Artificial Intelligence, Structural Transformation, and the Rethinking of Labour-Intensive Growth in India

This study examines how artificial intelligence (AI) interacts with structural transformation to shape labour market outcomes in India, with particular focus on whether labour-intensive growth remains a viable strategy for inclusive development. India's demographic advantage demands large-scale productive employment, yet traditional pathways through manufacturing-led industrialisation are being disrupted by AI and automation technologies that affect both routine and cognitive tasks across sectors. Using a descriptive-analytical method, this paper draws on secondary data from the Periodic Labour Force Survey (PLFS), the India Employment Report (2024), World Bank indicators, OECD (Organization for Economic Co-operation and Development) publications, and IMF (International Monetary Fund) research to examine sectoral employment trends, AI adoption patterns, and workforce exposure across skill levels and regions. The findings reveal that India's structural transformation remains incomplete: employment growth is concentrated in low-productivity construction and informal services rather than in manufacturing. AI adoption follows a highly uneven trajectory, confined largely to formal, urban, high-skill environments, while the majority of workers remain in low-exposure, low-complementarity occupations that are bypassed by technological productivity gains. This creates a form of technological dualism that reinforces existing labour market segmentation. The study concludes that while labour-intensive growth retains developmental relevance, its viability depends on the simultaneous pursuit of technological upgrading, broad-based skill development, and supportive institutional frameworks. India's challenge lies not in choosing between employment and technology, but in redesigning its growth strategy so that both reinforce each other.