I first came across a visual dashboard of the innovation ecosystem in India in 2008 when I read “NASSCOM-BCGInnovation Report 2007: Unleashing the innovative power of IT-ITES industry” (NB2007)[1]. The report presented the innovation ecosystem across various regions and countries such as Singapore, Israel, Germany (Bavaria), Eureka, Taiwan, and Silicon Valley. It mentioned that the Indian innovation ecosystem was at that time “weak on multiple dimensions.” It fit my image of simple dashboards like a weighing scale that would be useful in deciding courses of action. In 2008, I mentioned the dashboard in my blog and observed that “things aren’t that gloomy and the lead indicators look good at this point.” Indian innovation ecosystem has come a long way in the last two decades. However, when it comes to deep-tech and science-based innovations, it is in its infancy. This became evident during the trade war last year. How does the innovation ecosystem dashboard in India look right now in 2026? That is what I would like to explore in this blog.
2007 India innovation ecosystem dashboard: NB2007 presented the following radar view of the innovation ecosystems of 8 countries/regions. It has five dimensions: Government (G), Industry Bodies (IB), Firms (F), Education, Research & Development (E-R&D), Investors ($). The report highlighted that the degree of participation of the different constituents and the nature and strength of their interactions give the ecosystem its vibrancy and existential support. Some ecosystems, like Cube (biotech), were overly dependent on one dimension, such as Government. In contrast, the innovation ecosystems of Eureka (consortium), Taiwan, and Silicon Valley had all players playing a significant role in their interactions. Indian innovation ecosystem was weak due to insufficient participation by the constituents and also weak or negligible interaction between them. Both Israel and Taiwan began with one dominant player – the government. But over the years, other constituents and their interactions were strengthened.
Modifying the dimensions: Startups play a unique role in fostering an innovation ecosystem. Hence, it makes sense to add it as a separate dimension rather than clubbing them with established firms. So, let’s separate Established Firms (EF) and Startups (S) as different dimensions. Incubators and accelerators play an important role in connecting startups with investors, mentors, labs, and established firms. So, let’s enhance the scope of the Industry Bodies (IB) dimension to include these intermediaries. So IB includes Industry Bodies and Incubators. Before we can redraw India’s 2007 ecosystem radar with 6 dimensions, let’s define the rating scale.
Defining the ratings: NB2007 doesn’t present what the rating scale means. If
this were to be a useful framework, it needs to elaborate on what 1 to 4 means on
each dimension.
|
Dimension |
1 - weak/isolated |
2 – emerging /
functional |
3 - strong/capable |
4 – world-class /
self-reinforcing |
|
Government (G) |
Little meaningful
support; policy/regulation may constrain innovation |
Government provides
some programs, funding, and infrastructure, but support is fragmented or
bureaucratic |
Government is a
strategic enabler through proactive policy, funding, infrastructure,
procurement and regulation |
Government plans
proactively, systematically removes
bottlenecks and coordinates the ecosystem, while allowing innovation to
emerge bottom-up |
|
Industry Bodies/ Incubators (IB) |
Actors are largely
disconnected; little matchmaking, mentoring or technology transfer |
Some associations,
incubators, accelerators and other intermediaries exist, but connections are
uneven. Incubators are weak/missing for deep-tech |
Effective facilitation
of knowledge, talent, finance and market access among government
↔ research
↔ startups ↔ investors ↔ established firms. Connections remain dense for a few regional hubs. Rest
weak. |
Dense, high-quality
connective tissue continuously creates valuable connections and substantially
lowers information/transaction costs across the ecosystem |
|
Established Firms
(EF) |
Firms mostly imitate or
resist; little technology adoption, R&D or experimentation |
Technology
adopters: firms broadly deploy
technologies developed elsewhere |
Technology
absorbers & developers:
firms systematically absorb, adapt and improve external technologies, with
meaningful proprietary R&D |
Technology
creators & platform builders:
firms repeatedly develop frontier technology and build reusable
technological/organizational platforms, influencing technological
trajectories |
|
Startups (S) |
Few startups; weak
entrepreneurial capability and experimentation |
Growing startup
population, but concentrated in a few sectors and dependent on external
technology/capital |
Strong pipeline of
startups able to experiment, develop products, attract capital and scale
across multiple sectors |
Continuous creation and
scaling of globally significant, technology-intensive companies and new
industries |
|
Educational &
Research institutes (ERI) |
Weak research base;
limited relevant talent and little industry connection |
Pockets of research
excellence, but fragmented and weakly connected to commercialization |
Strong
universities/research institutes producing relevant talent and knowledge,
with meaningful industry/startup links |
World-class research
continuously generates frontier knowledge, talent and technologies, with
exceptionally strong research → technology →
startup/firm → market conversion |
|
Investors (I) |
Very limited risk
capital; major financing gaps |
Functioning VC/angel
market, but concentrated on proven/short-cycle opportunities; deep tech
difficult to finance |
Significant specialized
capital across seed-to-growth, including patient capital for
high-risk/deep-tech innovation |
Exceptionally deep,
competitive and globally connected capital ecosystem that routinely finances
frontier technology from lab/seed through global scale |
Innovation ecosystem India, China & Silicon Valley: This is how the dashboard looks for India-2007 (original graph modified with an additional dimension), India-2026, China-2026, and Silicon Valley. For Silicon Valley, actually, the incubator/accelerator dimension got strengthened further, with a couple of dozen new accelerators established. But for our purposes, we have assumed it to be the benchmark and not changed significantly.
Assumptions behind the ratings:
India 2007 rating: Assumptions are kept the same as those presented in NB2007. All dimensions are rated 1.5 except the investors dimension, which is rated 1.
