There have been many questions over the past few months over whether India’s IT sector will survive the AI wave, whether the 1.5 million engineering graduates we produce every year will be made redundant by AI-driven automation. The reality is, humanity is where it is today because of our ability to adapt, and that will likely continue. Except this time, with AI, we may have to adapt quicker than ever before.
In many ways, that is happening behind the scenes, says Ganesh Gopalan, CEO & co-founder of Gnani. ai. “Our country is, in fact, one of the most innovative in adopting AI. The boardroom sanction for AI is far higher in India than many places in the world, because India is so value-obsessed. They want to see what AI systems can do, and they’ll invest if they see the potential. We look at business problems and say, ‘How can we solve them?’ And often, we’ll use AI behind the scenes.”
He points to real-world use cases as proof that Indian organisations care deeply about quick outcomes. “We work with more than 100 financial services customers,” he continues, “and we build AI-based agents that help, for instance, to automate tasks like lending or reconciling claims. We don’t always talk about AI in the marketing pitch. We say, ‘We will help you collect more money at a lower cost,’ and behind it, we use AI. That’s how you see real adoption.”
Changing labour marketYet, whispers of doom persist, especially around jobs. Indian IT’s bread-and-butter so far lay in providing large teams of coders who do repetitive tasks, the kind that might be replaced or drastically reduced by code-writing AI. “It is already happening,” says Amit Chaurasia, founder of Dataneers. “For a particular task, if I had to hire ten engineers, maybe I will hire two or three. The code generation can happen automatically. But those two or three people need to be experienced. I would rather hire a senior engineer who can review the code. And if the software is complex, I definitely need that experienced person to deal with potential gaps or security issues the AI might not address. So experienced developers will be in demand, because no matter how advanced these large language models become, there are many layers of complexity that still require human oversight.”
Chaurasia’s point underscores a shift in the labour market. “By the time we reach a point where AI is writing all code, we don’t know how thoroughly tested or secure that code will be,” he says. “But already, the job requirement is changing from ‘write these thousands of lines of code’ to ‘inspect, secure, and integrate them.’”
He notes that more junior roles might come under strain, but that a new generation of engineering graduates can nonetheless plan ahead. “I tell students: be aware that AI tools are available. You can stand out if you learn how to use them effectively. There is plenty of room for creativity in everything from advanced systems programming to data storage. But if you are not curious and if you do not keep learning, you will be left behind.”
At the same time, AI can spawn fresh opportunities. “We are at the cusp of something substantial,” says Gopalan. “When you need custom solutions, especially in local languages for large companies in BFSI, retail, telecom, or manufac turing, you can’t simply rely on an off-the-shelf large language model. You need domain-specific solutions. That means a lot of people building smaller, tailored models, writing front-end integrations, or training them on local data, which can be a lot more involved. It’s not all about one giant LLM.” He adds that the same synergy is likely to produce new roles in prompt engineering, AI design, domain strategy, and more. “The combination of domain expertise plus AI knowledge is a winner. We are seeing that with every new project.”
Amit Walia, CEO of Informatica, too, says the job market has expansions in store. “We need cloud security professionals. We need people with deep knowledge of large language models, as well as the folks who can handle areas like data governance. So, yes, some jobs might vanish, but the old story of technology is that every time it disrupts some roles, it tends to create new ones in areas we had never anticipated. And that story continues.”
Education, upskilling are concernsSonica Aron, founder & CEO of HR advisory Marching Sheep, points out that Indian IT’s strength has long been its capacity to adapt. “While AI is reshaping the sector, Indian IT firms have likewise adapted and evolved.”
The concern, she says, is that we still produce 1.5 million engineering graduates every year, many of whom do not receive training in the advanced areas that AI demands. “There is a mismatch,” she says. “But it can be addressed with the right partnerships and upskilling efforts. Those who reskill and align themselves with these emerging AI-based roles will find the future bright.”
Some senior Indian IT execs say the engineering chops of fresh graduates leaves a lot to be desired. The danger is that in the age of AI, these new cohorts could be left behind if not properly upskilled.
India’s well-known service-based mindset has come under criticism too. Some fear that, by focusing on tasks that require only incremental innovation, Indian firms may miss out on building truly original AI products. “We’re simply fulfilling the needs of large clients,” says Chaurasia, “instead of investing in original research or deep tech product development. Investors here are usually more comfortable with safer, smaller bets. That can delay progress. We always hope for big leaps, but you need the environment that encourages it. Where is that fundamental research happening? Primarily in the West, or in China.”
But the field today is a lot more level than it used to be. Gopalan notes that “everything is accessible,” thanks to open-source tools and the cloud. “We no longer have the disadvantage we used to have in the late 90s or early 2000s, where if you were a student in India, you didn’t have the same software environment as an MIT student. Now you do. That’s huge. We just have to seize that advantage.”