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Artificial Intelligence (AI) is revolutionizing Human Resource Management (HRM) by integrating automation, predictive Analytics, and data-driven decision-making. Organizations are increasingly adopting AI-powered solutions to enhance talent acquisition, employee engagement, performance management, and workforce planning. AI-driven recruitment systems streamline hiring by reducing biases, improving candidate-job matching, and expediting the selection process. Additionally, chatbots and virtual assistants are transforming onboarding, training, and employee support by providing real-time assistance and personalized learning experiences. Beyond recruitment, AI plays a crucial role in workforce analytics, helping HR professionals predict attrition risks, optimize talent management, and enhance employee well-being. Machine learning algorithms and sentiment analysis enable organizations to proactively address workforce challenges, implement effective retention strategies, and cultivate a positive workplace culture. Moreover, AI enhances HR operations by automating payroll processing, benefits administration, and compliance tracking, reducing manual errors and ensuring regulatory adherence. This paper covers the evolving role of AI in shaping future HRM strategies, highlighting the impact of AI on HR, opportunities, and challenges. It also emphasizes the significance of a balanced AI-human approach, where AI augments HR capabilities without replacing human judgment. By integrating AI ethically and strategically, organizations can create an agile, data-driven, and employee-centric HRM framework that aligns with future workforce needs.
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: Bala Bharathi, bharathitalla1@gmail.com V.R. Ramakrishna, rams2976vr@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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