Aug 2026· Frontiers in Psychology· Vol 17· 0 citations· 82 references
Medicine
TL;DR
It is proposed that, from employees’ perspective, AI reliance is associated with higher levels of involution through elevated performance expectations and anxiety, and the importance of protecting employee wellbeing, communicating realistic performance expectations, and maintaining workplace social capital when implementing AI in digitally enabled organizations.
Abstract
The rapid integration of artificial intelligence (AI) into organizational contexts is reshaping how employees work, interact, and respond to changing workplace dynamics. Although AI is often expected to improve efficiency and reduce workload, emerging evidence points to a potential dark side, as AI adoption may intensify competitive pressure within organizations. Motivated by this paradox, this study examines how AI reliance may erode workplace social capital by fostering involution—an excessive and inefficient form of competition characterized by escalating effort and diminishing returns. This research focuses on digitally enabled and highly competitive workplace settings, where employee performance and outputs are more visible, transparent, and comparable. We propose that, from employees’ perspective, AI reliance is associated with higher levels of involution through elevated performance expectations and anxiety. Using survey data from employees in China, the study hypotheses were tested using structural equation modeling. The results support the proposed model and indicate a significant sequential mediation pattern linking AI reliance, performance expectations, employee anxiety, and workplace involution. Notably, the direct relationship between AI reliance and involution is not significant, suggesting that AI reliance is associated with employees’ defensive competitive behavior primarily through employees’ perception of external evaluative pressures and internal psychological responses. These findings highlight the unintended social consequences of AI adoption in organizations, and underscore the importance of protecting employee wellbeing, communicating realistic performance expectations, and maintaining workplace social capital when implementing AI in digitally enabled organizations.
This study investigates the efficiency paradox of AI, emphasizing the impact of technical optimization on human values, social cohesiveness, and workplace culture and indicates that the ethical and human-centric integration of AI is crucial to ensure that efficiency gains align with inclusivity, justice, and the maintenance of social well-being in contemporary workplaces.
Nandini Aquila Lukito, Nazwa Sabila· International Journal Admini...· 0 citations
It is concluded that while AI offers significant opportunities for improving HR effectiveness, organizational performance, and employment relations, successful implementation requires a balanced approach that integrates technological innovation with human-centered management practices and responsible workplace governance.
Habiganuchi Godfrey Bekwe, Nathaniel A. Ngerebara· International journal of res...· 0 citations
A moderated mediation model is developed in which perceived work meaningfulness acts as the mediator and job complexity serves as the moderator in the relationship between AI usage and employee resilience, showing that AI usage positively predicted employee resilience, and perceived work meaningfulness mediated this relationship.
Yuanyuan Ji, Huaming Wu· Frontiers in Psychology· 0 citations
This paper examines how AI reshapes managerial decision-making by distinguishing decision augmentation from decision automation, and considers the governance tensions between centralized and decentralized approaches to AI deployment, as well as identifying the leadership competencies that gain value once routine managerial tasks are delegated to algorithmic systems.
R. Narenderajan· Scholedge International Jour...· 0 citations
This paper aims to examine the relationship between employees' use of artificial intelligence (AI) for work and digital-enabled innovative performance (DEIP) from the perspective of employee engagement and trust in AI. Based on these perspectives, this study identifies specific solutions for achieving high levels of DEIP.
Drawing on job demands-resources (JD-R) theory and analyzing data from 431 employees, this paper proposes a research model to investigate how employee AI use affects employees' DEIP through partial least squares structural equation modeling and highlights the configurations of causal conditions associated with DEIP through fuzzy-set qualitative comparative analysis (fsQCA).
The results show that AI use for work exerts the strongest positive impact on employees' behavioral engagement, followed by emotional and cognitive engagement. Employee engagement (three types mention before) play a partial mediating role between work-related AI and DEIP. Furthermore, both human-like and functionality trust in AI positively moderate the relationship between work-related AI and behavioral engagement. Finally, a total of four solutions leads to a high level of DEIP.
Organizations should enhance employees' engagement and trust in AI through training and supportive implementation strategies. Managers should adopt context-sensitive approaches that align AI use, engagement and trust to improve DEIP.
Firstly, this study enriches the literature on DEIP and JD-R theory by exploring the AI-performance link via employee engagement. Secondly, this paper supplements work-related AI literature by clarifying AI trust's boundary conditions. Thirdly, this paper contributes to the performance literature by identifying key solutions for DEIP from a configuration perspective.
Liang Ma, Zhihao Qi, Xin Zhang et al.· Internet Research· 0 citations
This study explains how employees translate the day-to-day value they derive from generative artificial intelligence into employees' perceived insider status and knowledge sharing behavior, and finds that emotional value is positively associated with perceived insider status, conditional value is negatively associated with perceived insider status, and functional and epistemic value show no direct associations.
Mai Nguyen, Tuan Phong Nham, Danish Mehraj et al.· Journal of Enterprise Inform...· 0 citations