Recruiting Revolution: How AI is Streamlining Hiring

  • Vaishnavalakshmi V IInd Year MBA, School of Management Dwaraka Doss Govardhan Doss Vaishnav College, Chennai, Tamil Nadu
Keywords: Artificial Intelligence,, Recruitment Process, Talent Management, Correlation Analysis, Chi-Square Test Analysis

Abstract

Artificial Intelligence (AI), a fundamental aspect of the Fourth Industrial Revolution, has become a pivotal concern across various industries, including business management. It is increasingly applied in fields such as marketing, human resource management (HRM), and manufacturing. Within HRM, AI and machine learning technologies are utilized to enhance employee experience, provide personalized training, and analyze HR data for informed decision-making. This integration of technology into HRM, traditionally a people-focused domain, represents a significant shift. AI technology adoption in HRM has surged in prominent settings. For instance, IBM has leveraged AI solutions like Blue Matching, CogniPay, and Watson Career Coach to streamline HR operations. Blue Matching predicts mobile tasks based on employee profiles, while CogniPay aids managers in decision-making by evaluating performance. Watson Career Coach offers personalized career guidance. However, notable cases like Amazon’s AI Recruitment Program have highlighted concerns regarding biases. Artificial intelligence is reshaping various aspects of our lives, including recruitment practices. As more businesses harness AI for candidate selection and evaluation, there’s a growing interest among HR managers in adopting AI solutions. However, this technological advancement also brings challenges, such as the displacement of existing job roles and the need for additional professionals to manage the evolving landscape. Understanding the potential benefits and challenges of AI in recruitment is essential for informed decision-making in HRM.

Published
2024-03-22
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How to Cite
V, V. (2024). Recruiting Revolution: How AI is Streamlining Hiring. Shanlax International Journal of Management, 11(S1-Mar), 63-70. https://doi.org/10.34293/management.v11iS1-Mar.8085
Section
Articles