- The government had a DST budget, but there was no
focused effort in commercializing the science and technology. Most
departments operated in silos. National Innovation Mission was established
3 years later in 2010. (rating: 1.5)
- Industry bodies existed for some sectors like IT,
automotive, pharma, and consumer electronics but didn’t exist for sectors
like medical devices, robotics, and space tech. Moreover, there were very few
incubators in the country. (rating: 1.5)
- Very few startups, especially in emerging sectors
like e-commerce. MakeMyTrip, Naukri.com, Shaadi.com, a few companies
creating IP in telecom and multimedia like Ittiam, Tejas, Sasken, etc.
- There were a few established firms like Tata
Motors, Mahindra, Titan,
- Indian startups got $0.5B in venture capital in 2007. In contrast, Silicon Valley startups got $11B, and Chinese startups got $3.8B in the same year. (rating: 1)
India 2026 rating:
- Government (rating change 1.5 to 2.5): The Indian government has developed a more ambitious and sophisticated set of innovation-policy instruments since 2007. For example, India Semiconductor Mission (ISM) (launched: December 2021, ₹76,000 crore), National Quantum Mission (NQM) (launched April 2023, ₹6,000 crore), and IndiaAI Mission (March 2024, ₹10,000 crore) [2]. The government has demonstrated sustained effort in developing digital public infrastructure (DPI)[3]. However, there are still significant gaps between policy announcements, resource deployment, and technological outcomes—and limited evidence of anticipatory preparedness. All of these missions were announced after the crisis was evident or after the US and China demonstrated significant milestones. The government’s R&D expenditure has increased substantially since 2007, but as a percentage of GDP it remained roughly the same, below 1%. Most of these programs are too recent, and their actual expenditure remains significantly below the projected budget for the duration of their life so far. For example, for the Semicon India Program (SMI), expenditure in the first two years, FY23-24 and FY24-25, was 23% and 5% of the Budget estimate, respectively [4]. For IndiaAI Mission, the expenditure in FY24-25 and FY25-26 is at 3.5% and 13% respectively of the allocated budget [5].
- Startups (rating change from 1.5 to 3): In FY26, India recognized 55,200 startups as opposed to 36,400 in FY25 [6]. Some of them have scaled well in the last two decades, like Flipkart, Zerodha, and Ather Energy. However, most of them are software-heavy, asset-light, with the exception of Ather. The positive side is that many have come up before policy push was established. India’s startup ecosystem is still weak in deep-tech and manufacturing sectors. We have startups in space tech, defense, healthcare, and semiconductors, but most of them are in the early stages of the lifecycle.
- Established Firms (rating change from 1.5 to 2.5): India’s R&D expenditure itself is below 1% of GDP and within that, the contribution of established firms is around 30%. In contrast, the private sector contributes more than 60% of R&D in the US. This is also reflected in the annual reports of listed companies. Pharma companies like Dr Reddy’s, Sun Pharma (~8% of Revenue), Tata Motors (5%), Mahindra (~4%), HAL (~9%), and BEL (6%) are some of the top R&D spenders, with 20 of the 1000 listed companies accounting for 70% of the R&D expenditure [6]. That is how concentrated it is. Firms like Amara Raja Energy and Mobility (batteries) and Poly Medicure (medical devices) are making a conscious effort to move up the value chain in the last few years. But most of the established firms remain efficiency-focused.
- Investors (rating change from 1 to 2.5): India attracted $60B private-equity and venture-capital investment in 2025 across 1475 deals according to EY-IVCA report [8]. Indian deep-tech funds companies raised ~$3B in 2025 across 189 deals. Deep tech’s share of PE-VC activity increased from 4% to 15% in 2025. However, capital remains concentrated in selected sectors.
- Industry Bodies and Incubators (rating change from 1.5 to 2.5): According to the IIT Madras CREST Research 2024 [9], India has 1,100 incubators. In 2007, there were around 100 incubators. So the number of incubators has increased significantly. However, current incubator density in India is 0.8 incubators per million population compared with 8-10 in the US, UK, and China. Moreover, 45% of them are in southern India, and Tier-1 cities account for 48% of incubators. So these are geographically concentrated in a few cities. Effectiveness of the incubators, especially in establishing ecosystem connectivity i.e., connecting research institutions, startups, established firms, and investors, remains questionable. It is likely to be low for most incubators.
- Education and Research Institutes (rating change from 1.5 to 2.5): Number of researchers in Indian education and research institutes has increased from around 100 in 2000 to 350 in 2025 [10]. In contrast, China had approximately 1500 researchers per million in 2020. India has developed centres of excellence such as the IISER network, IIT Hyderabad, IIT Madras Research Park, NCBS, and Technology Innovation Hubs (TIHs). However, university-industry collaboration and translational research remain weak in India. For example, between 2021 and 2023, there were 1,839 technology transfers by 233 public R&D institutions. In contrast, there were 661,000 contracts worth $34B from 4000 universities in 2024 in China [11].
To summarize, India's innovation ecosystem has improved significantly in the last two decades. However, there are significant gaps in the government’s strategic and proactive policymaking and execution, deep-tech technology incubation and investments, R&D contribution from established firms, ecosystem connectivity from incubators/industry bodies, and translational research in education and research institutes.
AI assistance disclosure: This article was developed with assistance from OpenAI's ChatGPT, powered by the GPT-6 model family (accessed from August 12 to October 30, 2026). The author is responsible for the final content, interpretation, and conclusions.
Sources:
1. NASSCOM_BCG Innovationreport 2007
4. Union Budget 2026-27, Analysis of Expenditures by
Ministries, PRS India, March 2026
10. Research and Development statistics at a glance,
Department of Science and Technology, July 2026
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