Embedding Artificial Intelligence in Next Generation Human Resource Development Implementations( Vol-11,Issue-4,July - August 2025 ) |
|
Author(s): Arshad Matin |
Download Full Text PDF
Download with Cover Page
Total View : 794
Downloads : 12
Page No: 140-148
|
Keywords: |
|
|
Artificial Intelligence, Human Resource Management, AI in HR. |
|
Abstract: |
|
|
A new era of data-driven, automated, and intelligent decision-making processes across a broad range of HR tasks is being ushered in by the development of artificial intelligence (AI), which is significantly changing the field of human resource management (HRM). This study examines the revolutionary effects of AI technology on HRM practices by a thorough secondary review of recent scholarly works, industry reports, and case studies. AI-powered hiring and talent acquisition platforms, predictive analytics for assessing employee performance, intelligent workforce planning, automated onboarding, and real-time employee engagement platforms are some of the major areas of disruption that have been highlighted. The study not only highlights these developments but also critically analyzes the risks and difficulties that come with integrating AI, including issues with data privacy, algorithmic and cognitive biases, lack of interpretability, transparency, and the widening digital skill gap among HR professionals. In addition to highlighting the significance of coordinating AI deployment with organizational ethics, legal compliance, and human-centric values, the study delves deeper into the strategic implications of AI in promoting agile, inclusive, and responsive HR ecosystems. As crucial avenues for long-term adoption, emerging themes like explainable AI (XAI), ethical AI governance, and AI literacy in HR are also covered. According to the findings, while AI has the ability to greatly improve HRM's operational efficiency, decision accuracy, and employee experience, long-term success depends on a methodical, morally sound, and strategically integrated strategy. |
|
| Article Info: | |
|
Received: 09 Jun 2025; Received in revised form: 07 Jul 2025; Accepted: 11 Jul 2025; Available online: 14 Jul 2025 |
|
Cite This Article: |
|
|
Citations:
APA | ACM | Chicago | Harvard | IEEE | MLA | Vancouver | Bibtex
| |
Share: |
|

DOI: 



























