🇮🇳 India’s Moment: Can We Become the Next AI Superpower?

We’re living through a technological tectonic shift. Artificial Intelligence, Robotics, NLP, Machine Learning, Automation, and Computer Vision—collectively dubbed Industry 4.0—are no longer future-facing concepts. They are transforming power structures, national competitiveness, and how humanity functions at its core.

As the global AI race accelerates, a serious question demands our attention:

Can India be more than just a participant? Can we lead?

Let’s not pretend the answer is simple. But if we reflect on history—and look closely at our trajectory—it becomes clear:

India doesn't play the same game as the West or China.We rewrite the game.

⚖️ Global AI Investments: India’s Disadvantage?

Let’s begin with the hard numbers:

• USA: $200 billion+ annually in AI investments (public + private)

• China: ~$66 billion annually

• Europe, Japan, South Korea (combined): ~$40 billion

• India: ~$6 million so far, with ₹8,000 crore ($1B+) committed over 5 years through the IndiaAI Mission PIB, 2024

Even with purchasing power parity, India’s investments are a mere fraction of global leaders. The natural conclusion might be that India stands no chance.

But here’s where it gets interesting:

India doesn’t just invest capital. We invest resilience, scale, and ingenuity.

🚀 Leapfrogging, Not Catching Up

Every tech wave saw India lagging in infrastructure—until we leapfrogged:

• We skipped landlines → Jumped to mobile

• Skipped credit cards → Created UPI, the world’s best payment infrastructure

• Had vaccine scarcity → Built CoWIN, a global health logistics benchmark

• Lacked national ID → Built Aadhaar, the largest biometric system on earth

Why not AI next?

🎯 India’s Unique Strengths in AI

1. Population-Scale Digital Infrastructure

India has built a stacked digital base:

• Identity (Aadhaar)

• Payments (UPI, 11B+ monthly transactions as of 2024)

• Health (ABHA, CoWIN)

• Governance (DigiLocker, UMANG)

These generate massive, real-time, multilingual, multimodal data streams—exactly the fuel AI models need.

2. Talent Depth and Growth

India is home to:

• Over 1 million AI professionals

• The second-largest AI developer base globally [NASSCOM, 2024]

• The fastest-growing GitHub AI contributor base, on track to surpass the US by 2028 [GitHub CEO, 2024]

We’re already the engineering backbone of global AI models. Now, it’s time we become the brain too.

3. Real-World Problems at Scale

We’re solving for 1.4 billion people:

• In 20+ languages

• Across vastly unequal digital access

• With limited resources

This makes India the most fertile testing ground for scalable, frugal, inclusive AI.

🧱 But There Are Gaps. Real Ones.

Despite all this potential, we’re not where we should be.

1. Talent: Quantity Over Quality

• We lack top-tier AI researchers.

• A disproportionate share of our best minds migrate abroad.

• Our engineering colleges produce coders—but not enough core AI scientists or interdisciplinary thinkers.

🧠 Fixes:

• Build and fund 30+ world-class AI research institutions

• Offer global salaries to retain talent

• Create visa pathways for AI researchers from the Global South

• Develop AI career tracks across engineering, law, ethics, product, and design

2. Data: Locked, Fragmented, and Unusable

Despite UPI and Aadhaar, quality AI training data is inaccessible:

• Corporate-held datasets are closed or siloed

• Government data is outdated or poorly structured

• Indic language data is still sparse

🧠 Fixes:

• Create open data marketplaces with privacy and consent safeguards

• Incentivize private sector data-sharing via credits, tax breaks, or IP rights

• Appoint a Chief Data Officer of India to standardize and unlock datasets

• Scale multilingual data generation via Bhashini and telecoms

3. R&D: From Publication to Product

India ranks among the top 5 in AI publications, but our patent output and productization are low:

• R&D investment is just 0.6% of GDP (vs 2.8% in the US and 2.4% in China)

• CoEs lack autonomy and scale

• Startups rarely emerge from university research

🧠 Fixes:

• Increase AI R&D funding 5x over next 5 years

• Give AI parks and CoEs budget autonomy, private fundraising power

• Encourage professor-led spinouts

• Forge international R&D partnerships, especially with other emerging markets

🏢 Role of Indian Corporates: Beyond AI-as-a-Service

Indian corporates—IT giants, banks, pharma leaders, FMCGs—must play a more ambitious role:

• Stop thinking of AI as a service delivery enhancement.

• Start treating it as a core R&D and IP investment zone.

What’s needed:

• Set up AI Research Wings, not just analytics units

• Collaborate with startups and CoEs to co-create AI IP

• Build India-first LLMs optimized for domain-specific problems: agri, health, infra, insurance

• Fund AI skilling across vendors, partners, and developers

If Indian conglomerates continue to treat AI as a plug-and-play efficiency tool instead of a strategic capability—they will miss the next 20 years.

🧑‍🚀 The Startups and Innovators

India is brimming with AI-driven startups. But the missing piece is patient capital, policy trust, and national support.

What we need:

• Access to GPUs + compute credits

• Govt-backed seed funds for AI infra-layer startups

• Real-world sandboxing opportunities in public infrastructure, health, governance

• Export channels to global south countries

India can lead the Global South’s AI Stack—just like it did with UPI.

🏛️ What the Government Must Continue and Accelerate

To its credit, the government has already launched:

• IndiaAI Mission (₹10,371 crore outlay)

• 10,000 GPU procurement (backed by NVIDIA H100s and H200s)

• Bhashini (language stack)

• IndiaAI Datasets Platform

• DPI Strategy for global diplomacy

But we now need urgency in execution:

• Don’t stop at infra—invest in human capital and AI commons

• Push India’s AI diplomacy globally through GPAI, G20, and BRICS+

• Build India’s equivalent of HuggingFace, StabilityAI, and OpenCompute

🌏 What’s at Stake?

This is not just a race for GDP. This is a race for global AI philosophy.

While the West builds AI for capital,While China builds AI for control,India can build AI for inclusion, humanity, and democracy.

Imagine:

• AI that diagnoses tuberculosis in tribal clinics

• AI that automates compliance for small kirana shops

• AI that helps farmers manage soil, water, weather

• AI that helps citizens navigate public services in their own dialects

🔮 The Indian AI Superpower

India will not become an AI superpower by copying America or China.

We will lead by:

• Redefining the game

• Solving for 1.4 billion people

• Scaling responsibly

• Open-sourcing generously

We need all hands: the state, the startup, the student, the scientist, the corporate, and the citizen.

The next five years are critical.

The question is not whether India can lead AI.The question is whether we have the courage to do it in our own way.

Let’s rise together—not just to catch up, but to define the future.

References:

1. IndiaAI Mission – PIB Release, 2024

2. GitHub CEO Thomas Dohmke praises India's developer growth, Mint, 2024

3. NASSCOM AI Skilling Report, 2024

4. Digital Personal Data Protection Act, 2023