New Delhi: Nearly 197 million Indian workers are in jobs with a high share of routine tasks that could eventually be automated, while around 46 million work in occupations where artificial intelligence (AI) could improve productivity, according to a new study.
The paper, titled AI, Automation and India’s Workforce: Who Gains, Who’s Exposed, and How Policy Can Shape the Future, was released Sunday by the Centre for Finance and Economics Research at the Great Lakes Institute of Management, Chennai.
Written by Vidya Mahambare, Vivek Jadhav and Vishnu Venugopalan, it examines how AI and automation could affect employment, which workers are likely to benefit from the technology and who may face greater risks.
AI exposure and the risk of job displacement
One of the key findings of the study is that around 150.5 million workers, or 24.6 per cent of the working-age population, are in occupations exposed to AI. However, more workers face the prospect of AI replacing some of their tasks than stand to benefit from the technology supporting their work.
The report estimates that around 197 million workers are in jobs where routine tasks could eventually be automated. This does not mean all these jobs will disappear, but it highlights the scale of the workforce that could be affected by automation.
“Even with less than 8 per cent of the employed in AI-complementary occupations, India has one of the largest workforces that can directly raise productivity through effective use of AI tools and expert domain knowledge,” the report states.
The study also highlights the challenges facing young Indians in the job market. More than 20 million Indians aged 15–64 were unemployed in 2025, including 18.7 million people aged 15–34. The unemployment rate among graduates aged 20–29 was more than twice the overall rate, while 25 per cent of people with engineering degrees were unemployed.
Also Read: AI is not intelligent. We have just lowered the bar
Young workers and women face different risks
Around 39.4 per cent of employed people aged 15–24 work in jobs with a high share of routine tasks. In urban areas, the proportion rises to 55 per cent, making young urban workers particularly vulnerable to changes.
The report also found differences in how AI exposure affects men and women. Women in AI-exposed occupations are more likely than men to work in roles where AI can support their tasks rather than replace them.
Among AI-exposed workers, 37.6 per cent of women’s work was AI-complementary, compared with 28.4 per cent for men. In urban areas, 19.5 per cent of employed women worked in AI-complementary occupations, compared with 14.5 per cent of employed men.
“Among women, AI-exposed employment is of better quality than men’s, reflecting concentration in non-routine health and education work,” the report states.
However, women’s participation in paid employment remains a concern. Only around 18 per cent of women aged 20–29 were in paid employment, compared with about 79 per cent of men in the same age group.
AI exposure varies across states
The study found that Kerala has the highest AI exposure among workers, at 42 per cent, followed by Haryana at 37.9 per cent and Tamil Nadu at 32.9 per cent. Madhya Pradesh, meanwhile, has one of the lowest rates, at 16.1 per cent.
However, greater AI exposure does not necessarily translate into greater benefits for workers or states. The report found that the extent to which workers stand to benefit from AI, rather than face the risk of task substitution, varies across regions.
In Himachal Pradesh, 43.3 per cent of AI-exposed workers are in jobs where AI can support their work. Meanwhile, Uttar Pradesh, Bihar, Jharkhand and Madhya Pradesh face greater pressure from possible task substitution. Punjab has the highest share of workers in jobs with routine tasks that could be automated, at 44.6 per cent.
Early investment in skills and training
Against the backdrop of concerns about job displacement and the potential productivity gains from AI, the authors call for India to prepare its workforce for technological change. Their recommendations include introducing AI education in schools, making AI tools more accessible, and providing training to young people and workers in jobs with a high share of routine tasks.
“The aggregate employment effects of AI and automation – positive or negative – will take time to show, with adoption uneven across firms and sectors: deployment costs need to fall, complementary human skills need to improve, machines need to become more capable and reliable, and firms need to work out where and how to deploy them. Prudence, however, calls for acting early rather than waiting,” the paper states.
Edited by Maryam Hassan