Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence
ISSN: 2040-8269
Article publication date: 4 January 2021
Issue publication date: 16 July 2021
Abstract
Purpose
The purpose of this paper is to examine the use of artificial intelligence (AI) in human resource management (HRM) in the Global South.
Design/methodology/approach
Multiple case studies of AI tools used in HRM in these countries in recruiting and selecting as well as developing, retaining and productively utilizing employees have been used.
Findings
With AI deployment in HRM, organizations can enhance efficiency in recruitment and selection and gain access to a larger recruitment pool. With AI deployment in HRM, subjective criteria such as nepotism and favoritism are less likely to come into play in recruitment and selection of employees. AI deployment in HRM also has a potentially positive impact on the development, retainment and productive utilization of employees.
Research limitations/implications
AI is an evolving technology. Most HRM apps have not gained enough machine learning capabilities with real-world experience. Some of them lack a scientific basis. AI in HRM thus currently affects only a tiny proportion of the population in the GS.
Practical implications
The paper explores the roles of AI in expanding recruitment pools. It also advances our understanding of how AI-based HIRM tools can help reduce biases in selecting candidates, which is especially important in the Global South. It also delves into various mechanisms by which AI helps in the development, retainment and productive utilization of employees.
Originality/value
We provide details of various mechanisms by which AI brings input and output efficiencies in recruitment and selection in these countries.
Keywords
Citation
Kshetri, N. (2021), "Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence", Management Research Review, Vol. 44 No. 7, pp. 970-990. https://doi.org/10.1108/MRR-03-2020-0168
Publisher
:Emerald Publishing Limited
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