Malik, Ashish, Lirio, Pamela, Budhwar, Pawan, Nguyen, Mai and Fauzi, Muhammad Ashraf (2025). Artificial Intelligence (AI) in the World of Work: Bibliometric Insights and Mapping Opportunities and Challenges. Personnel Review ,
Abstract
Purpose: This editorial review presents a bibliometric account of the convergence of the fields of Artificial Intelligence (AI) and Human Resource Management (HRM) and an overview of the related contributions in this special issue. It also explores the expansive area where research on AI and HRM intersects, a domain experiencing rapid growth and transformation, faster than we envisaged. Design/methodology/approach: This substantive editorial employs a range of bibliometric analytical tools to present a state of knowledge on the topic and also provides an analytical overview of the contributions in this Special Issue. Findings: A thorough examination of scholarly publications spanning two decades illuminates the evolutionary path of themes, key contributors, seminal works, and emerging trends within this interdisciplinary sphere. Leveraging co-word analysis, we distill essential themes and insights from an extensive dataset of 654 journal publications curated from the Web of Science database. Our analysis underscores critical research domains, highlighting the nuanced interplay between HRM and AI. Originality/value: By integrating findings from the bibliometric analysis and the contributions from the papers in the Special Issue, we highlight and speculate where the field is heading and where scholars have crucial opportunities to contribute to going forward.
Publication DOI: | https://doi.org/10.1108/pr-12-2024-1061 |
---|---|
Divisions: | College of Business and Social Sciences > Aston Business School > Work & Organisational Psychology College of Business and Social Sciences > Aston Business School |
Additional Information: | Copyright © 2025, Emerald Publishing Limited. This author's accepted manuscript is deposited under a Creative Commons Attribution Non-commercial 4.0 International (CC BY-NC) licence. This means that anyone may distribute, adapt, and build upon the work for non-commercial purposes, subject to full attribution. If you wish to use this manuscript for commercial purposes, please contact permissions@emerald.com |
Uncontrolled Keywords: | artificial intelligence,Quantitative,HRM,bibliometrics,Human Resource Management,AI |
Publication ISSN: | 1758-6933 |
Last Modified: | 31 Mar 2025 17:41 |
Date Deposited: | 22 Jan 2025 17:00 |
Full Text Link: | |
Related URLs: |
https://www.eme ... -1061/full/html
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2025-02-03 |
Published Online Date: | 2025-02-03 |
Accepted Date: | 2024-12-06 |
Authors: |
Malik, Ashish
Lirio, Pamela Budhwar, Pawan ( ![]() Nguyen, Mai Fauzi, Muhammad Ashraf |