UNDERSTANDING HOW AI-DRIVEN INNOVATIONS RESHAPE HUMAN RESOURCE MANAGEMENT AND INFLUENCE ORGANIZATIONAL EFFECTIVENESS

Authors

  • Calvin Nuril Musthofa Universitas Islam Nahdlatul Ulama Jepara, Indonesia

DOI:

https://doi.org/10.70764/gdpu-jihr.2025.1(1)-02

Keywords:

Digital Transformation, Operational Efficiency, Technology Adaptation

Abstract

Objective: This research aims to understand the use of Artificial Intelligence (AI) in the context of human resource management (HRM), identify the challenges of its integration, and explore its impact on operational efficiency, decision-making, and employee work experience. Research Design & Methods: This study used a qualitative approach through in-depth interviews and analysis of relevant literature. The data was thematically analyzed to explore employees' perceptions, hopes, and fears as well as the organization's strategy in adopting AI in HR. Findings: Findings show that AI has great potential in improving the effectiveness of HR management, especially in terms of process efficiency, decision-making accuracy, and personalization of employee experience. However, barriers such as lack of digital competency, reliance on conventional HR practices, and concerns about losing the human dimension remain crucial. Employees show mixed responses, ranging from enthusiasm for efficiency to anxiety about job security and dehumanization of work processes. Implications & Recommendations: This research recommends strengthening digital literacy and adaptive training for HR practitioners, developing ethical and human-centered AI integration policies, and the need for organizations to maintain a balance between technological efficiency and human touch in managerial practices. Contribution & Value Added: This research contributes to the conceptual and practical understanding of AI integration in HR management. The added value of this study is the presentation of a multidimensional perspective-both from the organization and employee side-in addressing digital transformation in the HR domain.

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Published

2025-07-15

Issue

Section

Articles