International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Predictive People Analytics: Integrating Artificial Intelligence for Proactive Human Resource Decision-Making

Author(s) Vipul Sharma, Dr. Charu Sharma
Country India
Abstract The contemporary organizational environment is being reshaped by the rapid infusion of Artificial Intelligence (AI) and data analytics into managerial decision-making processes. Within the domain of Human Resource Management (HRM), this transformation is particularly profound, as organizations increasingly depend on digital data to understand, anticipate, and influence employee behaviour. HRM, once considered an administrative support function, is evolving into a strategic, data-driven discipline capable of generating predictive insights about workforce performance, engagement, and retention (Marler & Boudreau, 2017). “People Analytics” refers to the systematic collection and analysis of employee-related data to enhance organizational outcomes. Initially focused on descriptive reporting—tracking absenteeism, turnover, or recruitment efficiency—modern analytics now incorporate machine learning (ML) and natural language processing (NLP) to uncover complex patterns that elude human intuition. The integration of predictive algorithms transforms HR decisions from reactive responses to proactive interventions, enabling organizations to forecast employee turnover, burnout, and productivity fluctuations well in advance (Bondarouk et al., 2022).
Keywords Artificial Intelligence; Predictive People Analytics; Human Resource Management; Machine Learning; Decision Intelligence; Predictive Modeling; Employee Behavior
Published In Volume 6, Issue 4, July-August 2024
Published On 2024-07-12
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E-ISSN 2582-2160
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