NEW DELHI — India stands at a crossroads where its aspirations to become a global leader in deep-technology and artificial intelligence (AI) are colliding with persistent challenges in funding, talent retention, and execution, according to one of the country’s most influential scientists. Dr. Raghunath Anant Mashelkar, former director-general of the Council of Scientific and Industrial Research (CSIR) and a Padma Vibhushan awardee, has warned that while India’s policy frameworks are ambitious, the gap between vision and implementation threatens to undermine its strategic and economic goals.
Speaking at a recent industry forum, Mashelkar framed deep-tech and AI as not merely economic opportunities but existential imperatives for India’s sovereignty, security, and sustainable development. His remarks come as India races to position itself among the top three global deep-tech hubs by 2030 under its National Deep Tech Startup Policy (NDTSP), launched in 2024. Yet, with India’s gross expenditure on research and development (GERD) stagnating at 0.7% of GDP—far below the global average of 2.2%—the country’s ability to compete with the U.S., China, and the European Union remains in question.
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What Happened
Mashelkar’s address at the forum, hosted by the Confederation of Indian Industry (CII), outlined a roadmap for India’s technological transformation. He identified quantum computing, advanced materials, biotechnology, and semiconductors as critical sectors where India must shift from being a “follower” to a “front-runner.” His call to action was rooted in recent achievements, including India’s successful Chandrayaan-3 lunar mission, the establishment of semiconductor fabrication plants under the production-linked incentive (PLI) scheme, and the launch of the IndiaAI Mission, which aims to democratize AI tools and develop indigenous large language models.
“The next decade will belong to nations that can innovate at scale, not just consume technology,” Mashelkar stated, urging both public and private sectors to adopt a long-term vision for R&D investment. He praised the NDTSP for its incentives for startups, funding for R&D labs, and academic partnerships but cautioned that “policy is the first step. Implementation, talent development, and ecosystem collaboration are where the real battle lies.”
On AI, Mashelkar emphasized its potential to revolutionize agriculture, healthcare, and manufacturing but warned against unchecked adoption. “AI is not just about efficiency; it’s about equity. We must ensure that the benefits of AI reach every village, every farmer, every small business,” he said. He also highlighted ethical concerns, data privacy, and workforce displacement as risks that India must address to set global standards for “responsible AI.”
Geopolitically, Mashelkar framed deep-tech and AI as central to national security, noting that countries like the U.S., China, and the EU are investing heavily in these domains. “India cannot afford to be a bystander in this race. We must build our own capabilities or risk being left behind in the new world order,” he warned, calling for greater collaboration between India’s defence establishment, private sector, and academia in areas like cybersecurity, drone technology, and space-based systems.
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Why It Matters
Mashelkar’s remarks underscore a pivotal moment for India’s technological future. The country’s deep-tech and AI ambitions are not just about economic growth but about securing strategic autonomy in an era of intensifying great-power competition. With the U.S. and China locked in a technological Cold War, India’s ability to develop homegrown capabilities in semiconductors, quantum computing, and AI could determine its geopolitical leverage in the coming decades.
The stakes are particularly high for India’s defence sector. The country remains the world’s largest arms importer, with over 60% of its military hardware sourced from abroad, primarily Russia. Mashelkar’s call for indigenous solutions in cybersecurity and drone technology aligns with the government’s push for self-reliance under the “Atmanirbhar Bharat” (Self-Reliant India) initiative. However, India’s defence R&D spending, at just 0.7% of its defence budget, lags behind global peers, raising questions about its ability to reduce dependence on foreign suppliers.
Economically, deep-tech and AI could unlock new growth engines for India. The country’s digital economy is projected to reach $1 trillion by 2030, with AI alone expected to contribute $500 billion to GDP, according to a report by Nasscom and McKinsey. Yet, India’s innovation ecosystem remains fragmented. While the number of deep-tech startups has grown from 1,500 in 2020 to over 4,000 in 2026, funding remains a bottleneck. Indian deep-tech startups raised just $2.3 billion in 2025, compared to $12.5 billion in the U.S. and $9.8 billion in China, per Tracxn data.
Mashelkar’s emphasis on equity also highlights a critical tension. While AI and deep-tech could transform sectors like healthcare—where India faces a doctor-patient ratio of 1:1,500, far below the WHO-recommended 1:1,000—the benefits risk being concentrated in urban centers. Rural India, home to 65% of the population, has limited access to digital infrastructure, with only 30% of villages having reliable internet connectivity, according to the Telecom Regulatory Authority of India (TRAI).
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Background and Context
India’s push for deep-tech and AI leadership is not new but has gained urgency in recent years. The NDTSP, launched in 2024, was the first comprehensive policy to address the sector’s challenges, including funding gaps, regulatory hurdles, and talent shortages. The policy set a target of creating 10,000 deep-tech startups by 2030, with a focus on sectors like semiconductors, biotech, and quantum computing. It also introduced a $1 billion fund to support R&D and offered tax incentives for startups working on “dual-use” technologies—those with both civilian and military applications.
