An Analytical Study on the Impact of Artificial Intelligence (AI) Adoption on Job Satisfaction Among Office Employees in the Lower Northern Region of Thailand

บทคัดย่อ

This study investigates employees’ acceptance of artificial intelligence (AI) and its influence on behavioral intention and job satisfaction in AI-integrated workplaces. Guided by the Technology Acceptance Model (TAM), the research examines perceived usefulness, perceived ease of use, subjective norm, self-efficacy, and attitude as predictors of AI adoption. A quantitative, causal-predictive, cross-sectional design was employed, and data were collected from 456 office employees in Thailand’s Lower Northern Region who had prior experience using workplace AI tools. Structural equation modeling (SEM) was used to assess the measurement and structural models, while regression analysis provided additional explanatory insights.

Results indicate that employees reported high levels of perceived usefulness, self-efficacy, subjective norm, and positive attitudes toward AI. Four TAM variables perceived usefulness, attitude toward AI, self-efficacy, and subjective norm had significant positive effects on behavioral intention, collectively explaining 31.4% of its variance. Perceived ease of use was not a significant predictor once other variables were accounted for, suggesting that experienced users prioritize performance benefits over usability simplicity. Findings related to job satisfaction show that employees who perceived AI as useful, confidence-enhancing, and aligned with workplace expectations reported higher satisfaction levels. Positive attitudes toward AI were also associated with improved job satisfaction, indicating that acceptance and satisfaction are mutually reinforcing in digitally transforming organizations. Conversely, uncertainty about AI’s relevance or low ease of use showed indirect negative associations with satisfaction, though these effects were weaker than performance-related determinants. Overall, the study demonstrates that AI adoption influences not only employees’ behavioral intentions but also their job satisfaction in meaningful ways. Performance-oriented perceptions, strengthened self-efficacy, and supportive workplace norms play central roles in promoting both satisfaction and sustained AI use. These insights highlight the need for targeted training, communication strategies, and organizational support systems to optimize AI integration and enhance employees’ work experiences.