Infosys co-founder Nandan Nilekani says India should support more startups and small businesses because they could become the main source of new jobs as AI changes the way companies work.
Infosys co-founder Nandan Nilekani believes India’s next wave of job creation will come less from large corporations and more from millions of startups and small businesses as artificial intelligence changes how companies operate.
Speaking at the Global Fintech Fest 2026, Nilekani said large companies are better positioned to use AI for automation because they typically have structured roles and established processes. Smaller businesses, by contrast, tend to operate with more fluid responsibilities, making many of their jobs harder to automate completely.
“If you want to AI-proof an economy, you actually should create a situation where job creation is done by millions of small companies,” Nilekani said.
He argued that India’s response to AI-driven workforce disruption should therefore include policies and technology that make it easier for entrepreneurs to start businesses, access capital and reach customers.
Why Nilekani Thinks Small Businesses Will Create More Jobs
Nilekani said the structure of large organisations makes them particularly suited to automation.
When a company has clearly defined workflows, repetitive processes and large numbers of employees performing similar tasks, AI can potentially automate significant portions of that work.
Smaller companies operate differently. Their employees often handle several functions at once, while founders and teams constantly adapt to changing customer and business requirements.
That does not make small businesses immune to AI. Instead, Nilekani sees AI as a tool that could allow smaller companies to become more productive without necessarily replacing the people who work in them.
“Both the new startup world as well as the traditional world, they will be the employers of the future,” he said.
India’s Startup Base Could Expand Dramatically
Nilekani pointed to the expansion of India’s startup ecosystem as evidence that the country already has the foundation for a more distributed employment model.
He said India had roughly 10,000 startups in 2015, compared with around 1.5 lakh in 2025, and expects the number to reach approximately 10 lakh by 2035.
That would mean a much larger base of businesses capable of creating jobs across sectors and geographies.
The argument also shifts the focus away from whether India’s biggest technology and manufacturing companies can absorb workers displaced by AI.
Instead, the question becomes whether millions of smaller enterprises can grow quickly enough to create new opportunities.
For that to happen, Nilekani said, technology must reduce the advantages historically enjoyed by larger companies.
Tokenisation Could Give Small Businesses Better Access to Capital
One area Nilekani highlighted is tokenisation.
He said tokenisation is moving from an emerging technology concept towards practical financial applications, with the Reserve Bank of India and Securities and Exchange Board of India exploring tokenised financial assets.
Nilekani said the RBI is examining the tokenisation of certificates of deposit, while the RBI and SEBI are also working together on tokenised corporate bonds.
At its simplest, tokenisation involves creating a digital representation of an asset containing information about its identity, characteristics and associated rules.
The potential benefit, Nilekani argued, is that an asset and the information needed to verify it can move together digitally.
That could make productive assets easier to identify and potentially easier to use across lenders, insurers, fintech platforms and marketplaces.
Three Tokenisation Pilots Could Show How It Works
Nilekani highlighted three pilots being developed using the Finternet architecture, an open and interoperable digital financial infrastructure intended to allow different financial systems and asset types to interact.
The first involves tokenising cattle.
The digital credential would capture information including the animal’s identity, ownership, health and milk productivity. That information could then be shared with lenders, potentially allowing the cattle to be used as collateral for financing.
The second pilot involves warehouse receipts.
Information such as the quantity and quality of stored agricultural produce could be represented digitally and shared with lenders. That could make agricultural inventory easier to verify when businesses seek financing.
The third focuses on loan documents.
By tokenising loan documents and making them interoperable across marketplaces, standardised transactions could potentially be executed using smart contracts.
The three use cases are different, but they are built around the same basic idea: make an economic asset digitally identifiable, verifiable and portable.
AI Agents Could Create a Market for Tokenised Assets
Nilekani said tokenisation on its own is not enough.
For digital assets to become useful at scale, they also need interoperability and liquidity. This is where he sees a role for AI agents.
An AI agent could, for example, take an invoice, convert it into a token, identify potential lenders and offer the asset to them.
That would move beyond simply digitising an asset towards automating the process of finding financing or other economic opportunities.
“Tokenisation by itself will only handle issuance. But tokenisations on public chains supported by agentic transactions will also create demand,” Nilekani said.
The implication is that AI could become the layer that actively searches for opportunities around tokenised assets rather than leaving small businesses to navigate multiple financial platforms manually.
A Potential Level Playing Field for Small Businesses
This combination of tokenisation and AI is central to Nilekani’s broader argument about India’s future workforce.
Large companies have traditionally had advantages because they can afford specialised teams for finance, legal work, procurement, market research, technology and other functions.
A small company cannot usually employ all those specialists.
But a tokenised financial asset that carries trusted information, combined with an AI agent capable of searching markets and negotiating or executing transactions, could give smaller businesses access to some of those capabilities digitally.
In theory, that could reduce the gap between a small enterprise and a large corporation.
For example, a small manufacturer could potentially turn receivables or inventory into verified digital assets, have an AI agent identify financing options, and access lenders without maintaining a large financial team.
The technology therefore becomes less about replacing workers and more about giving smaller businesses tools that help them grow.
India’s Digital Infrastructure Is Moving Into a New Phase
Nilekani has been closely involved in India’s digital public infrastructure, including the systems that helped make digital identity and payments available at population scale.
He sees tokenisation as another layer in that evolution.
Aadhaar made identity digitally accessible. UPI transformed digital payments. Tokenisation, in his view, could make economic assets and rights similarly identifiable and transferable.
AI agents could then sit on top of that infrastructure and carry out transactions on behalf of people and businesses.
That combination could have implications well beyond startups, particularly for agriculture, manufacturing, logistics, lending and other sectors where access to capital remains a constraint.
Maharashtra Is Also Exploring Asset Tokenisation
Nilekani’s comments came shortly after Maharashtra Chief Minister Devendra Fadnavis said the state was working on a framework for blockchain-based tokenisation of land and other immovable assets.
The proposed Maharashtra Digitisation and Exchange of Land Token Asset (DELTA) Act is intended to explore a state-level legal framework for land tokenisation.
The development illustrates how tokenisation is beginning to attract interest beyond financial securities and into physical assets such as property.
However, legal recognition and practical adoption remain critical before tokenised representations of assets can function at scale in mainstream markets.
The Bigger Question Is How India Creates Jobs in the AI Era
Nilekani’s argument starts with a simple concern: AI could make large companies much more productive without requiring them to employ as many people.
If that happens across major industries, simply relying on large corporations to absorb India’s growing workforce may become increasingly difficult.
His alternative is to create an economy with millions of small employers, supported by technology that gives them better access to money, markets and capabilities.
Tokenisation could make assets easier to finance. AI agents could help businesses find and execute transactions. And a growing startup ecosystem could turn those tools into new companies and new jobs.
For Nilekani, the answer to AI-driven job disruption is therefore not to stop automation.
It is to build an economy in which millions of smaller businesses can use the same technological infrastructure to create opportunities faster than traditional enterprises can eliminate them.
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Source: Inc42
