Augmentation of Human Resource Management leveraging Machine Learning Paradigms: An Analytical Study within the Landscape of Information Technology Entities

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Authors: Dipanwita Dey, Shantanu Chakraborty
Cited by: 0
References: 1

Abstract

The information technology (IT) industry heavily depends on the vital function of human resources (HR). With a diverse workforce possessing varying levels of expertise and skill sets, the sector manages its operations efficiently. The integration of machine learning enhances several HR processes, including talent acquisition, candidate matching in recruitment process and employee retention, empowering HR leaders to make more informed, data-centric decisions.This research delves into the potential application of machine learning techniques to enhance various stages of the HR lifecycle. By employing Natural Language Processing based unsupervised machine learning algorithm in candidate matching, a robust and meticulous selection process is established to identify the ideal candidate during recruitment process, aligning with job description. This not only aids in cost-effective and time-efficient recruitment but also mitigates the need for frequent replacements and training efforts. Departing employees often take with them valuable tacit knowledge, a critical source of competitive advantage. To reduce attrition, a machine learning-driven approach is implemented to pinpoint employee attributes contributing to the prediction of attrition within organizations. The study draws upon human resource data from a service-oriented IT company to derive meaningful insights. DOI - https://doi.org/10.65525/SVUP.9788199651586.2026.80-96.

Fields of Study & Subjects

AI and HR Technologies Employer Branding and e-HRM Human Resource and Talent Management

Publication details

Pages
80–96
Publication date
1 January 2026
Language
EN
Document type
Book chapter