AI‐Augmented Leadership: How, Why, and When Leaders' Collaboration With AI Enhances Team Performance
Pei Liu et al.
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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.