The Intelligent Human Resource Management System: Enhancing Corporate Talent Competitiveness

Shuang Liu
Additional contact information
Shuang Liu: WQKX (Wanqi Qianxiao), Beijing 100002, China

Frontiers in Management Science, 2025, vol. 4, issue 4, 89-95

Abstract: In the face of intensifying market competition, enterprises are confronted with increasing demands for talent and more rigorous requirements for talent management. Traditional human resource management methods are no longer capable of meeting the modern enterprises’ need for efficient and precise talent management. This paper introduces an Intelligent Human Resource Management System (IHRMS) based on big data analysis and artificial intelligence technology. It aims to comprehensively enhance corporate talent competitiveness through intelligent recruitment, performance management, and employee development modules. Through theoretical analysis and case studies, this paper demonstrates the application effects of IHRMS in various enterprises. The research findings indicate that IHRMS can significantly improve recruitment efficiency, with an average increase of 40%. Moreover, employee satisfaction and loyalty are also significantly enhanced, with an average increase of over 30%. Additionally, IHRMS strengthens corporate talent competitiveness by optimizing performance management and employee development paths. This paper also explores the implementation strategies and recommendations for IHRMS, providing references for enterprises to better adapt to the human resource management demands of the digital age.

Keywords: intelligent human resource management; big data analysis; artificial intelligence; talent competitiveness; recruitment efficiency; employee satisfaction; performance management; employee development; digital human resources; SMEs application (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.paradigmpress.org/fms/article/view/1702/1530 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bdz:frmans:v:4:y:2025:i:4:p:89-95

DOI: 10.63593/FMS.2788-8592.2025.07.008

Access Statistics for this article

More articles in Frontiers in Management Science from Paradigm Academic Press
Bibliographic data for series maintained by Editorial Office ().