Nandan Nilekani says India’s AI opportunity is not limited to building the most powerful models: it is making useful applications accessible across businesses and the population. He also expects small businesses to become an important source of employment as larger companies automate more work. That jobs outlook is his argument, not a measured forecast or established outcome.
What Nilekani said about AI and jobs in India
Speaking at the Bloomberg New Economy Forum in New Delhi on October 13, 2026, Nilekani argued that AI is not a winner-take-all technology and that many companies can participate. He said India could lead by applying AI widely and delivering useful applications at population scale, rather than judging success only by who builds the most powerful models. Moneycontrol reported his remarks.
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He expects large companies to use AI to improve efficiency, potentially reducing workforces, while small businesses could contribute a growing share of future employment. Nilekani also said demand for work at companies such as Infosys is increasing, suggesting that he does not see automation as eliminating all demand for technology services. These comments are not a quantified forecast of jobs gained or lost in India.
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What AI diffusion means—and why it differs from building models
AI diffusion means getting useful AI applications into practical use across firms and communities. That can include tools that help businesses serve customers, organize work or make decisions; the central idea is broad, useful adoption, not simply access to frontier models.
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At NCAER’s India Policy Forum in August 2026, Nilekani described applied AI as the area where India could lead, drawing a parallel with the population-scale reach of digital public infrastructure. The distinction matters: model development is one part of the AI economy, while diffusion depends on whether people and businesses can access and use applications that fit their needs. Business Standard reported his remarks.
Why he expects small firms to create more jobs
Nilekani’s reasoning rests partly on how work is organized. Large companies can divide roles into defined, repeatable tasks, which may be easier to automate. Workers in smaller firms often handle varied responsibilities, making their roles less neatly reducible to a single task. That difference may leave room for AI to support small-firm workers rather than simply replace a narrowly defined job.
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But varied work does not make small businesses immune to automation, and it does not guarantee that they will hire. Their ability to grow and employ people depends on whether they can use technology productively and reach customers, financing and markets. Nilekani has called for simpler regulation, improved access to credit and markets, and AI-enabled business support to help them do so.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteExamples of the support he has proposed
- Accessible interfaces: Voice and local-language tools could make applications easier to use for people who do not work primarily in English or with conventional text interfaces.
- Credit access: Nilekani pointed to Account Aggregator as a way to improve small firms’ access to formal credit.
- Market access: He cited ONDC as a route for small businesses to reach larger markets.
- Portable benefits: If work becomes more mobile, benefits such as savings, pensions, insurance, unemployment support and health care could follow workers between jobs.
These are proposed enablers, not evidence that the programs have already created jobs. Portable benefits address worker security as employment changes; credit and market access address constraints on small firms’ ability to expand.
Will AI replace jobs at large companies?
It may automate some tasks and reduce the need for some roles, but that is not the only possible effect. AI can also augment workers, change existing tasks or create complementary work. The outcome depends on what employers automate, how they reorganize work, what new tasks emerge, and whether workers and firms can adapt.
ICRIER’s paper Interactions of Artificial Intelligence with India’s Labour Market describes these forces as task displacement and task reinstatement or reshaping. It cautions that productivity gains do not automatically produce better employment outcomes: deployment choices, workplace organization, skills and institutions affect who benefits. Read the ICRIER paper.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the jobs claim does—and does not—establish
Nilekani’s view is a policy argument about where new work could come from, not a settled labour-market finding. The reporting gives no number for jobs AI might create or destroy in India, and it does not demonstrate that small-firm hiring will offset workforce reductions at larger companies.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesFor context, ICRIER cites an Economic Survey 2023–24 estimate that India needs 7.85 million non-farm jobs annually by 2030. This is an economy-wide employment requirement cited in the paper, not an AI job forecast; the original Survey figure has not been independently verified here. It conveys the scale of the employment challenge without predicting which sectors or firm sizes will meet it.
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What to watch as AI spreads
The test of Nilekani’s thesis is not simply how many people can access AI or how capable a model becomes. It is whether adoption helps firms become productive, whether smaller businesses can translate that productivity into growth and hiring, and whether workers can move into reshaped or new tasks with the necessary skills and protections. The technology may create opportunities, but firm decisions and public policy will help determine how widely those gains are shared.
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