Can India Catch Up With China in AI Innovation?

By Gopal Patwardhan, CEO, GTT Data Solutions Ltd.

In the rapidly evolving world of artificial intelligence, India finds itself at a critical technological crossroads. Despite being a global powerhouse in IT and software services, the country lags significantly in AI innovation, a trend that threatens its long-standing technological competitive advantage. Recent data paints a stark picture of India’s AI challenges. According to research from PwC, the global AI market is projected to reach $15.7 trillion by 2030, with China and the United States leading the charge. In contrast, India’s AI market remains relatively nascent despite being the second largest market for OpenAI. Further research shows that between 2010 and 2022, only half a percent of the patents in the world’s AI landscape were granted to India, while China and the US received 60% and 20%, respectively.

Innovation Ecosystem Comparison
China’s AI ecosystem is powered by aggressive state support and academic innovation. Tsinghua University has emerged as a breeding ground for AI startups, producing leading companies like Zhipu AI, Baichuan AI, Moonshot AI, and MiniMax. In comparison, Indian institutions have struggled to create similar innovation clusters. In fact, India’s AI startups also received only a fraction of the private investment that Chinese companies did in 2023.

Challenges Holding India Back
Several critical factors impede India’s AI progress, with a fundamental structural challenge emerging in the nation’s approach to technological innovation. Exports note that the country remains critically fixated on application-layer innovation, predominantly relying on foreign-built AI models rather than investing in foundational research. This approach presents a significant long-term risk, potentially relegating India to a perpetual position of technological dependency.

AI breakthroughs are fundamentally rooted in sustained, strategic investment in foundational research. However, India’s current innovation ecosystem predominantly focuses on immediate, practical applications rather than developing deep technological capabilities. This short-sighted approach means the country is essentially building its technological future on infrastructural foundations constructed by China and other nations.

The existing challenges compound this fundamental research deficit:

1. Policy Hesitation: Unlike China’s strategic AI development approach, India remains cautious, primarily concerned with potential job displacement and data privacy issues. While China launched its New Generation Artificial Intelligence Development Plan in 2017, India currently does not have specific laws directly addressing generative AI, and has instead introduced a series of advisories and guidelines to encourage responsible development and implementation of AI technologies.

2. Investment Gaps: Another key challenge is the lack of adequate investments in AI in the country. While the Indian government has earmarked a total of Rs 10,000 crore for the IndiaAI Mission over the next five years. China has created a new investment fund for AI that has an initial capital of approximately $8.2 billion.

3. Language Diversity: India’s biggest superpower, its diversity of language and culture, has not yet been successfully harnessed in the AI landscape. A unique challenge in India is the scarcity of data needed to train AI in local languages, largely due to the limited presence of Indian-language content online. Developers of the tools also fail to take into account the fact that there are vast cultural differences between populations within India.

Roadmap for AI Leadership
To compete globally, India must implement a comprehensive and multifaceted strategy that addresses innovation, policy, and human capital simultaneously. The research ecosystem requires fundamental transformation through AI Centers of Excellence in top universities. These centres will drive innovation by creating robust industry-academia partnerships that translate cutting-edge theoretical research into practical technological solutions. By securing dedicated funding, these centres can attract top-tier talent and pursue groundbreaking research.

A national data strategy is critical, requiring comprehensive frameworks that prioritise ethical AI data collection and responsible data exchange. Clear regulatory guidelines will balance technological ambition with privacy and societal values, ensuring innovation happens within a structured, responsible environment.

Public sector AI adoption can be a powerful transformation mechanism. By mandating AI integration across government services, healthcare, education, and administrative processes, India can create a robust ecosystem that demonstrates AI’s practical value while providing real-world testing grounds for innovative solutions.
Workforce transformation demands a holistic skill development approach. Engineering colleges must redesign curricula to provide comprehensive AI training, while reskilling programs for existing professionals will prevent technological obsolescence. Subsidised certification courses and targeted research scholarships will democratise AI education and encourage innovation.

From an industry perspective, strategic investment is paramount. Companies must create dedicated AI innovation funds, while governments can accelerate progress through tax incentives and supportive policies for AI startup ecosystems. This approach will nurture a comprehensive technological innovation environment.
Innovation acceleration requires a multi-pronged strategy. Industries must develop sector-specific AI solutions in agriculture, healthcare, finance, and education. Cross-industry collaboration and support for open-source AI development will break down traditional silos, allowing broader participation in the national AI ecosystem.
The goal is clear: transform India from a technology service provider to a genuine AI innovation leader.

Conclusion: A Critical Moment
The AI revolution demands bold, immediate action. India’s rich technological talent pool and entrepreneurial spirit could be the catalyst for transformative AI innovation. The question is no longer whether India can compete in AI, but whether it will seize this critical moment to redefine its technological narrative.