AI as Co-Leader: Effects of Human Consideration and AI Structure Behaviors on Leadership Effectiveness and Neural Activation

Abstract

With rapid technological advancements, AI has emerged as a potential performer of some leadership functions, supplementing or even substituting certain human leadership. The collaborative leadership dynamics between humans and AI remain underexplored. This study investigated the effects of human consideration (high versus low) and AI structure (high versus low) behaviors on task performance, subjective experiences, and neural activation in a human–AI co-lead scenario. A total of 80 participants engaged in quality inspection tasks that were co-led by human and AI leaders, with 20 participants randomly allocated to each behavior combination. The results revealed that high AI structure was associated with increased job-related satisfaction, employee engagement, and leader trust, while low AI structure slightly facilitated task completion speed (about 6.80%). High human consideration increased the trust in and satisfaction with the human leader. Overall, the combination of high consideration in the human leader and high structure in the AI leader enhanced leadership effectiveness and diversification of work methods (with 30% of participants choosing inspection methods other than AI suggestions). Low-structure AI leader behavior led to increased neural activation during the human-leading process in the prefrontal cortex, which was associated with increased attention, motivation, and semantic processing.

Keywords:

• AI
• leadership
• initiating structure and consideration
• human–AI collaboration
• neuroleadership

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was funded by National Natural Science Foundation of China 71942005.

Notes on contributors

Xiaojun Lai

Xiaojun Lai received her B.S. degree in Industrial Engineering from Tsinghua University, China, in 2019. She is currently pursuing the Ph.D. degree in the Department of Industrial Engineering, Tsinghua University. Her research interests include artificial intelligence and management, human-computer interaction, and human factors engineering.

Pei-Luen Patrick Rau

Pei-Luen Patrick Rau received his Ph.D. degree in industrial engineering from Perdue University, USA. He is a Professor in the Department of Industrial Engineering, Tsinghua University, China. His research areas include human factors engineering, human–computer interaction, cross-cultural design, design for older people, and service design and evaluation.