sectional research design was selected involving 369 employed UiTM sports graduates. Respondents were selected using a stratified random sampling. Data were collected using a structured questionnaire that consisting of seven items on artificial intelligence adoption adapted from previous research. An independent sample t-test was used to determine the differences of artificial intelligence adoption between public and private organizations. The findings indicate a non-significant difference in artificial intelligence adoption across employment sector (p = 0.11 > 0.05). The result suggests that both sectors have increasingly adopting artificial intelligence into workplace, resulting in similar utilization of digital technologies in completing task efficiently. This finding also emphasizes that organizational initiatives like upskilling and reskilling program contributed to the comparable integration of artificial intelligence. Additionally, the growing national emphasis on digital transformation and inclusive artificial intelligence development further supports balance technological adoption across public and private organization. With that, this study contributes empirical evidence to the existing body of literature on artificial intelligence and graduate employability within the Malaysian context. Practically, this study may assist organizations, educational institutions, and policymakers in promoting effective artificial intelligence adoption and digital competency development in the organization. Future studies are recommended to include broader graduate population and other variables in examining the adoption of artificial intelligence within a workplace.