Rise of Artificial Intelligence: the threat of jobless future or better job opportunities through reskilling and upskilling.

The Machine Learns, So Must We

In a Bengaluru office park, a young graduate who spent three years answering customer queries for a global bank finds that a chatbot now handles most of the calls she used to take. A few kilometres away, a radiologist in a district hospital reads twice as many scans as before, because software flags the suspicious ones first and lets her spend her time on the hard cases. Both stories are about the same technology. One reads like the first chapter of a jobless future; the other reads like a promotion. The difference between them is not the machine. It is whether the worker was prepared, and whether the society around her chose to prepare her. Artificial intelligence will destroy many tasks and some jobs, but whether India faces a jobless future or a better one depends on how fast and how fairly it reskills its people, because technology sets the menu while policy and learning decide who gets to eat.

To begin with, the fear is old even if the machine is new. When textile machinery spread through England, the Luddites between 1811 and 1816 broke the frames they believed would starve them. In 1930 John Maynard Keynes coined the phrase technological unemployment, warning that we were finding ways to save labour faster than we could find new uses for it. Yet each wave also created work no one had imagined: the railway gave the world the station master, electricity gave it the electrician, the computer gave it the software engineer. What makes the present anxiety sharper is that artificial intelligence does not only replace muscle. It imitates judgement, language and pattern recognition, the very capacities that once protected white-collar work from machines.

The case for alarm deserves to be taken seriously. In 2013, Carl Frey and Michael Osborne of Oxford estimated that about 47 per cent of American jobs were at high risk of automation. Since the release of ChatGPT in November 2022, generative models have begun drafting code, contracts and marketing copy. India is exposed in a particular way. The Economic Survey 2024-25 noted that a large part of the country's IT workforce does low value-added service work, exactly the routine cognitive tasks that AI performs well, and warned that these roles are particularly vulnerable to automation. TCS's decision in 2025 to shed about 12,000 roles was read by many as an early signal. NITI Aayog's 2025 roadmap on jobs in the AI economy estimated that, in a business-as-usual scenario, employment in the technology sector could fall from 7.5-8 million in 2023 to about 6 million by 2031.

Yet the same evidence also points the other way. The World Economic Forum's Future of Jobs Report 2025 projected that, between 2025 and 2030, technological and economic change would create about 170 million jobs worldwide and displace about 92 million, a net gain rather than a collapse. History offers a telling detail: when automated teller machines spread in America, the economist James Bessen found that the number of bank tellers grew, because cheaper branches meant more branches, and tellers moved from counting cash to selling services. Jobs are bundles of tasks, and machines usually take some tasks, not whole jobs. The same NITI Aayog roadmap that warned of losses estimated that with deliberate action India could create up to 4 million new AI-enabled jobs by 2031. The Economic Survey itself describes the future of work as augmented intelligence, humans and machines working together rather than one replacing the other.

What decides which path a country walks is reskilling and upskilling. The economist Daron Acemoglu distinguishes between technology that augments workers and "so-so automation" that replaces them without raising productivity much. Which kind spreads is a choice of firms and governments, not a law of nature. Here India's demography is both its greatest asset and its greatest risk: more than 65 per cent of its people are under 35. A young, trained workforce can become the world's AI back office and front office alike; a young, untrained one becomes a reservoir of frustration. Skill India and the Pradhan Mantri Kaushal Vikas Yojana, launched in 2015, built a base, while FutureSkills Prime, run by NASSCOM with the IT ministry, offers courses in AI, cloud and data. The IndiaAI Mission, approved in 2024 with an outlay of over ₹10,000 crore, adds computing capacity and AI skilling.

"Tomorrow's illiterate will not be the man who can't read; he will be the man who has not learned how to learn." (Herbert Gerjuoy, quoted by Alvin Toffler in Future Shock, 1970)

Reskilling, however, is not merely about coding. A curious feature of AI is Moravec's paradox: machines find abstract reasoning easy and simple physical or social tasks hard. The nurse who comforts a patient, the electrician who works in a cramped ceiling, the teacher who notices that a child is hungry and the counsellor who calms a farmer in debt all do work that is difficult to automate. India's care economy, green energy installation and tourism can absorb millions if training and dignity are attached to them. Equally, AI can widen the circle of opportunity: tools such as Bhashini, which translates across Indian languages, can let a weaver in Varanasi or a farmer in Vidarbha use services that were once open only to English speakers. Upskilling then means giving people both the human skills machines lack and the digital fluency to use machines as tools.

Nevertheless, the optimistic story has blind spots that a serious essay cannot ignore. The great majority of Indian workers are in the informal sector, with no employer to fund their retraining and little time to attend a course. Women, who already face low labour force participation, may find that the clerical and data-entry jobs that drew them into offices are the first to go. The platform economy that AI powers creates work without security: NITI Aayog estimated 77 lakh gig workers in 2020-21 and projected 2.35 crore by 2029-30. The Code on Social Security, 2020 recognised gig and platform workers for the first time, but its benefits are still being built. A reskilling drive that reaches only urban graduates would turn AI into a machine for widening inequality.

Therefore the way forward lies in treating skilling as a lifelong public good rather than a one-time certificate. Singapore's SkillsFuture, launched in 2015, gives every adult citizen credits to spend on approved courses throughout life, an idea India can adapt through its digital public infrastructure. Schools must teach learning to learn, as the National Education Policy 2020 urges with its emphasis on critical thinking and vocational exposure from the middle school years. Industry must share the gains of productivity by retraining before retrenching, and the state must extend social security to platform workers so that the cost of transition does not fall on the weakest. Mahatma Gandhi once said that he objected not to machinery as such but to the craze for machinery that displaced labour; his test still applies, since technology should serve people, not the other way round.

In the end, the graduate in Bengaluru need not be the face of a jobless future. If she is offered a course in data annotation or AI testing, a stipend while she learns and a firm willing to hire her back, she could become the person who trains the chatbot that replaced her old role. The radiologist's story shows what is possible when skill meets the machine: more work done, better work done, and human attention reserved for what matters most. Artificial intelligence is neither a curse that will empty our offices nor a blessing that will lift everyone on its own. It is a test of whether India can learn as fast as its machines do. If it passes, the AI century will be remembered not for the jobs it ended but for the abilities it awakened in a billion people.