Purpose In order to drive decision-making, manage teams and improve performance, leaders are increasingly encouraging employees to use AI. Despite its expanding popularity, the literature on its effects on employee behavior and well-being is lacking. This study addresses this gap by studying how AI leadership influences behavioral outcomes like quite quitting and job satisfaction and well-being indicators like emotional exhaustion and self-efficacy. The study also examines how work meaningfulness mediates this link and how trust in AI moderates it. Design/methodology/approach A cross-sectional survey design was utilized, gathering data from 539 personnel in the IT and IT services sector. Established scales were employed to assess study factors. We used structural equation modeling (SEM) with bootstrapping approaches to examine the hypothesized mediation and moderation effects on the data. Findings The findings demonstrated that AI-oriented leadership favorably impacted work meaningfulness, thus increasing self-efficacy and job satisfaction while decreasing quiet quitting and emotional tiredness. Trust in AI influenced these linkages, resulting in a more pronounced positive effect of AI-oriented leadership on meaningfulness and its indirect consequences on outcomes when trust in AI was elevated. Originality/value The existing literature mostly restricts Artificial Intelligence to productivity or technical acceptance, this research fundamentally shifts the narrative around AI in the workplace from replacement to augmentation. By integrating Self-Determination Theory (SDT), we demonstrate that AI-oriented leadership does not dehumanize work but rather enhances Work Meaningfulness by liberating employees from cognitive drudgery. The study further explores how technological trust alters the social exchange between leaders and employees.
Parray et al. (Thu,) studied this question.