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Article

Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of Artificial Intelligence-Based Solutions

1
Faculty of Management Studies, The ICFAI University, Baddi 174103, Himachal Pradesh, India
2
Center for Digital Technology Innovation and Entrepreneurship, Institute of Wenzhou, Zhejiang University, 325000 Wenzhou, China
*
Author to whom correspondence should be addressed.
Information 2025, 16(7), 555; https://doi.org/10.3390/info16070555 (registering DOI)
Submission received: 18 May 2025 / Revised: 21 June 2025 / Accepted: 24 June 2025 / Published: 29 June 2025
(This article belongs to the Special Issue Feature Papers in Information in 2024–2025)

Abstract

Organizational behavior examines the interactions of individuals and groups within businesses, while human resource management (HRM) focuses on enhancing workforce efficiency through recruitment, training, and employee relations. The success of an organization depends on the relationship between employee engagement and performance, as engaged individuals enhance productivity and innovation. This study aims to conduct a comprehensive bibliometric analysis of the academic research on the relationship between artificial intelligence (AI), employee engagement, and performance. This study highlights trends, countries, sources, and keywords in this field. The authors analyzed 11,291 articles in the first phase, 42,358 articles were analyzed in the second phase, and 606 articles were analyzed in the third phase. This study highlights the growth of the research in this area and identifies the most productive years and regional contributions. The citation analysis is used to identify the relevant research and renowned authors. This study also addresses ethical concerns related to the implementation of artificial intelligence (AI) in the workplace. This study indicates theme variations among national contributions, highlighting differing socio-cultural and theoretical perspectives on AI adoption in HRM, from behavioral leadership models to efficiency-oriented frameworks. In summary, this bibliometric study provides valuable insights into the evolution of the research topics related to AI’s impact on employee engagement and productivity, spanning multiple disciplines, such as psychology, organizational behavior, and computer science. It is relevant for the researchers, practitioners, and businesses interested in understanding and utilizing AI in the workplace.
Keywords: artificial intelligence; employee; engagement; performance; leadership; human resource artificial intelligence; employee; engagement; performance; leadership; human resource

Share and Cite

MDPI and ACS Style

Sharma, C.; Chanana, N.; Chen, H.-Y. Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of Artificial Intelligence-Based Solutions. Information 2025, 16, 555. https://doi.org/10.3390/info16070555

AMA Style

Sharma C, Chanana N, Chen H-Y. Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of Artificial Intelligence-Based Solutions. Information. 2025; 16(7):555. https://doi.org/10.3390/info16070555

Chicago/Turabian Style

Sharma, Chetan, Nisha Chanana, and Hsin-Yuan Chen. 2025. "Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of Artificial Intelligence-Based Solutions" Information 16, no. 7: 555. https://doi.org/10.3390/info16070555

APA Style

Sharma, C., Chanana, N., & Chen, H.-Y. (2025). Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of Artificial Intelligence-Based Solutions. Information, 16(7), 555. https://doi.org/10.3390/info16070555

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