Why India is Lagging Behind in the AI and Tech Industry?
India is one of the largest producers of engineers in the world, with institutions like the IITs churning out thousands of graduates every year. Yet, the country struggles to retain its top talent, with many engineers moving abroad for better opportunities. Meanwhile, other nations like the U.S. and China continue to dominate the artificial intelligence (AI) and machine learning (ML) sectors with groundbreaking innovations. This article explores the key reasons behind India's struggles in the AI and tech industry and why it has failed to produce a globally competitive platform in these fields.
1. India Produces Engineers, But Where Are the Jobs?
Every year, around 1.5 million engineers graduate in India, but the country faces a severe lack of employment opportunities. Many engineers either remain unemployed or settle for non-technical jobs. The absence of high-tech industries that can absorb this vast talent pool forces many skilled professionals to seek jobs abroad.
Case Study: The Brain Drain to the West
- The developement team head of DeepSeek, China’s leading AI research team, is an Indian.
- The landing system of SpaceX’s reusable rockets was developed under the guidance of an Indian engineer at SpaceX.
- Sundar Pichai (CEO of Google) and Satya Nadella (CEO of Microsoft) are Indians who built their careers abroad.
Despite India's rich talent, the lack of a strong research and innovation ecosystem has made it difficult for homegrown professionals to thrive in their own country.
2. The Absence of a World-Class AI Platform from India
While the U.S. has OpenAI (ChatGPT) and China has DeepSeek, India has no globally recognized AI or ML platform. The closest example, AstroTalk, is a startup in astrology, which does not compare to AI giants in other nations.
Why Does India Lack AI Innovations?
1. Poor Government Support – Unlike China and the U.S., India lacks structured policies to fund AI startups and high-tech innovations.
2. Limited R&D Investments – Companies and the government invest very little in cutting-edge research.
3. Traditional Mindset – The education system and societal expectations focus on getting a degree rather than encouraging innovation.
4. Risk-Averse Investors – Indian investors are more inclined toward proven business models (e.g., e-commerce) rather than deep-tech startups.
3. India’s "Rat Race" Mentality vs. Innovation Culture
In India, success is often measured by exam scores and degrees rather than creativity and problem-solving. The education system emphasizes rote learning, leaving little room for innovation.
Contrast with the U.S. and China
- U.S. encourages entrepreneurship – Stanford and MIT students frequently drop out to start revolutionary companies (e.g., Mark Zuckerberg, Elon Musk).
- China’s government actively funds AI startups, ensuring continuous research and development.
Meanwhile, in India, a fresh graduate is expected to secure a safe job rather than take risks in AI or deep tech startups.
4. The Startup Ecosystem in India: Challenges and Limitations
While India has a thriving startup ecosystem, most successful Indian startups focus on services like e-commerce, fintech, or food delivery rather than AI/ML.
Why AI Startups Struggle in India?
- Lack of Infrastructure – AI and ML require massive computing power, but India lacks world-class supercomputing facilities.
- Funding Issues – Unlike U.S. and Chinese startups, which receive billions in funding, Indian deep-tech startups struggle to raise capital.
- Slow Government Approvals – Any tech-based startup in India faces bureaucracy and red tape, slowing down progress.
5. The Way Forward: How India Can Compete in AI & Tech
For India to compete with the U.S. and China in AI and ML, major reforms are needed:
1. Government-backed AI Research Labs – Similar to China’s DeepSeek, India must invest in world-class AI labs.
2. Startup-Friendly Policies – Easier funding, faster approvals, and tax benefits for AI startups.
3. Industry-Academia Collaboration – IITs and research institutions should work closely with industries to create practical AI solutions.
4. Encouraging Risk-Taking – Schools and colleges should promote innovation and entrepreneurship rather than just exam-based success.
Conclusion:
India has the talent, but systemic issues prevent it from becoming a global leader in AI and deep tech. Without strong government policies, increased funding, and a shift in cultural attitudes, India will continue to lag behind in the AI revolution.
