India AI: As DeepSeek and ChatGPT surge, is Delhi falling behind?

China’s DeepSeek has caused ripples through the technology sector by collapsing the price for developing relational artificial intelligence uses two years after ChatGPT took the world by surprise.

However, as the global battle for AI power gains momentum, India appears to have fallen behind, especially when it comes to developing its own basic language model for things like chatbots.

A homemade version of DeepSeek, according to the state, is not far away. It provides companies, institutions, and researchers with the thousands of premium chips required to create it in less than ten months.

Recently, a burst of international AI leaders have been promoting India’s features.

After initially being unfavorable, OpenAI CEO Sam Altman this month stated that India may be playing a significant part in the AI trend. The state is then OpenAI’s next largest industry by consumers.

Others like Microsoft have put serious money on the table – committing$ 3bn ( £2.4bn ) for cloud and AI infrastructure. Nvidia’s Jensen Huang also spoke of India’s “unmatched” professional expertise as a key to unlocking its future possible.

There is enough entrepreneurial activity in the pipeline with 200 companies working on conceptual AI.

Without fundamental structural adjustments to education, research, and state coverage, India risks falling behind, according to authorities, despite having the necessary ingredients for success.

According to tech researcher Prasanto Roy, China and the US now have a “four to five time head start,” having heavily invested in research and education and developed AI for use in military applications, law police, and significant language models.

India is still far behind the two nations in some important areas, despite being in the top five globally on Stanford’s Artificial Vibrancy Index, which ranks nations based on metrics like patents, money, plan, and analysis.

China and the US were granted 60 % and 20 % of the world’s total AI patents between 2010 and 2022 respectively. India got less than half a cent.

Additionally, India’s AI companies received a small portion of the secret funding that US and Chinese firms received in 2023.

India’s state-funded AI vision, nevertheless, is worth a inconsequential$ 1bn compared with the astounding$ 500bn the US has earmarked for Stargate- a plan to build enormous AI system in the US- or China’s reported$ 137bn effort to become an AI hub by 2030.

While DeepSeek’s victory has demonstrated that Artificial models can be built on older, less costly chips- something India you get relief from- lack of “patient” or long-term capital from either industry or government is a major problem, says Jaspreet Bindra, founder of a consultancy that builds AI literacy in organisations.

” Despite what has been said, there was much more capital behind it than what was known about DeepSeek developing a model with$ 5.6 million,” the source said.

Lack of high-quality India-specific datasets required for training AI models in regional languages such as Hindi, Marathi or Tamil is another problem, especially given India’s language diversity.

But for all its issues, India punches far above its weight on talent – with 15 % of the world’s AI workers coming from the country.

The issue though, as Stanford’s AI talent migration research shows, is that more and more of them are choosing to leave the country.

According to Mr. Bindra, “foundational AI innovations typically come from deep R&D in universities and corporate research labs.”

And India lacks a supporting research environment, with few deep-tech breakthroughs emerging from its academic and corporate sectors.

The enormous success of India’s payments revolution was due to strong government-industry-academia collaboration- a similar model, he says, needs to be replicated for the AI push.

Millions of people can now transact digitally in India using the unified payment interface ( UPI), a government-developed digital payment system, with the click of a button or QR code.

Bengaluru’s$ 200bn outsourcing industry, home to millions of coders, should have ideally been at the forefront of India’s AI ambitions. However, IT companies have never really switched from developing basic consumer AI technologies to developing cheap service-based work.

” It’s a huge gap which they left to the startups to fill”, says Mr Roy.

He’s not sure whether startups and government missions can finish this work quickly enough, adding that the minster’s 10-month schedule was a knee-jerk reaction to DeepSeek’s unanticipated rise.

For the next few years at least, he continues,” I don’t believe India will be able to produce anything like DeepSeek.” It is a viewpoint that many people also hold.

India can, however, continue to build and tweak applications upon existing open source platforms like DeepSeek” to leapfrog our own AI progress”, Bhavish Agarwal, founder of one of India’s earliest AI startups Krutrim, recently wrote on X.

However, according to experts, developing a foundational model will be necessary in the long run to achieve strategic autonomy in the sector and lessen import dependencies and threats of sanctions.

India will also need to develop its hardware and computational resources to run these models, which would require the production of semiconductors, something that hasn’t yet begun.

Before the US and China’s differences are significant, much of this will need to be put in place.