From Learning to Employment: A Bibliometric Review of AI's Role in Bridging HRM and Career Readiness

Authors

DOI:

https://doi.org/10.56294/dm20251229

Keywords:

Artificial Intelligence, Human Resource Management, Career Readiness, Bibliometric Analysis

Abstract

Introduction: The integration of artificial intelligence (AI) is transforming both human resource management (HRM) and educational pathways, yet a comprehensive understanding of the intellectual structure linking these domains remains underdeveloped. 
Objective: to map the intellectual structure and evolutionary trends of research on artificial intelligence (AI) at the intersection of human resource management (HRM) and career readiness.
Methods: A bibliometric analysis was performed on 208 documents retrieved from the Scopus database, covering the period from 2019 to 2025. The study utilized performance analysis, science mapping, and thematic evolution techniques, employing VOSviewer software to assess the intellectual landscape of the field.
Results: The analysis revealed a field characterized by rapid interdisciplinary growth, particularly from 2023 to 2025. Key findings show a significant increase in publications addressing ethical considerations and sustainable development. Three major thematic clusters emerged: Human-AI Collaboration (38,5 %), Ethical Frameworks (32,2 %), and Pedagogical Innovation (29,3 %). The most prominent topics were 'artificial intelligence', 'education', and 'human resource management', which formed the core of the research activity.
Conclusions:The study offers a comprehensive conceptual framework, highlighting the interplay between technological innovation, ethical governance, and human development. The findings provide valuable insights for researchers and practitioners in navigating the evolving landscape of AI-driven work and learning environments.

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2025-10-18

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1.
Indrasari M, Pamuji E, Raharja A, Setiadi T, Handayani T. From Learning to Employment: A Bibliometric Review of AI’s Role in Bridging HRM and Career Readiness. Data and Metadata [Internet]. 2025 Oct. 18 [cited 2025 Oct. 30];4:1229. Available from: https://dm.ageditor.ar/index.php/dm/article/view/1229