Shri Sunil Gupta, Co-Founder, managing director & CEO, Yotta Data Services on India’s AI future.
India’s latest Union Budget quietly placed a strategic bet on artificial intelligence: a tax holiday for export-oriented AI and data infrastructure workloads. While the announcement triggered mixed reactions, industry leaders argue the move is less about short-term tax incentives and more about positioning India as a global AI compute hub.
At the heart of this shift is a hard reality: AI does not run on ambition alone. It runs on data centres, GPUs, power, cooling, and talent. And India is still under-supplied on all four.
“India wants to attract global AI workloads and become a serious hub for data centres and computing power.” ~ Shri Sunil Gupta
This move comes at a critical time. AI adoption is growing fast, but the real constraint is not ideas or use cases. The real constraint is infrastructure.
The AI Economy Runs on GPUs and Data Centres
AI needs massive computing power. Today, even a few thousand high-performance GPUs can make a big difference in India’s overall capacity. But this is far from enough.
Highlighting the scale of India’s AI infrastructure gap, Gupta notes Yotta’s rapid progress, saying, “I am happy that I have 10,000 GPUs. But my 10,000 GPUs are almost like 70% of India’s GPUs.”
This shows how early India still is in the AI infrastructure journey. As AI moves from experiments to real-world use – where AI tools serve millions of users demand for computing power will grow sharply. The current shortage of GPUs is not a short-term issue. It reflects a deeper gap in national capacity.
Why the Tax Holiday Matters
The Budget incentive is aimed mainly at global workloads that currently get hosted in places like Singapore. The idea is simple: if foreign companies and cloud providers host their global AI workloads in India, the country benefits in multiple ways.
Data centres bring more than servers. They create demand for power, cooling, construction, physical security, networking, and facility management. A single large data centre project can engage thousands of workers during construction and create long-term technical and operations jobs.
This also strengthens India’s cloud ecosystem. Global cloud players are increasingly partnering with Indian data centre and cloud providers to serve the local market. Over time, this builds domestic capability instead of keeping India dependent on foreign infrastructure hubs.
Is AI in a Bubble? The Shift Is Real, Not the End
There is growing talk about an “AI bubble,” especially as AI tools become very strong at writing software code. This is already changing how software is built. Routine coding work is getting automated.
But this does not mean jobs will disappear. The nature of work is changing. The focus is shifting from writing code to designing AI solutions, building use cases, connecting AI to real business problems, and deploying AI safely at scale.
This plays to India’s long-term strengths. For decades, Indian teams have worked on implementing technology for global companies. The same model applies to AI: understanding business context, data, workflows, and deploying AI tools in banking, agriculture, healthcare, manufacturing, media, and government systems.
In simple terms, coding is becoming easier. Thinking, designing, and deploying AI is becoming more important.
Cybersecurity: Risks Rise, So Do Safeguards
As AI moves into core business systems, cyber risks will increase. This is not unique to India. Every major technology shift has brought new risks along with new tools to manage them.
AI security, guardrails, and governance frameworks are already becoming part of enterprise AI planning. The global conversation is not only about building AI, but also about preventing misuse and protecting systems.
The Bigger Picture for Leaders
The Budget announcement should be seen as a long-term infrastructure play, not a short-term tax benefit. Attracting global AI workloads helps India grow its data centre industry, build GPU capacity, create jobs, and strengthen its position in the global AI economy.
For IT leaders and CXOs, the key question is practical:
Do you have access to compute? Are your teams ready to deploy AI? Are you investing in skills beyond basic coding?
The AI hype cycle will go up and down. But data centres, GPUs, skilled engineers, and AI deployment capability are long-term assets. In the next phase of AI growth, infrastructure and execution — not just ideas — will separate leaders from followers.