Artificial intelligence in human resource management: models for recruitment, training, performance, compensation, and retention

Meysam Safshekan; Ardalan Feili; Ali Shojaeifard; Shahryar Sorooshian

doi:10.3389/frai.2026.1718244

Artificial intelligence in human resource management: models for recruitment, training, performance, compensation, and retention

Front Artif Intell. 2026 Feb 6:9:1718244. doi: 10.3389/frai.2026.1718244. eCollection 2026.

Authors

Meysam Safshekan¹, Ardalan Feili¹, Ali Shojaeifard², Shahryar Sorooshian^{3

4}

Affiliations

¹ Department of Management, Apadana Institute of Higher Education, Shiraz, Iran.
² Department of Management, Payam Noor University, Tehran, Iran.
³ Department of Business Administration, University of Gothenburg, Gothenburg, Sweden.
⁴ Faculty of Engineering and Sustainable Development, University of Gävle, Gävle, Sweden.

Abstract

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.

Keywords: artificial intelligence; business management; compensation; human resource management; performance; recruitment; retention; training.