Home / Volume 5, Issue 2 / Artificial Intelligence: A Tool for Optimizing Talent Acquisition Open access · CC BY-NC 4.0
Research Paper Volume 5 Issue 2 460 - 471 March 19, 2022

Artificial Intelligence: A Tool for Optimizing Talent Acquisition

Lead author · Corresponding
Dr. Krishan Lal Grover
Associate Professor at Department of Commerce, Sri Guru Hari Singh College, Sri Jiwan Nagar (Sirsa), Haryana, India.
View PDF Full text DOIhttps://doij.org/10.10000/IJLMH.112872
Abstract

In the new phase of Industry 4.0, businesses, organisations, and industries compete in the labour market for the most qualified, talented, and dynamic people in this age of technical developments. With the rising use of technology, Human Resource Management has undergone a transformation. Several Digitally Disruptive Technologies have radically altered the existing systems and resulted in the development of new business models. The present paper focuses on the application of artificial intelligence in the talent acquisition process, which is one of the most important functions of human resource management. It investigates the use of artificial intelligence as a tool for managing diverse talent acquisition initiatives. It includes case studies of firms that have effectively employed artificial intelligence to manage their hiring and talent acquisition operations. It can be concluded that AI has the potential to improve the quality of the hiring process by matching the best candidates to the job requirements.

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 5, Issue 2, Page 460 - 471
DOI: https://doij.org/10.10000/IJLMH.112872
Creative Commons
CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
Copyright
Copyright © IJLMH 2026
Disclaimer
The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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