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Artificial intelligence in human resource management: models for recruitment, training, performance, compensation, and retention
Department of Management, Apadana Institute of Higher Education.
Department of Management, Apadana Institute of Higher Education.
Department of Management, Payam Noor University.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Management, Industrial Design and Mechanical Engineering, Industrial Management. Department of Business Administration, University of Gothenburg.ORCID iD: 0000-0001-5336-827X
2026 (English)In: Frontiers in Artificial Intelligence, E-ISSN 2624-8212, Vol. 9, article id 1718244Article in journal (Refereed) Published
Abstract [en]

Introduction: In the era of rapid technological advancement, artificial intelligence (AI) has emerged as a transformative force across various industries, including human resource management (HRM). This study examines the application of AI in HRM systems, with a focus on recruitment, hiring, training, performance management, compensation, and human capital retention.

Methods: This study adopts a qualitative research approach. Experts in artificial intelligence and human resource management were identified, and data were collected through qualitative methods. The data were analyzed using thematic analysis.

Results: The findings reveal the introduction of AI application models across various HRM systems. These models demonstrate how AI enhances efficiency and effectiveness in key HR functions.

Discussion: The results highlight the transformative potential of AI in HRM by enabling data-driven decision-making and improving workforce planning. This research provides valuable insights for human resource professionals seeking to leverage AI to enhance organizational performance across industries.

Place, publisher, year, edition, pages
Frontiers , 2026. Vol. 9, article id 1718244
Keywords [en]
artificial intelligence; business management; compensation; human resource management; performance; recruitment; retention; training
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hig:diva-49421DOI: 10.3389/frai.2026.1718244ISI: 001695318500001PubMedID: 41728274Scopus ID: 2-s2.0-105030586012OAI: oai:DiVA.org:hig-49421DiVA, id: diva2:2042097
Available from: 2026-02-26 Created: 2026-02-26 Last updated: 2026-03-09Bibliographically approved

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Sorooshian, Shahryar

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