Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Applying Artificial Intelligence (AI) technologies in Human Resource Management (HRM) contributes to more capability, diverse insights, and analytical support to enhance people management. This study presents an integrated overview of the research trends through a PRISMA-compliant bibliometric review. We have analysed a dataset of 247 Scopus-indexed publications between the earliest available date (1993) till 2020 to understand the key themes and the related research focus. The study shows that most research has been conducted in recent years, with 70% of relevant papers published since 2010. The key themes subscribed to the development of this literature have been called out. The outcome of term co-occurrence analysis highlights majority research related to AI in HRM focuses on resource allocation, talent acquisition, and training and development. The research spotlights significant areas attributed to AI in HR functions that warrant additional research. Deliberation of research gaps and recommendations on future direction is also provided.
Dr. Mandeep Kaur. 2026. \u201cResearch on Artificial Intelligence in Human Resource Management: Trends and Prospects\u201d. Global Journal of Management and Business Research - A: Administration & Management GJMBR-A Volume 23 (GJMBR Volume 23 Issue A5): .
Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
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Total Score: 154
Country: United States
Subject: Global Journal of Management and Business Research - A: Administration & Management
Authors: Dr. Mandeep Kaur, Dr. Rekha AG, Dr. Resmi AG, Dr. Franco Gandolfi (PhD/Dr. count: 4)
View Count (all-time): 107
Total Views (Real + Logic): 1139
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Publish Date: 2026 01, Fri
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Neural Networks and Rules-based Systems used to Find Rational and
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Applying Artificial Intelligence (AI) technologies in Human Resource Management (HRM) contributes to more capability, diverse insights, and analytical support to enhance people management. This study presents an integrated overview of the research trends through a PRISMA-compliant bibliometric review. We have analysed a dataset of 247 Scopus-indexed publications between the earliest available date (1993) till 2020 to understand the key themes and the related research focus. The study shows that most research has been conducted in recent years, with 70% of relevant papers published since 2010. The key themes subscribed to the development of this literature have been called out. The outcome of term co-occurrence analysis highlights majority research related to AI in HRM focuses on resource allocation, talent acquisition, and training and development. The research spotlights significant areas attributed to AI in HR functions that warrant additional research. Deliberation of research gaps and recommendations on future direction is also provided.
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