Intention to Use Generative AI for Vocational College Administration

Abstract

The increasing adoption of Generative Artificial Intelligence (GenAI) has transformed educational administration by supporting decision-making, information management, and organizational efficiency. Despite its growing importance, limited research has examined the factors influencing GenAI adoption among vocational college administrators, particularly from a governance and policy perspective. This study investigates the determinants of administrators’ intention to use and actual use behavior of GenAI in vocational college administration by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with Trust, Privacy Concern, and Institutional Policy Fit. A quantitative cross-sectional survey was conducted with 330 administrators and deputy directors of private vocational colleges in Thailand. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that Social Influence, Trust, Privacy Concern, and Institutional Policy Fit significantly influenced Behavioral Intention to use GenAI. In contrast, Performance Expectancy, Effort Expectancy, and Facilitating Conditions did not significantly affect Behavioral Intention. Behavioral Intention emerged as the strongest predictor of actual Use Behavior, while Facilitating Conditions exerted a significant direct effect on use behavior. The proposed model demonstrated substantial explanatory power, accounting for 82.8% of the variance in Behavioral Intention and 76.1% of the variance in Use Behavior. Predictive assessment further confirmed the model’s satisfactory predictive capability. The study contributes to technology acceptance literature by demonstrating that governance-oriented factors play a more influential role than traditional technology-related perceptions in explaining GenAI adoption among educational administrators. Unlike conventional UTAUT assumptions that emphasize usefulness and ease of use, the findings suggest that trust, privacy awareness, social endorsement, and policy alignment are critical determinants of GenAI acceptance in administrative contexts. Practically, the results highlight the importance of establishing clear institutional policies, strengthening AI governance mechanisms, and promoting responsible AI practices to facilitate sustainable GenAI implementation in vocational education institutions.