AI-Powered HR: Enhancing Employee Experience and Engagement
Sanjeevan, B and Sherli, J and Jayanthi, N (2025) AI-Powered HR: Enhancing Employee Experience and Engagement. AI-Powered HR: Enhancing Employee Experience and Engagement, 14 (12s). pp. 1146-1143. ISSN ISSN(Online): 2226-0439
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Abstract
Human Resources (HR) to optimize employee experience (EX) and engagement within organizations. Leveraging
implications systematic analysis and bibliometric methodologies, this research aims to elucidate the current landscape,
trends, and of AI-driven HR interventions on employee-centric outcomes.
The systematic analysis delves into the existing literature, identifying and synthesizing studies that highlight the multifaceted
roles of AI in reshaping HR functions to foster enriched employee experiences. Furthermore, the bibliometric analysis offers
a quantitative assessment of the scholarly publications, revealing patterns, key thematic clusters, and influential works in the
domain of AI-powered HR and its impact on employee engagement.
Findings from this study demonstrate the evolving landscape of AI applications within HR, emphasizing its potential to
revolutionize talent acquisition, performance management, learning and development, and overall workplace culture.
Insights gleaned from the systematic review and bibliometric analysis offer a nuanced understanding of the prevalent trends,
emergent themes, and future directions for research and practical implementation.
In conclusion, this research underscores the transformative capacity of AI-driven HR initiatives in cultivating a more
engaging and fulfilling work environment for employees, providing valuable insights for HR professionals, researchers, and
organizational leaders seeking to leverage technological advancements to enhance the employee experience.
| Item Type: | Article |
|---|---|
| Subjects: | Commerce > Human Resources |
| Domains: | Commerce |
| Depositing User: | Mr IR Admin |
| Date Deposited: | 13 May 2026 10:35 |
| Last Modified: | 13 May 2026 10:35 |
| URI: | https://ir.vistas.ac.in/id/eprint/19105 |

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