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Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Challenges in Integrating Artificial Intelligence (AI) into HRM Practices: An Indian Perspective

Authors: Pratiksha Chavan; Dr. Vishal Gaikwad;

Challenges in Integrating Artificial Intelligence (AI) into HRM Practices: An Indian Perspective

Abstract

The purpose of this study is to evaluate Human Resource Management (HRM) practices in India and to underline the importance, benefits, and upcoming challenges of integrating Artificial Intelligence (AI). Unlike much of the existing research in India, which primarily examines conventional HR practices, this paper attempts to explore the next phase of HRM by assessing the potential of AI adoption. The study relies on secondary data sources, including books, research articles, newspapers, and authentic online resources. It highlights current HRM practices in India, the significance of AI, and the barriers to its adoption. The findings of this study are expected to help policymakers and practitioners recognize the value of AI in HRM, while also offering directions for future research on employee readiness and acceptance of AI. In conclusion, AI-enabled HR practices have the potential to improve employee productivity, talent management, learning and development, and retention, while reducing turnover. With India’s rapid growth trajectory, this is an opportune time to embrace AI for strengthening HR functions across business organizations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green