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This is a Quantitative Study study.

September 24, 2025Open Access

Innovate, Transform, Succeed: Artificial Intelligence-Enabled Transformation Acceptance in Private Higher Education Institutions

Key Points

Positive relationships were found for perceived ease of use and self-efficacy on AI acceptance, emphasizing their significance.
A total of 573 surveys were distributed across various departments, resulting in a 78.7% response rate with 451 returned responses.
Structural equation modeling was utilized for data analysis, allowing comprehensive assessment of relationships among acceptance variables.
These findings highlight the importance of user-friendly AI tools and targeted training to enhance AI acceptance and foster innovation.

Abstract

This study examines the acceptance of artificial intelligence (AI)-enabled transformation in private higher education institutions, emphasizing its importance for enhancing operational efficiency and educational outcomes. As AI technologies rapidly evolve, understanding employees' acceptance becomes critical for successful implementation. The primary aim of this research is to identify the key factors influencing acceptance, including perceived ease of use, perceived usefulness, self-efficacy, and their mediated effects on employee attitudes. Data for the study were collected through a survey utilizing a purposive sampling technique to target staff members across various departments of selected institutions. A total of 573 surveys were distributed, with 451 returned responses, yielding a response rate of 78.7%. The data analysis was conducted using structural equation modeling (SEM), which allowed for a comprehensive assessment of the relationships among the variables. Hypothesis testing results revealed significant positive relationships for perceived ease of use, self-efficacy, and their mediating effect on attitude towards AI acceptance, while perceived usefulness showed a weaker, non-significant effect. The findings underscore the necessity for institutions to develop user-friendly AI tools, demonstrate tangible benefits, and improve employee self-efficacy through targeted training programs. Suggestions for future research include longitudinal studies to track changes in perceptions over time and cross-institutional comparisons to uncover contextual factors influencing acceptance. Overall, this study contributes to the existing literature on technology acceptance and offers practical implications for private higher education institutions seeking to navigate the complexities of AI integration successfully. Enhancing acceptance among employees will not only facilitate adoption but also promote a culture of innovation in the educational landscape.

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