India technology research funding
India has long held ambitions of becoming a global leader in technology, particularly in emerging fields like artificial intelligence and space technology. However, a persistent gap in funding basic research threatens to derail these ambitions.
This issue is highlighted by Amit Sheth, a renowned computer scientist, who points out that India’s focus has primarily been on late-stage technological development, skipping crucial early research stages. For India to achieve its tech superpower dreams, it must realign its funding strategies to nurture foundational research in the context of tech superpower, especially regarding research funding, especially regarding artificial intelligence. Technology Readiness Levels (TRLs) offer a framework to understand this issue.
TRLs range from 1 to 9, with 1-3 representing basic research, 4-7 applied research, and 7-9 product-ready technologies. Unfortunately, Indian funding has been concentrated on TRLs 7-9, leaving early-stage innovations unfunded, especially regarding research funding.
As a consequence, India’s presence at top AI conferences remains minimal, signaling a missed opportunity to lead in deep research and innovation (Analytics India Magazine, 2023).
Research funding innovation pipeline
The Indian government’s recent ₹1 lakh crore Research Development and Innovation (RDI) scheme highlights a critical oversight in its eligibility criteria. This initiative supports only projects that have surpassed TRL 4, thereby excluding fundamental research phases essential for breakthrough innovations.
Such policies create a narrow innovation pipeline, effectively shutting out potentially disruptive technologies. The Civil Services Daily agrees, noting that by overlooking TRL 1-3, India is closing the door on the very innovations it aims to foster (Civil Services Daily, 2023), especially regarding tech superpower, particularly in research funding, particularly in artificial intelligence. Comparatively, India’s R&D spending stands at a mere 0.64% of its GDP, lagging behind advanced economies.
This limited funding is channeled toward late-stage development rather than nurturing early-stage research, particularly in tech superpower, including research funding applications, particularly in artificial intelligence. The Technology Development Board (TDB) mirrors this trend, supporting only projects in TRLs 7-9.
Consequently, India’s innovation ecosystem lacks the diverse and foundational research necessary to produce world-class technological breakthroughs.
funding research talent shortage
Amit Sheth argues that the funding gap has led to a shortage of deep research talent in India. Unlike the United States or China, where startups can raise billions in funding, Indian startups often secure only a fraction of that amount.
This disparity limits the scale of research and development efforts in India. Sheth highlights the example of Google, whose early success was built on a foundation of PhDs and cutting-edge research in the context of tech superpower, especially regarding research funding, particularly in artificial intelligence. In contrast, India’s educational institutions, despite their expansion, still prioritize teaching over research, contributing to a talent deficit.
The lack of support for early-stage research disincentivizes talented researchers, who may seek opportunities abroad where their work receives more recognition and funding. While institutions like the Indian Institutes of Technology (IITs) and the Indian Institute of Science (IISc) have expanded, they have not yet created an ecosystem that fosters groundbreaking research and industry connections, including tech superpower applications in the context of research funding, especially regarding artificial intelligence.
This gap underscores the need for India to invest in a research culture that values both teaching and innovative exploration.
TRL funding deep tech opportunities
The neglect of TRL 1-3 funding is particularly detrimental to deep tech sectors. Data indicates that 80% of Indian deep tech deals are seed-stage, with few progressing to later stages of investment (Analytics India Magazine, 2023).
As a result, the pipeline for early-stage technologies is drying up, stifling the potential for groundbreaking innovations akin to the internet or GPS, which began as low-TRL military projects, including tech superpower applications, especially regarding research funding, especially regarding artificial intelligence. In the space technology sector, the Madhya Pradesh government has taken steps to position the state as a hub for innovation. The draft SpaceTech Policy 2025 aims to leverage space-based solutions for agriculture, water management, and urban planning.
A proposed ₹200 crore spacetech venture fund, along with incubation programs and grants, seeks to support research and startups in the context of tech superpower in the context of research funding, especially regarding artificial intelligence. The policy also envisions infrastructure projects like space manufacturing parks and testing facilities, signaling a commitment to developing the state’s capabilities in space technology (Analytics India Magazine, 2023).
Enterprise AI technology innovation
Amit Sheth advises that India should not compete directly with global giants in large language models but instead focus on enterprise AI. This involves using data, knowledge, and human expertise to address specific challenges in sectors like manufacturing, health, and semiconductors.
Sheth emphasizes the importance of Indic language AI as a public good rather than a global business, suggesting that India’s unique linguistic landscape offers opportunities for localized innovations, including tech superpower applications, especially regarding artificial intelligence. Timing may also be on India’s side. As research funding shrinks in the US, India has an opportunity to attract top talent by investing in foundational research.
Sheth notes that without adequate funding, it is impossible to train and hire PhDs capable of conducting world-class research. By addressing these funding gaps, India can position itself as a leader in technology innovation.
research funding institutions
To truly transform its research ecosystem, India can look to models like China’s “Thousand Talents” program, which provides substantial grants to returning researchers. Amit Sheth once proposed a similar idea to create a world-class research university focused solely on research, not just teaching.
While initiatives like Nalanda 2 in the context of research funding, especially regarding artificial intelligence in the context of tech superpower, especially regarding research funding in the context of artificial intelligence.0 aimed to establish such an institution in Bangalore, they have since been discontinued due to a lack of support. Without real investment in foundational research and a culture that produces world-class PhDs, India risks remaining at the level of “product tinkering” rather than creating transformative technologies. Building institutions capable of nurturing talent akin to Stanford or Berkeley is crucial for India to realize its ambitions of becoming a tech superpower.
As Sheth aptly puts it, India needs institutions that can produce the kind of talent required to build the Googles and OpenAIs of the future.
