The technology skills equation is changing faster than India’s traditional higher education system can adapt. As AI increasingly takes over routine coding, analysis and other execution-heavy tasks, the value of simply knowing a programming language or having an engineering degree is being questioned. What is emerging instead is a premium on problem-solving, critical thinking, adaptability and the ability to work effectively with AI.
For Vishwa Mohan, Founder & CEO, upGrad School of Technology, this shift is also exposing a longstanding disconnect between what students learn in engineering colleges and what industry expects from them when they enter the workforce.
In an exclusive interaction with Express Computer, Mohan discusses why the industry-academia gap is widening, how AI is changing the definition of employability, why technology education needs to evolve faster, and why cybersecurity and quantum computing need to become part of the next generation of engineering education.
From “show me the code” to “show me the thinking”
Mohan’s assessment of the changing technology workforce starts with a simple shift in what employers value.
“When I started coding, I was studying between 2006 and 2011. And then when I joined Oracle, at that time, people used to say that idea is cheap; show me the code,” he says. “Fast forward to today, I think it’s taken a 360-degree shift where we say, ‘Code is cheap; show me the thinking.'”
He believes this shift should fundamentally change what universities prioritise. Computer science fundamentals such as databases, operating systems, compilers and how computers work will remain essential, but a significant part of technology education needs to respond to rapidly changing industry requirements.
At the same time, he argues that universities need to continuously update the practical component of their curriculum.
The industry-academia gap is widening
Mohan says the gap between education and industry has existed for years, but the speed of AI development is making it considerably wider. “The problem statement still holds true, but the gap has become much deeper. All thanks to every few months, Sam Altman and Claude are throwing new models, which is showing how the deeper the gap has become between what’s being taught in the college and what the student needs to be employable in the industry.”
One reason, according to him, is that technology is evolving faster than the people teaching it. The issue is not academic capability, but industry exposure. “The teachers are not into the industry; they’re not working day in, day out how the trends are moving on. They are not aware of which IDE the students should be using right now, which AI tool they should be leveraging right now, or what exact machine learning models are in demand.”
This creates a paradox where companies say they cannot find appropriately skilled technology talent even as large numbers of engineering graduates enter the workforce.
“The more they are lacking, the gap between industry, how they are moving ahead, and how people are being trained – that gap is becoming deeper and deeper.”
His conclusion is blunt: “Education institutes and universities have to understand that they have to run fast and they have to catch up the train, which is really moving at a bullet speed.”
AI is raising the cost of being average
Mohan believes AI is also changing the economics of employability. He expects most existing jobs to become increasingly AI-enabled rather than simply disappearing.
He believes the ability to think deeply and adapt continuously will become a defining characteristic of the future technology workforce.
AI is democratising access to technology education
The same technology that is disrupting traditional education is also reducing geographical barriers to learning.
Mohan believes cheaper internet, smartphones and increasingly accessible AI tools have created a more level playing field for students outside India’s traditional technology hubs.
“Today, when everything is available at the click, it is available on your phone. I think there’s not much barrier for anyone, whether you come from a Tier 1, Tier 2, or Tier 3 city.”
He believes this could fundamentally change where India’s next generation of technology talent emerges from. “Tier 2, Tier 3, and a lot of small institutes are on an equal footing right now.”
For him, the significance extends beyond education. As intelligence itself becomes increasingly accessible through AI, he expects it to become an essential part of everyday life.
Quantum computing is the next shift
While AI remains at the centre of technology education today, Mohan is already looking beyond the current cycle. “Quantum, because that’s going to fundamentally change how computer science works.”
He believes the intersection of quantum computing and AI will become increasingly important over the next few years, particularly as quantum systems challenge assumptions around computing and security.
That is why quantum is already being introduced into the School of Technology’s curriculum, with the objective of preparing students graduating towards the end of the decade for emerging technology roles.
Engineering education needs industry embedded into learning
Mohan does not position the School of Technology as a replacement for universities. Instead, he sees it as complementing the strengths of the traditional university model with greater industry exposure. While universities provide recognised degrees, campus experiences and multidisciplinary exposure, he says industry needs to play a greater role in preparing students for actual technology careers.
The model, therefore, involves industry professionals teaching students, practical coding from the first day and regular engagement with technology practitioners.
“We try to bring industry professionals. So, when I talk about having to train students on what the industry trend in 2026 is, for that we try to bring the people who are working in the company, say, for example, Google, Microsoft, or LinkedIn, top companies that are actually shipping the code right now.”
The curriculum is also designed to evolve more frequently. “When we design the curriculum, we definitely take the industry into the consultancy, in the help and the collaboration, so that we are actually teaching students what is relevant. Another thing that we have done is that we try to change and update our curriculum every six months.”
Industry participation is intended to become a regular part of campus life rather than an occasional intervention.
Cybersecurity becomes a core engineering skill
As AI-generated code becomes more prevalent, Mohan also believes cybersecurity can no longer remain a specialist subject reserved for students choosing a particular career path.
He expects demand for cybersecurity professionals to increase significantly but also believes every technology graduate needs a basic understanding of security.
In an AI-first technology environment, the ability to build software therefore needs to be accompanied by the ability to understand how that software can be attacked, compromised and secured.
For Mohan, the broader transformation in technology education is ultimately about moving beyond degrees and static skill sets. As AI compresses technology cycles and automates routine execution, the value of an engineer will increasingly depend on the ability to think, adapt, learn and apply knowledge to new problems. The education system, he argues, needs to evolve at the same speed.