Understanding the Nuances of How Followers Perceive AI Leadership

Abstract

Artificial intelligence (AI) technologies are increasingly integrated into organizational decision-making, raising important questions about how followers evaluate leadership enacted by AI systems. The present research examines how followers perceive human, AI, and AI-augmented (hybrid) leaders while considering the roles of decision-making transparency and situational context. Across two experimental vignette studies, participants evaluated leadership scenarios in which leader type (human, AI, AI-augmented) and decision-making transparency (high vs. low) were manipulated between subjects, while situational context (consideration vs. initiating structure) was manipulated within subjects. Study 1 (N = 281) and Study 2 (N = 420) assessed follower trust, satisfaction with the leader, and ratings of leader effectiveness. Results across studies indicated that human leaders generally elicited stronger relational reactions than AI leaders, particularly in terms of follower satisfaction. Decision-making transparency consistently increased follower trust and satisfaction across leader types. Perceptions of leader effectiveness were contingent on situational demands: AI leaders were evaluated more favorably in initiating structure contexts emphasizing task coordination, whereas human leaders received more favorable evaluations in consideration contexts emphasizing relational support relative to other leader types. AI-augmented leaders produced more moderate or stable evaluations across contexts. Study 2 further showed that when explicit leader characteristics were absent, followers relied more heavily on informational cues such as transparency when forming evaluations. Together, these findings suggest that follower responses to emerging leadership agents depend on relational expectations, transparency in decision processes, and alignment between leader capabilities and situational demands.