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A new Great Lakes CFER working paper estimates that 46 million Indian workers are in occupations where AI may complement their work, while another 197 million are in high-routine jobs where automation could eventually take over many tasks. At the paper’s launch on 11 October 2026, Chief Economic Adviser V. Anantha Nageswaran cautioned that exposure does not mean a job will disappear.
What the paper says about AI and Indian workers
“AI, Automation and India’s Workforce: Who Gains, Who’s Exposed, and How Policy Can Shape the Future” is the fifth working paper listed by the Centre for Finance and Economics Research (CFER) at Great Lakes Institute of Management. Published in October 2026, it is authored by Vidya Mahambare, Vivek Jadhav, and Vishnu Venugopalan. The publisher says the paper uses national worker-level data to assess how AI and automation may affect work and the distribution of potential gains and risks. Great Lakes CFER’s paper listing and summary
How many workers may be affected?
CFER’s summary gives two headline estimates for 2025. They describe different kinds of exposure, not a forecast of how many people will lose jobs.
| Type of exposure | Publisher’s estimate for 2025 | What it means |
|---|---|---|
| Potential complementarity with AI | About 46 million workers | They work in occupations where AI may complement their work and raise productivity. |
| High-routine work with automation potential | About 197 million workers | They work in jobs where automation could eventually take over a large share of tasks; CFER says full automation will take time. |
These figures are the publisher’s summary of the paper’s estimates. The available summary does not specify the occupation-classification rules, exposure thresholds, or estimation method, so it does not support finer claims about particular occupations or the timing of change.
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Who may face both risk and opportunity?
Young workers and entry-level roles
CFER highlights young, urban, entry-level workers as facing both substitution risks and potential productivity gains. It reports that 39.4 per cent of workers under 25 were in high-routine work in 2025. That figure describes workers in a category of work; it does not mean that 39.4 per cent of young workers will lose their jobs.
Urban and rural workers
The publisher describes rural India as less exposed to substitution by AI and automation, but also less likely to benefit from productivity gains. This is a contrast in potential exposure and upside, not a claim that every rural or urban worker will experience the same effect.
Why exposure is not the same as job loss
Exposure means that tasks in an occupation may be affected by AI or automation. It does not establish that an entire role will be automated, that a worker will be displaced, or when any change will occur. Some tasks may be automated while other parts of a job remain or change. At the paper’s launch, Nageswaran put the distinction plainly: “Exposure is not the same as job loss. In some jobs, of course, AI is likely to raise what a worker can do.” Financial Express’s report on the launch
Which policy priorities does the paper identify?
CFER says the paper calls for policy to shape AI’s effects on employment, with priorities that include:
- Reskilling: helping workers build capabilities relevant as tasks and roles change.
- AI literacy: improving workers’ ability to understand and use AI in their work.
- Social protection: supporting workers who face disruption or transition.
- Urban housing: addressing housing as part of the conditions that affect workers and employment in cities.
The publisher summary identifies these priorities but does not specify particular programs, providers, or implementation details. It also does not establish state-by-state estimates.
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