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Exploring The Landscape: A Literature Review Of Ai'S Impact On Human Resource Management

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  • Daniel-Florin Daniloaia

    (Alexandru Ioan Cuza University of Iasi, Romania)

Abstract

This article explores literature and finds the transformative impact of artificial intelligence (AI) on human resource management (HRM), highlighting its applications and benefits across various HR functions. AI enhances recruitment, training, performance management, and compensation by automating routine tasks and providing advanced analytics. This allows HR professionals to focus on strategic decision-making and personalized employee engagement. Despite challenges such as data privacy concerns and algorithmic bias, AI improves efficiency, accuracy, and employee satisfaction. The article emphasizes the need for balancing technological advancements with ethical considerations to ensure AI complements rather than replaces human skills.

Suggested Citation

  • Daniel-Florin Daniloaia, 2024. "Exploring The Landscape: A Literature Review Of Ai'S Impact On Human Resource Management," Jean Monnet Chair EU Public Administration Integration and Resilience Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 0, pages 15-22, June.
    • Handle: RePEc:aic:ejpair:y:2024:v:06:p:15-22
    as

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    References listed on IDEAS

    as
    1. Chunhao Ma & Jian Ye, 2022. "Linking artificial intelligence to service sabotage," The Service Industries Journal, Taylor & Francis Journals, vol. 42(13-14), pages 1054-1074, October.
    2. Dominik K. Kanbach & Louisa Heiduk & Georg Blueher & Maximilian Schreiter & Alexander Lahmann, 2024. "The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective," Review of Managerial Science, Springer, vol. 18(4), pages 1189-1220, April.
    3. Anna Lena Hunkenschroer & Christoph Luetge, 2022. "Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda," Journal of Business Ethics, Springer, vol. 178(4), pages 977-1007, July.
    4. Qingquan Tony Zhang & Beibei Li & Danxia Xie, 2022. "Alternative Data and Artificial Intelligence Techniques," Palgrave Studies in Risk and Insurance, Palgrave Macmillan, number 978-3-031-11612-4, November.
    5. Tania Babina & Alex X. He & Anastassia Fedyk & James Hodson, 2022. "Artificial Intelligence, Firm Growth, and Product Innovation," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    6. Ariel K. H. Lui & Maggie C. M. Lee & Eric W. T. Ngai, 2022. "Impact of artificial intelligence investment on firm value," Annals of Operations Research, Springer, vol. 308(1), pages 373-388, January.
    7. Ashish Malik & Praveena Thevisuthan & Thedushika Sliva, 2022. "Artificial Intelligence, Employee Engagement, Experience, and HRM," Springer Texts in Business and Economics, in: Ashish Malik (ed.), Strategic Human Resource Management and Employment Relations, edition 2, pages 171-184, Springer.
    8. Mengfan Li & Yongping Xie & Yuge Gao & Yanan Zhao, 2022. "Organization virtualization driven by artificial intelligence," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 633-640, May.
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