Why India Struggles to Build Its Own Tech Giants—And What’s Changing Now
Indian social media is buzzing with one question: If China can, why not India? Why can’t the country create its own Facebook, Google, or ChatGPT? The answer isn’t simple—it’s a mix of funding gaps, market challenges, and technological delays. Let’s break it down.
1. The Funding Problem: R&D Needs a Boost
Money matters, but it’s not just about budgets—it’s how they’re used. The U.S. spends 3.4% of its GDP on research and development (R&D), China invests 2.4%, and Israel leads with 5.7%. India, however, allocates just 0.6% of its GDP to R&D. Private companies in India contribute only 36% of total R&D spending, compared to over 70% in China and the U.S. Without coordinated efforts between the government and private sector to prioritize innovation, breakthroughs remain out of reach.
2. The Market Challenge: Competing With Giants
Imagine an Indian startup creating a homegrown search engine. Would users abandon Google for it? Unlikely. American tech giants dominate with established, affordable products. India’s open market leaves startups vulnerable to being crushed by competition—as seen with homegrown social media platforms like Coup, which faded quickly. China’s closed market, by contrast, shields its startups, giving them room to improve and succeed. For India, balancing openness with protection is key.
3. Playing Catch-Up in Technology
AI is today’s cutting edge, but building it requires stepping stones: semiconductors, smartphones, and internet infrastructure. India lags in these areas, and falling behind early makes it harder to catch up. Even if India skips ahead to focus on AI, there’s another hurdle: advanced chips. Most AI systems rely on semiconductors from U.S.-based Nvidia, and Washington restricts sales to countries like India. While OpenAI trained ChatGPT on 10,000 chips—a number India could match—the U.S. and China have unlimited access, pushing their AI further ahead daily.
What’s Changing? India’s New AI Push
The Indian government is finally stepping up. Union IT Minister Ashwini Vaishnaw recently announced plans to host open-source AI models like DeepSeek on Indian servers, addressing data privacy concerns. The initiative will be powered by the India AI Compute Facility, which has secured 18,000 GPUs (graphics processing units) to develop a homegrown Large Language Model (LLM).
Key moves include:
- Affordable Access: Government subsidies for computing costs at less than $1 per unit
- Local Chip Development: Partnerships to co-develop Indian-made GPUs
- Focus on Data Quality: Prioritizing high-quality datasets for better AI outcomes
The Road Ahead
China’s success came from state-backed stockpiling of chips and massive subsidies for tech firms. The U.S. thrived through government-military partnerships with Silicon Valley. India’s path requires a unified mission—bringing together policymakers, startups, investors, and citizens.
Open-source models and local compute infrastructure are a start, but long-term success needs sustained R&D funding, smarter market policies, and patience. Without this, India risks staying on the sidelines of the tech revolution. The clock is ticking, but the pieces are finally moving.