AI-Driven HR Analytics: Transforming Talent Management and Employee Engagement

• Kayusi, Fredrick ^[1] ; Chavula, Petros ^[2] ; Keari Omwenga, Michael ^[2] ; Juma, Linety ^[2] ; Agura Kayus, Bismark ^[3] ; Gonzalez Vallejo, Ruben ^[4] ; Mishra, Rashmi ^[5]
  1. [1] Maasai Mara University

     Maasai Mara University

     Kenia

     
  2. [2] Pwani University

     Pwani University

     Kenia

     
  3. [3] Kisii University

     Kisii University

     Kenia

     
  4. [4] Universidad de Málaga

     Universidad de Málaga

     Málaga, España

     
  5. [5] University of Technology and Applied Sciences, Al Mussanah, Oman

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• Localización: Revista Multidisciplinaria Voces de América y el Caribe: (REMUVAC), ISSN-e 2981-7463, Vol. 2, Nº. 1, 2025, págs. 558-582
• Idioma: español
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• Resumen

  • The research study explored the role of Artificial Intelligence in HR Analytics and its impact on talent acquisition, employee engagement, performance management, and learning and development. We have used the mixed-methods research approach by studying the extensive literature review and a quantitative survey of 146 HR professionals to examine how AI-driven tools are reshaping the Human Resource management dimension and its functions. Key findings highlight that AI has significantly reduced time-to-hire by 51.1%, improved appraisal accuracy by 50.8%, increased employee satisfaction by 51.3%, and enhanced training relevance by 26.1%. AI applications such as resume screening, sentiment analysis, predictive analytics, and adaptive learning systems have resulted in more data-driven, efficient, and personalized HR practices. Apart from the benefits, several challenges and issues are raised, such as ethical concerns, data privacy, and organizational resistance to AI adoption. Our research recommends integrating transparency, fairness, and ethical frameworks in AI-driven HR practices and improving the HR analytics so that HR professionals can leverage AI technologies responsibly, enhancing both workforce experience and organizational effectiveness. Future research is suggested to explore AI's role in diversity, hybrid work management, and the long-term cultural impact of AI adoption in Human Resource Management functions.