A Study on Role of AI in Modern Recruitment -Opportunities and Challenges for HR Professional

DOI

https://www.doi.org/10.59256/ijsreat.20240402011

Published In

Volume 4, Issue 2 (2024)

Published Online

March-April 2024

Pages

83-90

Article Type

Research Article

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Artificial Intelligence (AI) is revolutionizing the recruitment landscape, presenting both opportunities and challenges for Human Resources (HR) professionals. This abstract explores the evolving role of AI in modern recruitment and its implications for HR practitioners. AI technologies offer HR professionals a multitude of opportunities to enhance recruitment efficiency, streamline processes, and improve decision-making. From automated resume screening and candidate sourcing to predictive analytics for talent forecasting, AI empowers HR teams to optimize their workflow and allocate resources more effectively. Moreover, AI-driven chatbots and virtual assistants enhance candidate engagement by providing instant responses and personalized interactions, thereby elevating the overall candidate experience. However, the adoption of AI in recruitment also presents challenges that HR professionals must navigate skillfully. Ethical considerations surrounding data privacy, algorithmic bias, and fairness in candidate selection require careful scrutiny and proactive measures to mitigate potential risks. Furthermore, there is a pressing need for HR professionals to develop competencies in data analysis, algorithm management, and ethical AI usage to harness the full potential of these technologies effectively. The study is aimed to find out the opportunities and challenges faced by hr professional by employing AI tools, quantitative data has been collected through surveys using stratified sampling method and for analyzing the data chi-square, correlations and Anova tools has been used. Key Word: Artificial Intelligence (AI), recruitment, Human Resources (HR), opportunities, challenges, efficiency, decision-making, candidate engagement, ethical considerations, data privacy, algorithmic bias.