Artificial Intelligence and Its Influences on Enterprise Employees

Authors

  • Zuhao Yu Author

DOI:

https://doi.org/10.70693/4szm1p78

Keywords:

artificial intelligence, enterprise employees, job insecurity, organizational support, systematic literature review

Abstract

With the rapid advancement of artificial intelligence (AI), particularly generative artificial intelligence (Generative AI), its application in enterprises has become increasingly widespread, exerting significant influences on employees’ work efficiency and psychological well-being. This study adopts a systematic literature review to examine peer-reviewed journal articles published between January 2024 and May 2026. After screening, coding and synthesizing a corpus of 186 relevant domestic and international studies, this paper systematically explores the multifaceted impacts of AI on enterprise employees and develops a corresponding theoretical analytical framework. The findings indicate that AI exerts both positive and negative effects on employees, and such impacts vary substantially across employee groups. On the one hand, AI enhances employees’ productivity and organizational operational efficiency by automating repetitive and routine tasks. On the other hand, it increases employees’ perceptions of job insecurity, thereby negatively affecting job satisfaction and psychological well-being. In addition, the impact of AI varies across organizational levels: frontline employees face greater risks and challenges than middle and senior managers. The review further reveals that organizational AI training and transparent algorithm governance can effectively alleviate employees’ job insecurity and mitigate the negative consequences associated with AI-driven organizational transformation. By integrating recent research findings, this study enriches the theoretical understanding of the relationship between artificial intelligence and enterprise employees. It also provides practical implications for organizations seeking to advance intelligent transformation and optimize human resource management.

Downloads

Published

2026-08-27

Issue

Section

Articles