Rajeev Narayan

There is a painful truth about artificial intelligence that India needs to concede. It is not leading the race. That frontier is elsewhere. The United States has the deepest pool of AI companies, capital and computing power. China has built its technological capabilities at extraordinary speed. Taiwan sits at the heart of the semiconductor ecosystem on which the revolution hinges. India has talent, ambition and a rapidly expanding digital economy, but remains miles behind the countries shaping the technology at its cutting edge.

This reality has produced two conclusions. One is that India needs to run fast, build computing capacity, attract investment, develop its own foundation models and close the gap. The other is almost defeatist: that the race has already been lost and India will become merely a market for AI developed elsewhere. Both miss something important: there is another race, one in which India is unusually well placed to win.

Consider this. AI will not move from a server farm into the real economy by itself. Someone will have to check what it produces, correct what it gets wrong, train systems, oversee automated processes, adapt models to particular businesses, translate them into local languages and intervene when machines encounter the messy exceptions of real life. That will require people. A lot of people. The bigger question, then, is what happens when millions of people are needed to make machines work properly for a billion others? That is a new Indian layer of economic activity forming around AI.

New Middle Layer

Every technological revolution creates work around the technology itself. Cars created mechanics, service networks and an ecosystem of ancillaries. The internet created jobs that would have been difficult to imagine before the web. AI may do something similar, but with a critical difference: much of the new work may sit between the machine and the end-user.

Imagine a bank deploying AI to assess loan requests. The machine may process enormous amounts of information in seconds. But someone still has to test its recommendations, detect errors, monitor unusual cases and ensure an automated decision does not produce an absurd outcome. The same applies in hospitals, factories, insurance firms, logistics operations, schools and government departments.

AI can generate a document, but someone needs to verify it. It can translate a conversation, but someone needs to ensure the meaning survives. It can identify patterns in millions of records, but someone needs to decide whether those patterns mean anything. These are not jobs for elite researchers. They need domain knowledge, judgement, language skills, process expertise and the ability to work with AI tools, rather than build them.

For India, this distinction matters. The country has spent decades building a services economy around its educated workers performing sophisticated tasks for global businesses. AI will automate some of that work, but it may also create a new layer around checking, managing, customising and integrating AI. The opportunity is not to employ people in AI. It is to employ people around AI.

Advantage India

This is where India’s perceived weakness in the AI race could become an economic advantage. India does not need to produce every foundational model. It needs to become extremely good at putting those models to work across a complex and diverse economy.

India has hundreds of millions of potential users, millions of businesses and a stunning diversity of languages, industries and local contexts. A model developed in California or Shenzhen may be technologically impressive, but its usefulness in India will depend on how well it understands Indian customers, enterprises and realities.

Who will make that happen? People who know Hindi, Tamil, Bengali, Marathi or Telugu well enough to recognise when an AI system has translated something but missed its core meaning. People who understand banking, agriculture, law, medicine, manufacturing or retail well enough to distinguish an intelligent answer from a plausible-sounding wrong one. This is where Indian headcount could become an asset, rather than a demographic statistic.

There is also a geographical twist. Much of the work need not be done in Bengaluru, Hyderabad or other established tech hubs. If the tools are digital and the work can be performed remotely, AI-related services could spread to smaller cities and towns, as earlier waves of IT-enabled services did.

That said, India dare not turn the AI economy into another pool of low-paid digital work. If workers are reduced to correcting machine output for a few rupees a task, India would create employment without creating prosperity. The prize has to be upward mobility: acquiring AI-related skills, moving into complex forms of supervision and domain specialisation, and becoming productive as the technology improves. That is how headcount advantage can turn into an economic advantage.

Moving Beyond AI

Much of the talk around India’s AI future is centred on reskilling. Workers whose jobs are changing will need new skills, students entering the workforce will need to know how to work with intelligent systems, and companies will have to rethink training. All of that is necessary, but not enough. India should also ask: what new occupations, services and businesses can be built around AI?

The objective need not be to beat America at building the next frontier model or China at deploying AI at unprecedented scale. It can be to become extraordinarily good at adapting AI to a vast, complicated economy—and exporting that capability to the world.

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Sure, the AI revolution will destroy some jobs. But it will also create others. The nations that benefit most may not be those that automate the most, but those that become best at getting people and machines to work together. India may not win the race to build AI. But with the right skills, policies and ambition, it could build a workforce that teaches the AI machine how to work for the world.

The writer is a veteran journalist and communications specialist