| Abstract [eng] |
This research examines the impact of Artificial Intelligence (AI) product use on employee wellbeing at work, considering the moderating role of job autonomy and the mediating effect of technostress. The Master thesis consists of four main parts: a scientific literature review, empirical research methodology, analysis of empirical results, and conclusions and recommendations. The scientific literature review aimed to clarify the theoretical concepts of AI product use, employee well-being, job autonomy, and technostress in the workplace and identify their interrelationships. Based on the literature review, the research methodology was developed, and conceptual research was created. The data was collected using a structured questionnaire survey from 261 respondents working in organizations that use AI tools in their daily activities. Validated measurement scales were applied to assess AI product use, employee well-being, job autonomy, and technostress. Data analysis was conducted using the IBM SPSS Statistics 5.0 program, including descriptive statistics, reliability analysis, correlation analysis, regression analysis, and moderated mediation analysis using Hayes’ PROCESS macro (Model 14). The research findings indicate that AI product use does not have a statistically significant direct effect on employee well-being at work. However, AI product use is positively associated with technostress, which negatively affects employee well-being. The results confirm that technostress mediates the relationship between AI product use and employee well-being. Additionally, job autonomy was found tosignificantly moderate this indirect relationship. The conclusions and recommendations summarize the main concepts of literature analysis with the results of performed research. The findings of this study contributed to the model of the JD-R in the context of AI-supported work and could give some practical guidelines for organizations seeking to implement AI in a way that supports employee well-being. |
