India's ambitions to emerge as a powerhouse in artificial intelligence are facing mounting challenges as it struggles to keep pace with global leaders, particularly China and the United States. Two years after the influential launch of ChatGPT, the rapid advancements seen with China's AI model, DeepSeek, have highlighted India's lag in developing its own foundational language model, which is crucial for powering applications like chatbots.
Despite government assurances of a homegrown equivalent to DeepSeek being on the horizon, reality suggests a significant uphill battle. Authorities are allocating high-end chips to startups and research institutions to foster development over the next ten months, but structural deficiencies in education, research, and public policy remain key obstacles.
The narrative of India's potential has caught the attention of global AI figures, with OpenAI CEO Sam Altman acknowledging India's crucial role in the AI landscape. As India's second largest market for OpenAI users, the country is also attracting investments from tech giants like Microsoft, which has pledged $3 billion towards AI infrastructure. Nvidia's CEO noted India's impressive technical talent, further underlining the potential future growth of the sector.
While the groundwork appears promising with 200 startups engaged in generative AI development, concerns persist about the country's overall competitiveness on the global stage. Analysts emphasize the importance of addressing the foundational issues, as China and the US have already established a considerable head start through massive investments in research and development.
India ranks within the top five countries globally on the Stanford AI Vibrancy Index, yet it falls significantly behind the US and China in critical areas. Between 2010 and 2022, the two superpowers secured 60% and 20% of global AI patents, respectively, while India managed less than half a percent. Moreover, private investment in Indian AI startups pales in comparison to what is being funneled into their US and Chinese counterparts.
The financial constraints of India's AI mission, pegged at only $1 billion, starkly contrast with the extensive commitments from the US and China, which together reflect ambitions worth over $637 billion. Experts suggest that India's lack of long-term capital, crucial quality datasets for regional language training, and overall weak research ecosystem further exacerbate the challenge.
Despite a talent pool that comprises 15% of the world's AI workforce, a concerning trend is emerging as these skilled individuals increasingly look to migrate abroad, drawn by environments more conducive to deep research and development. The lack of systematic collaboration between government, industry, and academia, which once drove India's success in digital payments, must be replicated to foster significant advancements in AI.
India's IT industry, particularly in Bengaluru, has historically been focused on service-based work rather than foundational consumer AI technologies, creating a gap that startups have been forced to fill. The timeline set by officials for a breakthrough in foundational AI models is viewed by many as optimistic, with doubts expressed about the ability to achieve results comparable to DeepSeek in the near term.
Nevertheless, experts argue that by building upon existing open-source platforms and innovating further, India can still carve out a path forward in the AI sphere. Moving ahead, bolstering computational power, enhancing hardware capabilities such as semiconductor manufacturing, and addressing systemic issues will be critical for India to close the gap with the US and China.
