Humanizing GenAI at work: bridging the gap between technological innovation and employee engagement

独创性 员工敬业度 心理学 调解 自举(财务) 价值(数学) 调解 桥接(联网) 多级模型 知识管理 背景(考古学) 透视图(图形) 社会心理学 业务 公共关系 社会学 政治学 计算机科学 创造力 财务 计算机网络 社会科学 生物 机器学习 古生物学 人工智能
作者
Alba Manresa,Ammar Sammour,Marta Mas‐Machuca,Weifeng Chen,David Botchie
出处
期刊:Journal of Managerial Psychology [Emerald Publishing Limited]
标识
DOI:10.1108/jmp-05-2024-0356
摘要

Purpose This paper seeks to explore the influence of generative artificial intelligence (GenAI) on employee performance in the workplace, viewed from a managerial perspective. It concentrates on key elements such as employee engagement, trust in GenAI and attitudes toward its implementation. This exploration is motivated by the ongoing evolution of GenAI, which presents managers with the crucial task of understanding and integrating this technology into their strategic frameworks. Design/methodology/approach We collected 251 responses from managers and senior managers representing companies that have embraced GenAI in Spain. A hierarchical regression analysis was employed to examine the hypotheses. Subsequently, mediating effects and moderated mediation effects were scrutinized using the bias-corrected bootstrapping method. Findings The data analysis suggests a significant enhancement in employee engagement and performance from a managerial perspective, attributed to improved attitudes and trust toward the adoption of GenAI. This conclusion is drawn from our research conducted with samples collected in Spain. Notably, our findings indicate that while positive attitudes toward GenAI correlate with enhanced engagement and performance, there exists a weakening effect on the significant positive impact of GenAI adoption in the workplace. This suggests that GenAI is still in its early stages of adoption within these companies, necessitating additional time for managers to develop greater confidence in its efficacy. Originality/value This study represents one of the pioneering investigations centered on the implementation of GenAI within the workplace context. It contributes significantly to the existing body of literature concerning the stimulus-organism-response (S-O-R) model in technology innovation adoption within work environments.
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