Ai-Driven Automation And Labor Market Displacement In India: A Socio-Economic Data-Centric Perspective

Abstract

Artificial Intelligence (AI) is revolutionizing industrial processes, enhancing operational efficiency, and reshaping global labor markets. In the context of India—where economic development remains deeply intertwined with labor-intensive sectors—the rapid adoption of AI presents both opportunities and challenges. This study investigates the socio-economic implications of AI-driven automation on employment patterns in India through a multi-method research design. Using ordinary least squares (OLS) regression, a 1% increase in AI adoption was found to be associated with a 0.18% rise in job displacement, particularly within low- and middle-skilled occupations. However, AI integration simultaneously fosters the emergence of high-skilled job roles, especially in IT, BFSI, and emerging tech sectors.

Sentiment analysis of job postings from platforms such as LinkedIn, Naukri, and Glassdoor reveals public concerns regarding automation-induced redundancy, tempered by optimism in AI-enabling industries. Additionally, thematic analysis of expert interviews uncovers persistent skill mismatches, a lack of adaptive workforce strategies, and pressing policy gaps. The findings underscore the urgent need for comprehensive reskilling initiatives, institutional support, and regulatory frameworks that can promote inclusive AI deployment. The study concludes that while AI-driven automation may disrupt traditional employment structures, proactive policy interventions and an adaptable labor force can enable a more equitable transition.