AI‐Augmented Leadership: How, Why, and When Leaders' Collaboration With AI Enhances Team Performance

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Authors: Pei Liu, Daniel I. Watts, Xin Li, Xiaotian Wang, Aimei Li
Cited by: 1
References: 108

Abstract

ABSTRACT With the growing integration of intelligent machines, leaders are increasingly collaborating with artificial intelligence (AI) to enhance their leadership effectiveness. The effects on leaders' teams, including how, why, and when leader‐AI collaboration contributes to team performance, however, remain inadequately understood. Drawing from the model of work role performance, this study theorizes that leader‐AI collaboration can support distinctive collective role‐based functions (i.e., reducing team role overload, enhancing team reflexivity, and improving team role breadth self‐efficacy). These role‐based functions are posited to contribute significantly to team performance. Furthermore, we propose that leader age may amplify the positive relationships between leader‐AI collaboration and each of the three team role‐based functions. Across two multi‐source and multi‐wave surveys, our findings provide empirical support for the mediating roles of team reflexivity and team role breadth self‐efficacy in the relationship between leader‐AI collaboration and team performance. However, the mediating role of team role overload yielded mixed results. Additionally, leader age strengthened the positive relationships between leader‐AI collaboration and both team reflexivity and team role breadth self‐efficacy. These results underscore the benefits of leader‐AI collaboration for teams and the potential advantages of older leaders in the digitalization era.

Fields of Study & Subjects

Team Dynamics and Performance Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Journal of Organizational Behavior
Publisher
Wiley
Volume
47
Issue
7
Pages
1228–1254
Publication date
20 February 2026
Language
EN