Job Stress and Individual Creativity: A Screen-Based Partial Least Squares Structural Equation Modeling Protocol for AI-Enabled Workplaces.

The increasing use of artificial intelligence (AI) in organizations is reshaping employees' job demands, leadership perceptions, and opportunities for creativity. Drawing on the Job Demands-Resources (JD-R) model and Social Learning Theory, this study examines whether employees' perceptions of ethical leadership mediate the relationship between job stress and individual creativity, and whether organizational AI embeddedness amplifies this relationship. Using partial least squares structural equation modeling (PLS-SEM) with 5,000 bootstrap resamples, the findings show that job stress negatively influences ethical leadership perception, while ethical leadership perception positively affects creativity. Job stress was not directly related to creativity; instead, ethical leadership perception served as a significant indirect pathway. In addition, organizational AI embeddedness strengthened the relationship between perceptions of ethical leadership and creativity. These findings suggest that creativity in AI-enabled workplaces is shaped less by technology itself and more by organizational psychological mechanisms. Organizations seeking to enhance creativity during digital transformation should therefore manage job stress and foster ethical leadership environments, rather than focusing solely on AI implementation. This protocol uses the empirical model as a worked example for demonstrating a reproducible survey-to-PLS-SEM workflow.