Does Leader AI-Focused Attention Promote Employee Proactivity? A Work-Related Rumination Theory Perspective

With the increasing embeddedness of AI robots and other intelligent technologies in organizational workplaces, leader AI-focused attention has emerged as an important reference point for employees as they use and adapt to AI-related technologies. Drawing on work-related rumination theory, this study develops and tests an integrated mediation model to examine how leader AI-focused attention is related to employee proactive behavior through two parallel pathways: problem-solving pondering and affective rumination. It further investigates the moderating role of AI job role clarity. Based on structural equation modeling of multi-wave survey data from 514 employees, the results show that leader AI-focused attention positively predicts employees' problem-solving pondering and affective rumination. Problem-solving pondering is positively related to employee proactive behavior, whereas affective rumination is negatively related to employee proactive behavior. In addition, AI job role clarity positively moderates the relationship between leader AI-focused attention and problem-solving pondering; specifically, this positive relationship is stronger when employees report higher AI job role clarity. From the perspective of work-related rumination, this study extends the explanation of the psychological mechanisms linking leader AI-focused attention to employee proactive behavior. It also provides theoretical insights and practical implications for understanding the boundary condition of leaders' attentional signals in AI-related work contexts and for supporting employee proactive behavior.