Artificial Intelligence (AI) is transforming labour markets globally, creating high-skill opportunities while shrinking routine middle-skill jobs, intensifying inequality and urgent reskilling needs. This paper examines AI-driven labour market polarisation and workforce reskilling in India, where rapid technological change is reshaping job structures and skill demands. Grounded in Skill Biased Technological Change (SBTC) and Human Capital Theory, the study demonstrates that AI adoption disproportionately benefits high-skilled workers, driving growth in high-wage occupations, while routine middle-skilled roles decline, intensifying wage disparities and increasing demand for new competencies. 

Using secondary data and official reports from 2020–2024, the analysis identifies India’s distinctive polarisation pattern: a shrinking middle-skill workforce alongside a persistently large low skill labour segment. Limited reskilling coverage further constrains workers’ ability to adapt to AI driven changes, risking a “low-skill trap.” Comparative insights from the United Kingdom, a developed economy with more systematic AI adoption and structured training programs, highlight how proactive reskilling mitigates workforce displacement, offering lessons for emerging economies like India. 

The findings underscore the urgent need for targeted workforce planning, investment in human capital, and collaboration between industry, government, and educational institutions. By linking theory with empirical evidence, this study provides actionable insights for policymakers, business leaders, and  academics seeking to navigate AI-driven labour market transformations. The paper highlights how emerging economies can leverage AI for productivity and growth while addressing inequality and skill gaps, contributing to sustainable and inclusive workforce development.