Panda, Gayatri, Dash, Manoj Kumar, Samadhiya, Ashutosh, Kumar, Anil and Mulat-weldemeskel, Eyob (2024) Artificial intelligence as an enabler for achieving human resource resiliency: Past literature, present debate and future research directions. International Journal of Industrial Engineering and Operations Management, 6 (4). pp. 326-347. ISSN 2690-6090
Artificial intelligence as an enabler for achieving human resource resiliency- past literature, present debate and future research directions.pdf - Published Version
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Abstract
Purpose
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.
Design/methodology/approach
The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.
Findings
The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.
Research limitations/implications
The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.
Originality/value
The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.
Item Type: | Article |
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Keywords: | Artificial intelligence | Human resources | Resiliency | Employee engagement | Performance | Big data analytics |
Subjects: | Social Sciences and humanities > Business, Management and Accounting > Human Resource Management Physical, Life and Health Sciences > Computer Science Social Sciences and humanities > Social Sciences > Social Sciences (General) |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Dharmveer Modi |
Date Deposited: | 26 Nov 2024 15:34 |
Last Modified: | 26 Nov 2024 15:34 |
Official URL: | https://doi.org/10.1108/IJIEOM-05-2023-0047 |
URI: | https://pure.jgu.edu.in/id/eprint/8820 |
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