India’s AI skills ambition: How to train 10 million young people for the future of work

Addressing the nation from New Delhi’s Red Fort on the 80th Independence Day on 15th August 2026, Prime Minister Narendra Modi placed technology and innovation firmly at the centre of India’s development ambitions. Under his Saptadhara, or "seven streams" of development framework for Viksit Bharat, technology and innovation were identified as one of seven pillars of national progress, with manufacturing, agriculture, food processing, infrastructure, defence, green and blue economy, and soft power being the others.

Prime Minister Modi stressed that India needs to build capability and leadership in AI, quantum technologies, space, robotics and data centres, and announced that one crore, or 10 million, young Indians would be trained in AI skills over the next year.

The scale is striking, but so is the opportunity. If executed well, a programme reaching 10 million young people could strengthen productivity, widen access to emerging jobs and deepen India's capacity to innovate. More importantly, it has a direct bearing on Viksit Bharat, the national ambition to make India a developed nation by 2047, the centenary of its independence, by building the human capital needed to create, adapt and govern the technologies that will shape its future.

India’s AI skilling ambition

India has already shown that it can take digital skilling to considerable scale. YUVA AI for ALL, the free foundational programme under the IndiaAI Mission, had attracted 8.5 million enrolments by July 2026. FutureSkills PRIME, a digital skilling initative run by the Ministry of Electronics and IT with technology industry body NASSCOM has registered more than 3.4 million people from the existing workforce in India across emerging technologies, with more than 1.3 million completing training and certification. Notably, 86 per cent of its participants are from Tier-2 and Tier-3 cities. Andhra Pradesh alone has crossed 100,000 certifications in AI and Big Data Analytics.

These numbers suggest that reaching people is possible. The more difficult question is what happens after enrolment.

Reaching millions is only the first step

That urgency is difficult to overstate. The World Economic Forum estimates that 63 out of every 100 Indian workers will require training by 2030, while 12 may not receive the upskilling they need, equivalent to more than 70 million workers. The QS World Future Skills Index 2027 captures another side of the same problem. India ranks 13th globally overall and 5th for Future of Work, reflecting strong demand for the skills associated with a rapidly transforming economy, but only 18th for Skills Alignment. The gap suggests that labour-market transformation is moving faster than education and training systems are consistently able to respond.

Why AI skills need to go beyond prompting

This is why the definition of "AI skilled" matters as much as the number trained. Learning to use a chatbot or write an effective prompt is useful, but it is only the first layer of capability. The more valuable skill is knowing how to work intelligently with AI: an AI-learner should be able to define a problem, decide where AI can add value, interrogate its output, verify evidence, identify bias and exercise judgement when the technology gets something wrong.

The aim should be to develop young people who can think with AI without becoming dependent on it. There is an important distinction between creating users of AI and creating people who can build with AI. India will need both, but long-term technological leadership will depend increasingly on the latter.

Building AI capability across universities, colleges and industry

That distinction has important implications for delivery. India does not need one course delivered identically to 10 million people. It needs one national ambition delivered through multiple institutions.

Digital platforms can provide foundational literacy at enormous scale. Universities and colleges can provide disciplinary depth, research exposure and critical thinking. ITIs and polytechnics can connect AI to manufacturing, electronics, automotive services, logistics and other occupational pathways. Industry can bring current technologies, recognised certifications, mentors, apprenticeships and real workplace problems. Government's role is to provide the common direction, standards and national architecture that allow these different routes to work towards comparable outcomes.

Why universities have a central role

Universities have a particularly important role because AI capability cannot remain confined to computer science departments. An engineering student should be able to apply AI to an industrial problem. A management student should learn how it can redesign a supply chain or business process. A law student should be able to interrogate an AI-generated argument for evidence and bias. Students in agriculture, healthcare, climate science and Indian languages should encounter AI within their disciplines.

Credit-bearing AI modules, industry-led challenges, apprenticeships and project-based learning can provide stronger evidence of capability than course completion alone. The test should increasingly be not simply whether a student has studied AI, but whether he or she can use it to improve an outcome.

What India can learn from Singapore

There are useful international lessons. Singapore, for example, is seeking to develop 100,000 “AI bilingual” workers through its National AI Impact Programme, people who combine expertise in their profession with sufficient AI capability to transform workflows within it. The approach starts from the workplace: how can an accountant, lawyer or other professional use AI to transform a real workflow while retaining judgement and responsibility? Its programmes are being developed with industry and professional bodies, with hands-on application at their core.

India operates at a vastly different scale, but the principle is relevant: AI capability works best when it is layered onto domain expertise rather than treated as a generic technology skill.

Creating an AI skills ladder

A national delivery architecture could therefore operate as an AI skills ladder. The first level should offer mass foundational literacy: understanding what AI is, how to use it responsibly and where its limitations lie. The second should focus on applied AI within disciplines and occupations, delivered through colleges, universities, ITIs, polytechnics and industry-linked programmes. The advanced layer should develop those capable of building models, applications, datasets and new AI-enabled businesses. Industry-sponsored certifications and projects can sit across these levels, provided they measure demonstrated competence rather than familiarity with a particular product.

Measuring capability, not just course completions

There is one further shift worth making: from counting participation to measuring capability. Enrolments and certificates matter, particularly when the objective is democratising access. But the next set of indicators should ask harder questions. Did learners complete the programme? Can they apply what they learnt? Can they solve a real problem with AI? Has the training improved employability or workplace productivity? And is the opportunity reaching women, smaller towns, Indian-language learners and institutions outside the country's established technology hubs?

The existing reach of programmes such as FutureSkills PRIME, where a large majority of participants come from Tier-2 and Tier-3 cities, shows that a broad-based model is possible.

What AI skilling could mean for Viksit Bharat

The Prime Minister's 10 million target gives India the scale of ambition that this moment demands. The task now is to give that number depth. Ten million certificates would be an impressive achievement. Ten million young Indians who can question an AI-generated answer, apply AI to a real problem, improve productivity and eventually create something new would represent something much more significant: national capability.

That is what AI skilling should ultimately mean for Viksit Bharat: not greater dependence on AI, but greater human capability because of it. If government, universities, vocational institutions, industry and digital-learning platforms can build that capability together, India's AI-skilling mission could do more than prepare a generation to participate in the AI economy. It could help prepare one to shape it.