Why India Builds Engineers but delayed AI Engines ?

 

India has mastered the art of technology consumption.

 

Where are the operating systems built? In the United States.

Smartphones? Designed in California, assembled in China or Vietnam.

Search engines? American.

Social media platforms? American.

Cloud infrastructure? American again.

Which is precisely why this is not something to be proud of.

Being a large consumer for technology is easy.

Building and owning a technology is what matters.

We are the world champions of tutorials titled:

“How to install cutting‑edge AI in 7 minutes on your laptop.”

 

It’s like being the best restaurant customer in the world while never learning how to cook.

Appreciating all the latest development in AI space in India. 

Let’s examine this technological mystery. 

Why was the delay in launching our own open‑source AI?

 

The IITs & IIMs

 

India proudly reminds the world that graduates from institutions like the Indian Institutes of Technology (IITs) and the Indian Institutes of Management (IIMs) run many global tech companies.

 

Indian‑origin executives are leading companies like Google, Microsoft, and Adobe.

 

But here is the irony:

The CEOs may be Indian.

The research labs are not in India.

 

The foundational breakthroughs usually happen in Silicon Valley, Boston, London, or Beijing not Bengaluru or Delhi.

 

India produces brilliant engineers.

 

But the system primarily trains them to optimise existing systems, not invent new ones.

 

Perhaps globalisation and liberalisation, initiated in July 1991, enabled Western countries to utilise our human resources as relatively cheap labor.

 

Today we call it “outsourcing.”

 

We are extremely good at improving someone else’s machine.

We are less enthusiastic about building a new engine.

 

The Research Budget Exists Mostly in Speeches

 

India’s spending on research and development is under 1% of GDP.

 

For comparison:

• The United States spends roughly 3%

• China spends about 2.5%

• Israel and South Korea spend more than 4–5%

 

Research is expensive, slow, and uncertain.

It requires patience and funding.

That becomes difficult in a system where success is expected every quarter and results must appear before the next election cycle. 

In such an environment, the safest strategy is simple:

Import the technology.

Showcase it at an AI summit.

Repeat next year.

 

But to be fair, India does fund research just not always the kind that builds semiconductors, AI models, or quantum computers.

 

Sometimes we fund extremely important questions like:

 

• Can ancient scriptures predict modern physics?

• Can cow dung or cow urine cure everything from cancer to coronavirus? (Click to see the report)

• Did aviation actually exist 5000 years ago?

 

These questions may be fascinating from a cultural or historical perspective.

 

But unfortunately, none of them have yet produced a working GPU.

 

Modern scientific culture depends on skepticism, debate, and peer review.

Public discourse often prefers viral memes.

 

A spiritual influencer makes a bold claim: “We performed the first plastic surgery millions of year ago.”

A politician repeats it while inaugurating a hospital in fronts of qualified surgeons and gets applaud & validity.

A motivational speaker converts it into a TED Talk.

 

Soon it circulates across millions of phones.

 

Not as a hypothesis.

But as “ancient knowledge that science has finally proven.”

 

This creates a strange environment where pseudoscience spreads faster than actual research papers.

Thanks to social media algorithm.

 

India does produce world‑class researchers.

But many of them leave.

 

They move to places where research funding is stronger, laboratories are better equipped, and intellectual freedom is protected.

 

So the country invests heavily in educating brilliant students and then exports them to ecosystems that actually fund deep research.

 

It’s like raising a champion athlete and then sending them to compete for another country.

 

We proudly celebrates our startup ecosystem.

But most startups focus on:

• Fintech

• Delivery apps

• SaaS tools

• Service platforms

 

All valuable.

 

But very few invest in deep‑tech infrastructure like AI models, chip design, or fundamental research.

 

Why?

 

Because venture capitalists prefer products that can scale in three years & not research that might take a decade.

 

India may soon become one of the largest AI user markets on Earth.

 

Millions of developers will build products on top of AI platforms.

 

But hoping the underlying models may not come from labs thousands of kilometers away.

 

If India truly wants its own open‑source AI revolution, the formula is surprisingly simple:

• Invest seriously in research and long‑term funding

• Keep scientific inquiry independent of political pressure

• Encourage questioning instead of myth making

• Reward curiosity and critical thinking

 

Until then, the national innovation strategy may continue to look like this:

 

Step 1: Wait for a breakthrough in China

Step 2: Showcase its been developed in "centre of excellence" in famous university

Step 3: Write a LinkedIn post about Indian innovation

 

And of course...

 

Step 4: Forward it proudly on WhatsApp.