The Non-Linear Impact of Artificial Intelligence on Leadership Dynamics

Abstract

Artificial intelligence (AI) is disrupting traditional leadership power dynamics by challenging expertise-based sources of authority. Drawing on power dependence theory and regulatory focus theory, this study explores how AI influences leaders’ perceived expertise threats and their subsequent behavioral responses, emphasizing the moderating role of regulatory focus. Study 1, using a two-wave survey of 159 employees, revealed a U-shaped relationship between AI deployment and employees’ perceived expert power, indicating that expert power is lowest at moderate levels of AI deployment. Study 2 extends these insights using a three-wave survey of 194 supervisors, revealing an inverted U-shaped relationship between AI deployment and leaders’ perceived expertise threats, with threat perceptions peaking at moderate levels of AI deployment. Additionally, we found that perceived expertise threats decrease empowerment behaviors while increasing self-interested behaviors. The results further show that leaders’ regulatory focus significantly moderates these relationships: leaders with a promotion focus are more effective at mitigating perceived threats and their behavioral consequences, whereas a prevention focus shows no significant impact. This study contributes to leadership research by uncovering non-linear power dynamics in the AI era and highlighting individual differences in moderating these effects.

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