WHAT’S THE REAL INDIAN IT CRISIS?

Before we discuss Indian IT, the crisis it is quietly entering, and the predictions that are unsettling software professionals across the country, let’s begin with something seemingly unrelated. It may feel out of context at first — but by the end of this conversation, you’ll understand exactly why this story matters.

There’s a Japanese company named TOTO — a century-old brand known primarily for manufacturing bathroom equipment and sanitary ware. Recently, the company unexpectedly found itself in the spotlight. Why? Because its stock surged after investors realized that TOTO’s ceramic expertise could also be used in the production of components required for advanced AI chip manufacturing.

Think about that for a second.

A company once associated almost entirely with toilets and bathroom fittings suddenly became relevant to the future of artificial intelligence — not because it abandoned its core identity, but because it saw an opportunity beyond it.

And TOTO is not alone.

Companies like NVIDIA were once seen largely as gaming hardware manufacturers before they became the backbone of the AI revolution. Even companies like TSMC and ASML invested heavily in semiconductor and chip ecosystems long before the world fully understood how critical AI infrastructure would become. At that point, nobody could clearly predict the scale at which AI would transform the world. But these companies understood one thing early: the future would belong to those building the foundations of the next technological wave.

That belief changed everything.

So why are we talking about TOTO, semiconductors, and AI infrastructure while discussing Indian IT?

To understand that, we need to go back to the 1990s and look at India from a completely different perspective.

India in the 90s lacked a strong manufacturing ecosystem. We did not have massive oil reserves either. But we had something else — engineering talent.

And that became our economic engine.

India built what eventually became the “Global Delivery Model” — writing code in India at lower costs and delivering software services to clients sitting thousands of miles away in the United States and Europe. It was, in many ways, a large-scale labour arbitrage model. Indian talent was billed globally at premium rates while being produced domestically at far lower costs.

But ordinary graduates didn’t see it that way.

For middle-class India, it looked like a miracle.

Engineering colleges became placement factories. Campus recruitment felt like a festival. Students with decent technical skills suddenly found themselves earning in dollars, travelling abroad, and living what many families saw as the modern Indian dream.

This was also the era when the term “body shopping” entered the IT vocabulary. Offshore projects became aspirational. Every family seemed to have someone working either for the US or in the US. The software industry transformed the social and financial landscape of India.

And honestly, for a long time, it worked beautifully.

Until the rules of the game began to change.

Around the mid-2010s, the global conversation started shifting toward artificial intelligence. While the exact details remain debated publicly, there have long been discussions about how some Indian IT leaders underestimated the long-term disruptive potential of AI because automation threatened the traditional hourly billing model on which much of the Indian IT industry was built.

That hesitation matters today.

Because while the world was thinking about building AI, much of Indian IT was still focused on scaling manpower.

At one point, conversations around 70-hour work weeks dominated headlines. Many engineers openly questioned this culture. Their argument was simple: working longer hours to maintain foreign software systems or support global AI products would not fundamentally transform India’s technological future.

They wanted India to build intellectual property, not just maintain it.

And the irony is painful.

India had millions of engineers, one of the world’s largest data pools, and an IT export industry worth hundreds of billions of dollars. Yet much of the ecosystem remained focused on service delivery instead of foundational technology creation.

While the US produced companies like OpenAI and China accelerated aggressively with players like DeepSeek, India largely remained concentrated in service layers — integrations, support systems, quick-commerce platforms, outsourced engineering, and enterprise maintenance.

The question is uncomfortable, but necessary:

Is that all we are capable of?

Today, AI tools can automate large portions of repetitive coding work at speeds and costs impossible for junior developers to compete with manually. And this is where the real fear begins.

Because deep down, parts of Indian IT still appear to be betting that cheap human labour may remain economically viable longer than expected — hoping global clients continue depending on massive workforces instead of fully transitioning toward AI-driven software development.

That desperation is real.

And strangely, this entire situation resembles something from colonial history.

Two hundred years ago, the British took raw cotton from India, processed it in Manchester, and sold expensive finished products back to us.

Today, global technology giants collect data from billions of users worldwide — including Indians — train large AI models in Silicon Valley and elsewhere, and then sell AI subscriptions and platforms back to emerging economies like India.

Once again, raw value leaves the country while high-value intellectual property is owned elsewhere.

Even today, India’s strongest role in AI largely remains implementation, integration, and maintenance.

Meanwhile, multinational corporations are increasingly setting up Global Capability Centres directly in cities like Bengaluru, Hyderabad, and Pune — bypassing traditional Indian IT middle layers altogether. GCCs now employ millions of Indians directly. The talent remains in India, but the ownership of products, patents, platforms, and profits often does not.

And that changes everything.

Campus placements in major tech sectors are already slowing. Entry-level coding jobs are becoming more uncertain. The old software dream that defined Indian middle-class ambition for nearly three decades is entering a phase of disruption.

What India is facing today is not merely an IT slowdown.

This is a defining moment for the country’s technological future.

For over 30 years, India became the world’s back office — efficient, disciplined, hardworking, and globally reliable. But history rarely rewards nations that only execute. It rewards nations that create.

The real question is no longer whether AI will replace jobs.

The real question is whether India will remain a service colony in the AI era — or evolve into a creator of technology itself.

And that shift cannot happen through motivation alone. It requires a complete change in ambition, investment, and long-term thinking.

So what are some changes India seriously needs to consider?

Because the countries that own AI models, semiconductor ecosystems, cloud infrastructure, and intellectual property will shape the next century.

Everyone else will simply rent the future from them.

India has the talent. India has the scale. India still has the opportunity.

But the AI revolution is not waiting for anyone.

Either India becomes part of the next technological wave — or spends the next fifty years servicing someone else’s.

Having said so much, I want to leave you with an entirely different question here ..
AI is definitely growing by leaps and bounds but are our systems, companies and the world ready to manage those systems and the allied costs?. Do think about it and see you with the next tech blog ....over the next week