How can India build a self-reliant, globally competitive deep-tech ecosystem? 

Against this backdrop, let’s understand how nations with well-developed innovation ecosystems enabled the integration between research, capital, and industry, and what India’s new Rs 1 lakh crore Research, Development and Innovation (RDI) scheme seeks to achieve. 

America’s Triple-Helix Model

The US is widely seen as the world’s leading R&D power because of its well-funded and market-driven innovation atmosphere. Its deep-tech ecosystem uses the ‘Triple-Helix’ model to integrate government funding, academic research, and venture capital. This model is built on two key mechanisms.

First, the Bayh-Dole Act of 1980 transferred IP ownership directly to universities and inventors. Before 1980, the US government retained ownership of patents registered from publicly funded university research. This acted as a disincentive for academics who would not be able to take their innovations to the market and gain economic benefits from their ideas, leaving thousands of inventions dormant. 

This legislation of 1980 was a major policy shift that incentivised higher education institutions to establish campus-based TTOs (Technology Transfer Offices), promote licensing of patents to private industry, and allowed faculty members to retain equity in startups that are based on their research and innovation.

Second, the Defence Advanced Research Projects Agency or DARPA model was used to de-risk breakthrough innovations. DARPA operates as a high-risk funder for research and development in the US. Rather than relying on traditional peer-review mechanisms that tend to favour incremental research, this programme funds high-risk, high-reward technologies from early lab stages to the prototype stage (TRL 1 to 6). 

By serving as the initial buyer and funding partner, which requires no equity in return, DARPA de-risks early-stage engineering and allows private venture capital to enter the picture once the commercial viability of the innovation becomes clear.

In comparison to the Triple Helix model, India’s R&D model is largely characterised by the concentration of public spending in government laboratories and elite academic institutions, while the transfer of IP or de-risking early-stage technologies for private industry participation faces constraints.

ANRF – India’s new RDI scheme

To address the private spending deficit, the Indian government has introduced a dedicated RDI corpus of Rs 1 lakh crore under the Anusandhan National Research Foundation (ANRF). Unlike most research grant programmes or short-term venture funds available for R&D in India, the RDI scheme is designed to enable long-term capital deployment that operates on three important pillars.

1. Low-cost financing: ANRF uses the 50-year interest-free corpus allocated to it by the central government to provide long-term loans to private companies, public-private consortiums and research intermediaries for research and innovation. The loans range from interest-free terms for pre-commercial research to ultra-low interest rates (2% to 4%) for subsequent stages. This extended repayment period for loans eliminates the immediate pressure of short-term debt during long technology incubation cycles.

2. Targeting TRL 4–7: While academic grants support lab-level research (TRL 1–3) to a certain extent, the RDI corpus specifically targets mid-stage commercialisation (TRL 4–7), where funding sources are limited. The scheme prioritises funding for expensive processes such as physical prototyping, pilot validation, industrial testbeds, and critical technology acquisition.

Through the bridging of this funding gap, the ANRF targets the reduction of India’s dependence on foreign technology imports and the promotion of indigenous sovereign capabilities in strategic high-tech sectors.

3. Two-tier disbursement system: While the primary corpus is part of a Special Purpose Fund (SPF) under the ANRF and DST (Department of Science and Technology), the operational deployment of the funds is delegated to SLFMs (Second Level Fund Managers) such as the TDB (Technology Development Board) and BIRAC. This decentralised system ensures domain-specific technological assessments, faster deployment of funds, and closer alignment with market demand.

RDI’s success hinges on addressing key challenges

Thus, the RDI fund seeks to provide capital for advanced research and innovation in priority deep-tech sectors like artificial intelligence, quantum technology, space science, defence, robotics, clean energy, semiconductors and digital healthcare. But its success also hinges on addressing a few key challenges.

The first challenge is the largely risk-averse nature of institutions that usually limits bold capital allocation. Deep-tech investments inherently involve technological and commercial uncertainty. However, the present governance mechanism requires comprehensive post-facto scrutiny by oversight bodies, which actively encourages risk-averse behaviour from those in charge of disbursing funds. A clear distinction between routine technical failures and financial wrongdoing might help create the risk appetite that the ANRF seeks to encourage.

The second challenge is the highly time-consuming nature of underwriting and valuation, which prevents timely capital flow. The granting of long-term debt to early-stage deep-tech ventures requires specialised domain expertise. The present institutional setup largely lacks streamlined technical appraisal committees within SLFMs, which usually causes friction and delays in funding for high-potential projects. 

The development of domain-specific valuation frameworks to assess pre-revenue technologies could help address some of the difficulties associated with administrative delays in government funding.

The third challenge is the concentration of funds in a few institutions and regions. Deep-tech innovation requires broad institutional support across the country. However, the present market landscape heavily favours established industry players, resulting in very limited capital allocation for smaller institutions and research bodies. Specific allocation safeguards to ensure that funds go to venture-backed startups, university research departments and emerging tier-2 research clusters would facilitate goals of the ANRF.

For a transformational change in innovation ecosystem 

The ANRF project, with its large 1 lakh crore RDI corpus, has the potential to bring about transformational change in India’s innovation ecosystem. Realising this potential, however, requires addressing challenges that could constrain the flow of capital to high-risk technologies.

First, the government could consider introducing provisions that protect public fund managers against post-facto scrutiny for genuine technical failures, while ensuring that audit mechanisms focus on procedural integrity rather than commercial outcomes. This may enable them to bet on high-risk, high-reward innovations.

Second, SLFMs can standardise and speed up pre-revenue technology assessment mechanisms by integrating domain-specific technical appraisal committees, which include deep-tech investors, academic specialists, and industry experts.

Third, the ANRF framework might consider mechanisms to ensure that the RDI funding is accessible to a diverse range of participants. The majority of the guaranteed funding quotas for venture-backed startups, academic startups, and Tier-2 research centres fall into the hands of large, established industrial groups.

Through the combination of institutional autonomy, long-term risk capital, and clear commercialisation incentives, India can bridge its industry-academia gap and establish a self-reliant, globally competitive deep-tech ecosystem that is essential to realise our goal of being a developed nation.

Post read questions

1. India aspires to become a developed, knowledge-driven economy. In this context, critically examine whether the country’s existing R&D ecosystem is capable of converting scientific capabilities into globally competitive technologies and enterprises.

2. The ₹1 lakh crore Research, Development and Innovation Scheme represents a shift from conventional research funding towards technology development and commercialisation. Examine its potential and the challenges to its effective implementation.

3. Compare the broad features of the US innovation ecosystem with India’s R&D ecosystem. What insights does the US experience offer?

4. The Bayh-Dole Act of 1980 transformed the relationship between publicly funded research and commercialisation in the US. Discuss with reference to India’s technology-transfer ecosystem.

5. The US–China technology competition demonstrates that technological power increasingly depends on the integration of science, capital, manufacturing and markets. What structural changes does India need to make to compete in this emerging landscape?

(Kannan K is a Doctoral candidate at the Centre for Economic and Social Studies, Hyderabad.) 

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