Human Resource Management, Indian Institute of Management Indore, Madhya Pradesh, India.
Abstract
In response to India evolving labour market and policy reforms like the National Education Policy (NEP) 2020, organisations are increasingly adopting Artificial Intelligence (AI) and data analytics to streamline recruitment processes (MoE, 2020)1. However, the extent and effectiveness of AI integration across sectors remain largely underexplored, especially in relation to the skill-employability gap highlighted in government and NITI Aayog reports (NITI Aayog, 2021). This study conducts a comparative analysis of hiring practices in IT, non-IT, and public sector organisations using secondary data, policy documents, and organisational case studies. Drawing on frameworks from emerging HRM literature (Meijerink et al., 2021, Chamorro- Premuzic et al., 2019), the study evaluates adoption maturity, recruitment outcomes, and ethical considerations. Findings show that while IT firms leverage AI tools for end-to-end hiring, public and non-IT sectors face systemic barriers related to digital infrastructure, resistance to change, and policy alignment. The paper concludes by proposing a sector-specific framework for responsible and scalable AI adoption in hiring, with implications for education-to-employment linkages and workforce development strategy.
Keywords: AI in Recruitment, NEP 2020, Predictive Hiring, Public Sector HRM, Skill Gap, India
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