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Prof. Abhay Karandikar, Member (S&T), NITI Aayog
The ₹1 lakh crore Research, Development, and Innovation (RDI) Fund has seen a tremendous response with the Technology Development Board committing around ₹2,000 crore, its entire allocation, to 22 selected start-ups, and the selection of Second Level Fund Managers to be completed by end of this month, Prof. Abhay Karandikar, Member(S&T), NITI Aayog, told businessline in a chat. Karandikar also spoke about the strategic rollout of the new Prime Minister Research Chair Scheme, which will offer high-value research grants to attract top-tier global scientific talent to Indian R&D labs and select higher education institutions. On sovereign AI, the technocrat said that Sarvam AI, BharatGen, and other indigenous models are all scaling, and in the next six months to one year, there will be more push and differentiation in these models, improving their adoption.
Edited excerpts:
What is the status of the deployment of the ₹1 lakh crore Research, Development and Innovation (RDI) Fund?
We are in the process of selecting the Second Level Fund Managers. The Technology Development Board (TDB) and BIRAC were already nominated as SLFMs. The TDB already issued a call for proposals and has seen an overwhelming response. It has selected 22 start-ups, and the total commitment of these 22 start-ups has been about Rs 2000 crore, which is the entire fund allocated to TDB and that is already exhausted. Now, they have asked for additional funding from the RDI Fund. We have also received about 150 applications for the selection of SLFMs, and by the end of July, I think the alternate investment funds will also be onboarded from this.
A new Prime Minister's Research Chair Scheme has been announced to attract global research talent to India. How effective do you think it will be?
It is a transformative scheme for attracting talent to India. Under this scheme, scientists from abroad can work in select higher education institutions and also national R&D labs, in certain priority areas that have been defined. These priority areas were defined keeping in mind the national priority and the fact that we need to attract global talent in those areas. It’s less about attracting people with money but more to attract key talent in priority areas. For many of the senior scientists who have had their careers in the US and have made their money, the personal salary is not important. But when they come here, they would need some research funding and grants, so that will be fulfilled by the grants offered under this scheme. The host institutions have opened applications, and once we receive the application and do the initial processing, then an Apex committee chaired by the Principal Scientific Advisor will do the final selection.
Do you think the US govt's recent actions of export controls on AI are a wake-up call to India?
As a government, I think we are promoting indigenous foundational models, large language models, and AI application development already. It is not because of any recent actions of the US; it has long been the government’s vision of developing the technology indigenously, not just in AI, but in other areas also, like in quantum and other deep tech sectors. Even the Rs 1 lakh crore RDI fund was established for this reason. Sarvam AI and BharatGen are all scaling now, and what is really needed now is their adoption across sectors. Now, in the next six months to one year, there will be a push for adopting these indigenous foundational models.
At a policy level, what can further aid adoption of indigenous models?
I don’t think it is about just telling people to use the alternative models. The models have an edge when you consider the 22 Indian languages [they support], and this gives them an edge for specific applications. For example, for applications in the agriculture sector, giving crop advisory in local languages, etc. So, these models have that differentiation, and it will lead to their diffusion in a faster way.
What more needs to be done to ensure deep tech translates to commercial businesses?
In terms of policy, we need to incentivise transnational research in our academic institutions. We also need to support taking research to commercialisation. In IITs, faculty members can spin off companies, and they can be founders of startups, but in other institutions and R&D labs, it is still not very common. Many of them still do not have IP licensing and technology transfer cells. We also need to create more prototyping and fabrication infrastructure. We have started looking at all of these and are working on them.
Published on July 3, 2026
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