Machine Learning Applications in Human Resource Management: Predicting Employee Turnover and Performance
DOI:
https://doi.org/10.55938/ijgasr.v3i2.77Keywords:
AI, Machine Learning, Human Resource Management, Talent Management, Employee Engagement, Organizational PerformanceAbstract
The paper presents a fully-fledged survey of the transformative power of AI-driven Machine Learning (ML) models in revolutionizing Human Resource Management (HRM) practices. The research investigates the new-age applications of such emerging technologies about talent identification, workforce planning, employee engagement, and personalized career development. It also looks at how natural language processing and sentiment analysis can become instrumental in the construction of an employee feedback system that is both engaging and transparent. The research also explores how ML algorithms are used to design tailor-made career development plans to ensure a proper match between individual aspirations and organizational needs. It further proceeds to elaborate on the integration of ML with human resource development in creating personalized learning and development programs to address the limitations of one-size-fits-all approaches to training. This comprehensive AI-driven talent framework, represented here, strongly proves its enhanced potential to improve employee engagement, organizational performance, and competitive advantage by its implementation and evaluation.
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Copyright (c) 2024 Rachna Rathore, Saurabh Pratap Singh Rathore
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