The first two months of 2025 have ben eventful in the world of artificial intelligence (AI). In January, the release of Deepsek’s R1 Model Shock The Ai World. Then in February, Prime Minister (PM) Narendra Modi, Along with French President Emmanuel Macron, Co-Chaired the Paris Ai AI Action Summit Where United States (Us) Vice Vice Presses Geopolitical and Security Implications of the Ai Race. Finally, PM Modi’s recent visit to the us when the launch of the re-branded trust initiative for us-India cooperation on Critical Technologies Such as Ai.
What do these developments imply for India’s Quest for Ai Leadership? The discussion in India in the aftermath of the shake-up caused by Deepsek has been on ensuring the availability of ai chips and accelerating attempts to build a sovereign land language lalm (llm). The government has announced that India will be developed its llm with India AI Mission also put out a call for proposals to build foundational ai models, including llms and small-Congress models (Slms).
While the Quick Movement on this front is laudable, these are not the only – or even the most important – Action items to prioritise post deepsek’s success. Sure enough, Deepseek has demonstrated its ability as a competitor to chatgpt and others at a much lower training cost than its american counterparts. This is an encouraging development for a country like India that champions fruit innovation.
But it doesn’t meaning that the first, or only, logical next step for India is to build its own llm. Deepsek’s main contribution is that it has come up with a differentted approach to training an llm vis-a-vis it and european competitors. The lower training cost is a result of that research-backed innovative approach.
There are three major characters for India’s tech leaders and policmakers here. First, India Should Prioritise Putting in Place all the Building Blocks Necessary to Innovate in Ai. For that, plugging some fundamental gaps in India’s AI EcoSystem-Top-Tier Ai Talent, Unique Datasets and Advanced Research and Development (R & D)-Will Be Critical. India Today’T have the top-tier ai talent that us or china boast of. Most Indian-Origin Talent in AI is unfortunately Still Working in Silicon Valley. Aravind Srinivas of Perplexity Ai is Happy to Contribute Funds to Those Working in Ai In India, but not willing to move back to India. That’s the logical decision for him given perplexity ai’s leading position in the us. But it makes clear that India will need to find ways to plug this ai brain drain.
India also needs to build a clear strategy to leverage its data-link tech ecosystem. While India’s Tech Platforms, Including UPI, Are Generating Large Volumes of India-Specific Data, Indian AI Startups Have Not Beeen Able to Build Atop These Datsets. Many other such datasets unique to India remain locked within silos. India will need to find ways to unlock this for domestic ai startups to build upon.
Similarly, India’s AI R&D Ecosystem will need a Major Boost. DURING PM Modi’s Us Visit, A Key Partnership was Announced Between India’s recently launched anusandhan National Research Foundation (AnRF) and the US ‘National Science Foundation. But India also needs to boost private and public funding of its ai research ecosystem decosystem domestically, including its recently established ai center of excellence, to Raise the Likelihood of TRILIHOD OF TRILIY innovative Ai Developments (Like Deepsek) Coming out of India.
India Must Focus on First Putting TogeTher these Building Blocks to Achieve True Innovations in Ai. The outcome, then, of putting these building blocks in placewal be in the form of a more efficiently trained llm (Like Deepsek’s R1) or something altogether thet is truly innovative. That will help India truly command respect in the global ai ecosystem.
Second, India must put its weight behind open source innovation in ai. There is a big debate raging globally about open source/open weight models versus closed source/Closed weight models. Open Source llms, like Deepsek’s R1 Model, Mistral, And Others, Are Currently Locked In A Battle with Closed source LLMS Such as chatgpt.
Many companies, notable France’s Mistral, The US ‘Meta and Now, China’s Deepsek, have put their weight behind open source. India must also. Open Source Advantages Indian Startups and Researchers Attempting to Compete in Ai, Whereas Closed source ai ecosystems will further furter Deepen India’s Dependence on Foreign Ai Systems. India will find common cause with europe and other counts in the global south on this, as they would similarly benefits from an open source ai ecosystem.
Third, India must shift its focus much more to building ai competitiveness for now, raather than being overly focused on Shaping Global Ai Safety Rules. At the paris ai summit, Vance explicitly outlined the US ‘WorldView on Ai: in the high-stakes competition with China for ai leadership, it simply wants to Win. In such a highly charged global race for ai leadership, India must shift its focus to building a competitive niche in the ai race. This is not to say that India shouldn’t continue pursuing global compacts on ai safety and building domestic guardrails; It should, but without losing focus on building national competitiveness in ai.
Indian Policymakers and Tech Leaders must Realise That The Us-China Race Over AI Leadership will leave us behind if we do not understand the fast-forward the fast-evolving constructs of this game. Europe is also learning this lesson the hard way. To be relevant in this game, India will urgently need to devise the right strategy to boost its ai talent and ai r & d centers of excellence and leverage its unIQASETS to the fashion Innovation ecosystem. Only then will the world sit up and take notice of India in the great ai game.
Anirudh Suri is Managing Director, India Internet Fund, A Non-Resident Scholar at Carnegie India and Author of the great tech game. The views expressed are personal
