Abstract
The rapid proliferation of Artificial Intelligence (AI) and automation technologies has brought transformative changes to India's economic and employment landscape. These innovations have redefined production systems, reshaped labour structures, and introduced new forms of human–machine collaboration. This paper investigates the multi-dimensional impact of automation and AI on the Indian labour markets using both theoretical and empirical approaches. Based on primary data from 100 respondents across agriculture, industry, services, IT, and education, this study employs Descriptive Analysis, Chi-square tests, and ANOVA to evaluate employment shifts, income changes, and productivity trends. The theoretical framework integrates Human Capital Theory, Skill-Biased Technological Change (SBTC), and Schumpeter’s Innovation Theory to explain how automation creates both displacement and opportunity. Findings reveal that automation increases productivity but causes job polarization between high- and low-skill workers. Chi-square analysis confirms a significant relationship between skill level and income growth, while ANOVA demonstrates that productivity varies significantly across sectors. The study concludes that India must strengthen reskilling systems, implement inclusive digital policies, and enhance AI governance to ensure equitable technological progress.
Keywords: Automation, Artificial Intelligence, Labour Market, Skill Development, Human Capital, Chi-Square, ANOVA, Innovation Theory
References
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Schumpeter, J.A. (1939). Business Cycles: A Theoretical Analysis.