The policy built on earlier initiatives, such as the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS), launched in 2018, which aimed to create 25 technology innovation hubs across the country. However, progress has been uneven. While some hubs, like the one at the Indian Institute of Science (IISc) Bangalore, have made strides in robotics and AI, others have struggled with funding and bureaucratic delays.
India’s AI journey has also been marked by contradictions. The country is home to one of the world’s largest pools of AI talent, with over 400,000 professionals working in the field, per Nasscom. Yet, much of this talent is employed by multinational corporations or startups reliant on foreign platforms like Google’s TensorFlow or Nvidia’s AI chips. The IndiaAI Mission, launched in 2023, seeks to address this by developing indigenous large language models (LLMs) and AI tools tailored to Indian languages and contexts. However, as of 2026, India’s most advanced LLMs still lag behind models like OpenAI’s GPT-4 or China’s Ernie Bot in terms of performance and scalability.
The semiconductor sector offers a case study in both progress and challenges. In 2022, India launched its $10 billion Semiconductor Mission to attract chip manufacturers, and by 2026, three fabrication plants were operational, including a $2.75 billion facility in Gujarat by Tata Electronics. Yet, India’s share of global semiconductor manufacturing remains below 1%, compared to China’s 24% and Taiwan’s 60%. The country also faces a severe shortage of skilled engineers, with only 200,000 semiconductor professionals available against an estimated demand of 1 million by 2030, per a report by the India Electronics and Semiconductor Association (IESA).
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Competing Claims and Uncertainty
While Mashelkar’s vision has been widely endorsed by policymakers and industry leaders, skeptics argue that India’s deep-tech ambitions are hampered by structural weaknesses. One of the most contentious issues is funding. India’s GERD as a percentage of GDP has remained stagnant at 0.7% for over a decade, despite the government’s 2020 target of reaching 2%. In contrast, China spends 2.5% of its GDP on R&D, while the U.S. and South Korea allocate 3.5% and 4.8%, respectively.
Critics also point to India’s brain drain as a major obstacle. Over 1 million Indian students study abroad annually, with many opting to stay in countries like the U.S. and Canada due to better research opportunities and higher salaries. A 2025 report by the Indian Institute of Technology (IIT) Alumni Association found that 40% of IIT graduates leave India within five years of graduation, with deep-tech and AI being among the most common fields for emigration.
Another area of uncertainty is regulatory clarity. While the NDTSP offers incentives for deep-tech startups, the policy’s implementation has been criticized for being slow and bureaucratic. For instance, the $1 billion R&D fund promised under the policy had disbursed only $200 million by 2026, with startups citing lengthy approval processes and unclear eligibility criteria. Similarly, India’s data protection laws, which are crucial for AI development, have faced delays, with the Digital Personal Data Protection Act (DPDPA) of 2023 still lacking comprehensive guidelines for AI applications.
On the geopolitical front, India’s deep-tech ambitions are complicated by its balancing act between the U.S. and China. While India has strengthened ties with the U.S. through initiatives like the Initiative on Critical and Emerging Technology (iCET), it remains heavily dependent on China for electronics and pharmaceutical ingredients. In 2025, China accounted for 60% of India’s electronics imports and 70% of its active pharmaceutical ingredients (APIs), per government data. This dependence raises questions about India’s ability to achieve true technological sovereignty.
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What to Watch Next
1. Semiconductor Progress: India’s ability to scale its semiconductor manufacturing will be a key indicator of its deep-tech ambitions. The success of Tata Electronics’ Gujarat plant, expected to begin commercial production in late 2026, will be closely watched. If the plant meets its target of producing 50,000 wafers per month, it could attract further investment and reduce India’s reliance on imports. However, delays or cost overruns could set back the sector by years.
2. IndiaAI Mission: The development of indigenous large language models (LLMs) under the IndiaAI Mission will be critical. The first major test will come in 2027, when the government plans to launch “BharatLLM,” a multilingual AI model trained on Indian datasets. If successful, BharatLLM could reduce India’s dependence on foreign AI platforms and enable applications in local languages. However, its performance relative to global models will determine its adoption.
3. Funding and Talent: The government’s ability to address funding gaps and stem brain drain will be pivotal. In 2026, the Ministry of Science and Technology is expected to launch a $500 million fund to support deep-tech startups, with a focus on sectors like quantum computing and biotech. Meanwhile, the government’s “Stay in India” initiative, which offers tax breaks and research grants to scientists and engineers, will be tested in its ability to retain talent.
4. Regulatory Clarity: The implementation of the DPDPA and its guidelines for AI will shape India’s AI ecosystem. If the government provides clear rules on data usage, privacy, and ethical AI, it could boost investor confidence. Conversely, ambiguous or overly restrictive regulations could stifle innovation. The first draft of the AI guidelines, expected in early 2027, will be a critical milestone.
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