Whalesbook
Focus on Deep Tech Quality
India's research output ranks third globally in volume, but it faces a key challenge: lower citation impact and global influence. This marks a shift from focusing on the volume of research papers to prioritizing quality and creating strong global intellectual property (IP). Nasscom points out that deep tech areas like quantum computing, generative AI, and semiconductor design are getting more attention because they tend to receive higher global recognition and citations.
Boosting Infrastructure and Collaboration
Moving faster requires overcoming major hurdles. Key among these are better labs and stronger links between universities and industry. The government's India AI Mission is tackling compute infrastructure shortfalls by making over 10,000 GPUs available to researchers and startups at subsidized rates, lowering a key barrier for foundational research. Platforms like AIKosh are designed to help India move from consuming AI knowledge to creating it. However, only about 22% of these GPUs are reportedly used by end-users, indicating issues with deployment and financial limits for companies.
Policy and Funding Initiatives
Policy support is growing. The Rs 1 lakh crore Research, Development, and Innovation (RDI) scheme, managed by the Anusandhan National Research Foundation (ANRF), aims to build a stronger research foundation. The ANRF is set up as a main body to fund and coordinate research across different fields. It expects to raise ₹50,000 crore over five years, with ₹14,000 crore from the Central Government and the rest from the private sector. This, along with a recent $1.1 billion state-backed venture capital fund for deep tech and manufacturing, aims to bring in capital and encourage long-term, patient investment. Yet, India's Gross Expenditure on R&D (GERD) as a percentage of GDP is still low at about 0.64%, far behind leaders like the US (3.47%), China (2.41%), and Israel (5.71%).
Challenges and Criticisms
Despite these ambitious plans, key weaknesses remain. The private sector contributes only about 36.4% to India's R&D spending, much lower than over 70% in China and the US, showing a heavy reliance on public funds. This lack of private sector involvement is a major hurdle, particularly for deep tech ventures needing large, long-term investments that often go beyond typical venture capital timelines. Moreover, the research system needs a major overhaul, including creating global-standard R&D data systems and better ways to bring scientific discoveries to market. Concerns over regulatory hurdles, duplicated efforts, and the spread of predatory journals contribute to a perception of 'quantity over quality,' questioning the real impact of India's research growth. Focusing on publication numbers for academic careers, rather than actual impact, worsens this problem and can sideline more meaningful research. For example, though India ranks third in research volume, its H-index, which measures productivity and impact, is much lower than the US.
Workforce and Future Outlook
Regarding worries about AI-driven job losses, the focus is on adapting jobs rather than reducing them. India's large tech workforce is set to shift from relying on low labor costs to leveraging expertise, boosted by increased investment in training. Over 2 million professionals have undergone AI training, creating new roles like AI product owners. The deep tech sector is seeing strong investment, with AI making up 84% of its startups and 91% of funding in 2025. Estimates project India's deep tech sector will grow at 40% annually (CAGR) through 2027, contributing $350 billion to GDP by 2030. India's talent pool, producing millions of STEM graduates yearly at a lower cost than Western nations, remains a key advantage. The strategy is to use these strengths to become a global technology and innovation leader, especially in AI, semiconductors, and quantum computing, ensuring national resilience, competitiveness, and sovereignty.