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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49805
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In the digital age, Artificial Intelligence (AI) has emerged as a transformative force in reshaping human resource management, particularly in the domains of talent acquisition and employee experience. This study investigates the impact of AI-powered tools and technologies on recruitment strategies, candidate engagement, and the overall experience of employees in modern organizations. The research aims to assess how AI enhances recruitment efficiency, reduces biases, and improves decision-making processes while also evaluating its influence on employee satisfaction, onboarding, engagement, and workplace support. A quantitative methodology was adopted, using a structured Google Form survey distributed among HR professionals, recruiters, and employees from various sectors. The survey collected insights into the use of AI tools such as applicant tracking systems (ATS), chatbots, automated screening platforms, and sentiment analysis tools in HR operations. The results indicate a growing reliance on AI to streamline hiring, improve job-candidate matching, and personalize employee support systems. However, concerns around ethical implications, data privacy, and the potential depersonalization of human interaction were also highlighted. This research contributes to the academic and practical understanding of AIâs dual role in optimizing recruitment workflows and enriching the employee journey. It emphasizes the need for a balanced approach that integrates technological innovation with human- centered HR practices. The findings offer actionable insights for HR professionals, policymakers, and organizational leaders aiming to leverage AI for sustainable talent management and enhanced workplace experiences.
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Publication Date
6/9/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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