The Role of Artificial Intelligence in Transforming Human Resource Management: A Theoretical Perspective

Olga Tsiourva () and Fotis Vouzas
Additional contact information
Olga Tsiourva: University of Macedonia
Fotis Vouzas: University of Macedonia

A chapter in A Human-Centered Approach to Quality and Excellence in Management, 2025, pp 137-149 from Springer

Abstract: Abstract The article explores the theoretical implications of integrating artificial intelligence (AI) into human resource management (HRM) and proposes a framework outlining potential transformations in HR practices. It examines how AI can enhance efficiency, decision-making, and organizational performance by analyzing traditional HR functions through a theoretical lens. Using a literature review and theoretical analysis, the study delves into AI applications in recruitment, employee engagement, performance management, and training. Ethical concerns such as bias, fairness, and data privacy are also addressed, emphasizing the need for balanced integration. The proposed framework highlights key components and relationships in AI-enhanced HRM, providing a structured understanding of the subject. By synthesizing existing research, the study identifies theoretical constructs and challenges linked to AI in HRM. It serves as a guide for future empirical research and practical applications, emphasizing that AI should complement human decision-making rather than replace it. The article contributes to both academic discourse and practical insights for HR professionals, fostering evidence-based adoption of AI technologies while addressing ethical and organizational concerns.

Keywords: Artificial intelligence; Human resource management; AI integration; HRM theories; Recruitment; Performance management; Employee engagement; Ethical considerations; Data-driven HR (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:prbchp:978-3-032-00063-7_7

Ordering information: This item can be ordered from
http://www.springer.com/9783032000637

DOI: 10.1007/978-3-032-00063-7_7

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().