From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement

The rapid evolution of Human Resource Management (HRM) has been significantly influenced by advancements in Artificial Intelligence (AI) and data analytics. Traditional HR practices, which relied on manual decision-making and intuition, have been transformed by HR analytics, enabling data-driven workforce management. The integration of AI into HRM has further revolutionized employee engagement, talent acquisition, performance management, and workforce productivity. This paper explores the transition from HR analytics to AI-driven HRM, emphasizing its role in enhancing organizational efficiency. AI-powered HRM systems leverage predictive analytics, natural language processing, and machine learning algorithms to optimize talent management strategies. These technologies facilitate personalized employee experiences, automate repetitive HR tasks, and provide actionable insights for strategic decision-making. Moreover, AI-driven HRM enhances employee engagement through intelligent chatbots, real-time feedback mechanisms, and personalized learning platforms, fostering a more dynamic and inclusive workplace culture. Despite its benefits, AI adoption in HRM presents challenges such as data privacy concerns, ethical implications, and the risk of algorithmic biases. This paper discusses these limitations and explores potential mitigation strategies to ensure responsible AI implementation. Additionally, it highlights emerging trends in AI-driven HRM, including the role of generative AI, sentiment analysis, and adaptive learning systems in shaping the future of human resource practices. By examining scholarly research, industry case studies, and best practices, this review provides a comprehensive analysis of AI’s impact on HRM. It offers insights into how organizations can leverage AI and HR analytics to drive workforce productivity and engagement while addressing the associated ethical and operational challenges. The findings suggest that AI-driven HRM is not just a technological advancement but a strategic necessity for modern businesses seeking to build a resilient, high-performing workforce in an increasingly digital era.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-14
DOI
https://doi.org/10.52783/jisem.v10i21s.3395
Citations
3
Primary Topic
AI and HR Technologies
Type
article
Field-Weighted Citation Impact
8.29
Controls
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article

From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement

K Selvamohana
3 citations
Journal of Information Systems Engineering & Management
AI and HR Technologies
8.29
article

From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement

K Selvamohana
article en
3 citations

Abstract

The rapid evolution of Human Resource Management (HRM) has been significantly influenced by advancements in Artificial Intelligence (AI) and data analytics. Traditional HR practices, which relied on manual decision-making and intuition, have been transformed by HR analytics, enabling data-driven workforce management. The integration of AI into HRM has further revolutionized employee engagement, talent acquisition, performance management, and workforce productivity. This paper explores the transition from HR analytics to AI-driven HRM, emphasizing its role in enhancing organizational efficiency. AI-powered HRM systems leverage predictive analytics, natural language processing, and machine learning algorithms to optimize talent management strategies. These technologies facilitate personalized employee experiences, automate repetitive HR tasks, and provide actionable insights for strategic decision-making. Moreover, AI-driven HRM enhances employee engagement through intelligent chatbots, real-time feedback mechanisms, and personalized learning platforms, fostering a more dynamic and inclusive workplace culture. Despite its benefits, AI adoption in HRM presents challenges such as data privacy concerns, ethical implications, and the risk of algorithmic biases. This paper discusses these limitations and explores potential mitigation strategies to ensure responsible AI implementation. Additionally, it highlights emerging trends in AI-driven HRM, including the role of generative AI, sentiment analysis, and adaptive learning systems in shaping the future of human resource practices. By examining scholarly research, industry case studies, and best practices, this review provides a comprehensive analysis of AI’s impact on HRM. It offers insights into how organizations can leverage AI and HR analytics to drive workforce productivity and engagement while addressing the associated ethical and operational challenges. The findings suggest that AI-driven HRM is not just a technological advancement but a strategic necessity for modern businesses seeking to build a resilient, high-performing workforce in an increasingly digital era.

Journal of Information Systems Engineering & ManagementVol. 10(21s)
Openalex Percentile: Top 3%
AI and HR Technologies
8.29
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From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement — K Selvamohana · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS