Bridging the AI gap: how AI-oriented leadership empowers non-technical employees in AI-based innovation engagement

桥接(联网) 心理学 公共关系 知识管理 管理 社会学 政治学 计算机科学 经济 计算机网络
作者
Zhao Guang-jun,Nilesh Kumar,Changfeng Wang,Zhiqiang Liu
出处
期刊:Leadership & organization development journal [Emerald Publishing Limited]
卷期号:: 1-17
标识
DOI:10.1108/lodj-03-2025-0177
摘要

Purpose In the context of AI-based innovation, non-technical employees often perceive artificial intelligence as a threat to job security and role relevance, leading to uncertainty and disengagement. This study investigates how AI-oriented leadership enhances non-technical employees’ psychological safety and self-extension, thereby promoting their engagement in AI-based innovation. Design/methodology/approach A time-lagged cross-sectional survey design was employed, gathering responses from 456 non-technical employees and 78 leaders in manufacturing firms in China using convenience sampling. Data were analyzed using the SPSS PROCESS macro to test the hypothesized relationships and mediation model. Findings The results reveal that AI-oriented leadership positively predicts psychological safety and self-extension among non-technical employees. Furthermore, psychological safety and self-extension sequentially mediate the relationship between AI-oriented leadership and AI-based innovation engagement, supporting the proposed serial mediation model. Practical implications The findings highlight the importance of leadership practices that promote psychological safety and identity alignment in AI adoption. Organizations should prioritize not only technical training but also AI-oriented leadership strategies that empower non-technical employees to explore and engage with AI technologies confidently. Originality/value This study contributes to the emerging literature on AI-oriented leadership by identifying psychological safety and self-extension as key cognitive mechanisms through which leadership enables innovation. It offers a human-centered approach to driving AI-based innovation, especially among traditionally underrepresented non-technical staff.
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