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In the two years since ChatGPT took the world by storm, the global AI landscape has seen significant disruptions. One of the latest players in the field is DeepSeek, a Chinese generative AI company that has made waves by lowering the cost of AI development. Despite this global shift, India, with its vast technological potential, has yet to develop its own foundational AI language model, a critical technology required for applications like chatbots, automated systems, and other generative AI technologies.

However, the Indian government insists that it is committed to creating a homegrown equivalent to DeepSeek. With a focus on accelerating AI development, the government has allocated high-end chips to startups, universities, and research institutions, with plans to deliver an indigenous AI model within the next 10 months.

India’s Growing Role in Global AI

India has garnered attention from some of the biggest names in AI, signaling that the country could play an important role in shaping the future of AI technologies. OpenAI CEO Sam Altman, who was initially skeptical of India’s capabilities, has since changed his stance. He now believes India should be a key player in AI development. OpenAI’s user base in India is now its second-largest, a clear indicator of India’s growing potential in the AI space.

Other tech giants are also investing in India’s AI ecosystem. Microsoft has committed to a significant $3 billion investment in AI and cloud infrastructure in the country. Nvidia’s CEO, Jensen Huang, has praised India’s exceptional technical talent, underscoring the country’s promising position in the AI race. With over 200 startups focused on generative AI, entrepreneurial activity in the AI sector is thriving, and India’s AI future seems increasingly bright.

Structural Challenges: What India Needs to Catch Up

Despite the positive momentum, experts warn that India still faces significant challenges in its race to catch up with the global AI giants, namely the US and China. While India ranks among the top five on Stanford’s AI Vibrancy Index—measuring factors such as patents, research, funding, and policy—the gap between India and China or the US remains vast.

Between 2010 and 2022, China secured 60% of global AI patents, while the US obtained 20%. India’s share during this period was a mere 0.5%. This gap reflects India’s struggle to secure the necessary private investment to fuel its AI development. In 2023, Indian AI startups received only a small fraction of the investment that their US and Chinese counterparts secured. India’s government-backed AI mission, valued at $1 billion, pales in comparison to the staggering $500 billion Stargate initiative in the US and China’s $137 billion AI strategy.

A key challenge lies in the lack of long-term investment from both industry and government, a gap that has left Indian AI startups to fight for resources and attention on their own. While China’s DeepSeek proved that AI models can be developed using older, cost-effective chips, India has struggled to muster the necessary investment to make this a reality. According to AI consultant Jaspreet Bindra, the reported cost of developing DeepSeek’s model was $5.6 million, but the actual financial backing was much larger, highlighting the need for substantial funding to compete effectively.

Data and Talent Barriers: India’s Lack of Resources

Another obstacle in India’s path is the scarcity of high-quality, India-specific datasets. Training AI models, especially for diverse regional languages like Hindi, Marathi, or Tamil, is a complex task due to the limited availability of structured data. While India has a vast linguistic and cultural landscape, the lack of comprehensive, standardized datasets makes it difficult to train models effectively.

Despite these challenges, India remains a significant force in the global AI workforce, producing 15% of the world’s AI talent. However, many of India’s brightest AI minds are leaving the country in search of better opportunities abroad. This brain drain is driven by the absence of robust university and corporate research and development ecosystems, factors that have allowed the US and China to establish deep-tech breakthroughs. According to Bindra, the lack of top-tier R&D infrastructure is a key reason why India has struggled to produce cutting-edge AI innovations from its academic and corporate sectors.

Drawing Parallels to India’s Digital Payment Revolution

Despite these challenges, there is hope that India’s AI development could follow the trajectory of its digital payment revolution. India’s Unified Payment Interface (UPI), a government-driven initiative, transformed digital transactions nationwide through a successful collaboration between the government, industry, and academia. This model of cooperation could be replicated in the AI space to accelerate progress.

India’s $200 billion outsourcing sector, centered in Bengaluru, has long been a major player in the global tech industry. However, most IT firms remain focused on cost-effective service work rather than building foundational AI technologies. This gap has left Indian startups to bear the brunt of the challenge, without sufficient support from established industry players. Analyst Prasanto Roy questions whether startups and government-backed initiatives can close this gap quickly enough. He suggests that the Indian government’s ambitious 10-month timeline for developing a homegrown AI model is more of a reaction to DeepSeek’s sudden rise than a strategic, long-term plan.

Many experts agree that India will likely need several more years to develop an AI model comparable to DeepSeek. The nation’s AI aspirations are likely to face delays unless there is a substantial increase in both investment and long-term commitment to building a sustainable AI ecosystem.

Leveraging Open-Source Platforms and Long-Term Independence

While India faces challenges in building its own foundational AI model, there are opportunities to leverage existing open-source AI platforms like DeepSeek to advance the country’s AI capabilities. Bhavish Aggarwal, founder of one of India’s earliest AI startups, Krutrim, recently suggested that this could be a practical approach for now, while still focusing on developing India’s own AI infrastructure for the long term.

To achieve true AI independence, however, India must eventually develop its own foundational models. This would reduce the country’s reliance on foreign technologies and minimize the risks associated with potential sanctions or foreign influence. Alongside this, expanding India’s semiconductor manufacturing capacity is crucial to support the AI infrastructure needed to power the country’s future AI models.

Until these developments are made, closing the AI gap with the US and China will remain a distant goal. However, India’s AI sector is poised to grow, and with the right investments in education, research, and policy, the country could eventually emerge as a leader in the global AI race.

For more insights into India’s AI journey and global tech trends, visit Financial Mirror.