India's AI Aspirations Face Challenges in Innovation and Funding

New Delhi: India’s growing number of artificial intelligence (AI) startups are generating a lot of buzz, but the country is lagging behind the US and China in terms of innovation and groundbreaking research. This gap is evident in patent filings and foundational engineering work, which are crucial for global economic influence.

Secondary innovation, which involves technologies that cannot be patented globally, is a common issue in India’s AI sector. According to executives involved in AI-related work, spending on foundational engineering, research, and development (ER&D) in AI is minimal. This is a stark contrast to leading nations like China and the US.

Patent Filings Highlight the Disparity

In November, the World Intellectual Property Organization (WIPO) reported that India ranked sixth in overall patent applications, with 90,000 filings. This is a mere 5% of China’s 1.7 million patents. The disparity is even more pronounced in generative AI, where China filed over 38,000 patents, and the US filed around 6,500. India, with 1,350 patents, is far behind, accounting for just 3.5% of China’s advancements.

Fund Scarcity and Vision

A significant factor in this gap is the lack of large early-stage funds. US-based AI startups like Essential AI and Adept AI have raised substantial capital, allowing them to invest in foundational technologies that will be patented and licensed globally. In contrast, India’s AI startups have struggled to secure similar levels of funding.

Pranav Mistry, founder and CEO of Two.ai, noted, “There is definitely a lack of enough AI engineers working on core engineering in the field in India.” He emphasized the importance of patents for geopolitical soft power and urged India to focus on this field.

Government Support and Ecosystem Challenges

The Indian government’s AI Mission, which reduces the cost of access to processors for training AI models, is a crucial step. However, venture capital investors in India have limited appetite for deep-tech R&D, which is essential for building new foundational AI architecture.

Rohit Kumar, founding partner of The Quantum Hub, highlighted that R&D in India is not well-prioritized, with budgets being too small and institutions lacking the means to pursue fundamental innovation. Bureaucratic processes in top engineering institutes further hamper progress.

Balancing Core Innovation and Application Development

Despite these challenges, investors believe that a balance between core innovation and nifty application development is the way forward. Vishesh Rajaram, managing partner at Speciale Invest, stated, “India is a little behind the curve at the moment, but we haven’t missed the bus in AI yet.”

Prayank Swaroop, partner at Accel, emphasized the opportunity for Indian startups to create targeted solutions using existing foundational models. However, some experts argue that more focus on fundamental innovation is necessary for India to catch up.

Conclusion

India’s AI aspirations are hindered by a lack of innovation and funding, but with strategic government support and a balanced approach to core and applied AI, the country can still make significant progress in the global AI race.