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Predictive Analytics in Employee Engagement Using AI

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  • Shitalnath R. Ekhande
  • Anurodh Khanuja

Abstract

The rapid adoption of artificial intelligence (AI) in human resource management (HRM) has introduced new opportunities for enhancing employee engagement through predictive analytics. This research paper explores the role of predictive analytics in employee engagement, focusing on the integration of AI-powered models into human resource information systems (HRIS). By analyzing industry case studies, architectural frameworks, and emerging AI techniques, we propose a comprehensive approach to leveraging predictive analytics for optimizing workforce engagement and retention. Our findings highlight the importance of multi-modal data integration, scalable architectures, and ethical considerations in the development and deployment of AI-powered employee engagement systems. The proposed framework provides valuable insights for organizations seeking to harness the potential of predictive analytics in driving employee engagement and organizational success.

Suggested Citation

  • Shitalnath R. Ekhande & Anurodh Khanuja, 2024. "Predictive Analytics in Employee Engagement Using AI," International Journal of Scientific Research in Science, Engineering and Technology, Technoscience Academy, vol. 11(6), pages 186-195, December.
    • Handle: RePEc:ijs:ijsrse:v11:y2024:i6:id:265
    DOI: 10.32628/IJSRSET2411592
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