Recommended Free Tools
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Infosys co-founder Nandan Nilekani expects AI to affect some jobs, but he does not expect most affected roles to disappear entirely. In a Moneycontrol interview published February 22, 2025, he argued that AI will automate some tasks within many jobs, help workers become more productive, and create kinds of work that are difficult to anticipate. Those are his views, not a quantified labor-market forecast.
What Nilekani said about AI and jobs
Asked whether AI’s effect on jobs would be a major problem or an opportunity, Nilekani drew a distinction between automating tasks and eliminating entire jobs. He said only a few jobs would be “totally taken out,” while many others would lose some tasks but still leave people with work to do. The full Moneycontrol interview was a conversation with Managing Editor Nalin Mehta at an AIMA event in New Delhi on February 21, 2025, and was published the following day.
In Nilekani’s account, AI can make people more productive and effective in their existing roles. He also expects it to create new jobs that were not anticipated beforehand. The interview offers no estimate of how many jobs might be lost or created, or when those changes might occur; its claims are qualitative expectations rather than measured outcomes.
Windows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOutdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWhy he sees opportunity as well as risk
Nilekani described himself as someone who tends to be optimistic, a qualification that matters when weighing his outlook. He also said the benefits will depend on how AI is designed and who benefits from it. He contrasted an extractive model, where one party controls data and captures the profits, with an inclusive model intended to distribute benefits more broadly. The interview presents this as a choice about the technology’s design and distribution, not proof that AI’s gains will automatically be shared.
#1 Best Overall
That distinction puts his optimism in context: even if AI raises productivity, the result for workers will depend in part on how organizations deploy it and how the resulting gains are shared. The exchange does not specify a policy plan or predict which model will prevail.
What his comments mean for education and skills
When asked how educational institutions should respond, Nilekani argued for developing capabilities that may remain useful as specific tools and tasks change. He named empathy, motivating others, leadership, collaboration, first-principles thinking, and creativity. He preferred this broad foundation to prescribing a fixed list of technical skills, since a particular skill may no longer be relevant several years later.
Rank #2
This is a recommendation about what education should emphasize, not evidence that these abilities are immune to automation. Nor does the interview provide a curriculum, training plan, or assessment of which occupations will need particular skills.
What the interview establishes—and what it does not
The conversation is useful for understanding Nilekani’s perspective, but it is not an independent labor-market study. It provides no year-specific statistic for job losses, job creation, or tasks automated, and it does not quantify the likely scale or timing of disruption. Claims about employment outcomes should therefore remain attributed to him rather than treated as established forecasts.
Nilekani also discussed AI applications in education, agriculture, and health, against a backdrop of shortages of teachers, doctors, nurses, and other skilled workers. He sees AI as having potential to amplify scarce services and workers; the interview does not show that these applications will produce particular employment outcomes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess future claims about AI job losses
When comparing predictions, check what each source means by “job loss.” A projection about automating tasks is not the same as a prediction that an occupation will disappear. Also look for the geography, industries, and time horizon covered, and whether the number describes an observed result or a forecast. Nilekani’s interview supplies no comparable employment figures, so it cannot establish how his outlook stacks up numerically against other predictions.
His central point is narrower: AI may change the tasks people do without removing every job those tasks belong to. Whether that change translates into better work, fewer roles, or broadly shared productivity gains remains an open question in the interview.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
