will-india-miss-the-ai-bus-too

One often wonders why India always lags in technological innovations, despite being endowed with enormous human resources. The history of technological evolution is replete with instances of India consistently missing the innovation bus and later struggling with the catching-up game. 

 

The reasons for this are not far to seek: low R&D spending, limited private sector involvement, shortage of skilled researchers, poor infrastructure for research, focus on adaptation rather than creation and lack of entrepreneurial culture.

 

With such a track record of laid-back approach, are we going to miss the AI bus too?

 

When ‘DeepSeek’, a Chinese chatbot, took the technology world by storm early this year by developing an artificial intelligence assistant at a fraction of the cost of American models, the immediate question that arose was why India can’t come up with a similar product and emerge as a leading player in the AI race.

 

Challenges galore

 

Traditionally, India’s short-term approach to problem-solving has been hindering its ability to compete on a global scale. India and China had started their journey with similar per capita GDPs in the 1960s and 1970s. However, China’s rapid economic and technological advancements since the 1980s have allowed it to surge ahead, leaving India struggling to catch up. The entry of ‘DeepSeek’ is an example of what India is missing.

 

In response to it, India unveiled plans to build a domestic version of the Large Language Model (LLM). However, the road ahead is full of hurdles. The challenge for India is to not just play catch-up, but also to grab the opportunity that the production of advanced AI models at low costs presents.

 

Though India is stepping up its AI game through the ‘IndiaAI Mission’, involving an investment of Rs 10,371 crore and plans to build a scalable GPU ecosystem to support AI innovation, the key question is whether we are moving fast enough in a world where AI is advancing at a lightning speed.

 

The other question is whether the funding size and scale of ambition are sufficient, given the domination of America and China in the global AI arms race. The creation of a GPU (graphics processing units) infrastructure, a key component of ‘IndiaAI Mission’, is virtually a race against time. There are plans to acquire over 10,000 GPUs for AI research and applications. The US and China have already built vast GPU ecosystems, enabling real-time development and iteration of AI models. For India to catch up, we need not just faster deployment but also open access to this infrastructure for start-ups, researchers, and enterprises.

 

Where we stand in AI race

 

At present, the United States and China are AI superpowers, locked in a fierce race for faster development and adoption of AI.  If India is to realise its ambition of becoming a global leader in AI, it needs to plug the critical gaps in its strategy.

 

Also read: How do you stop an AI model turning Nazi?

 

According to a research paper published in the Carnegie Endowment for International Peace, the three missing pieces in India’s AI puzzle are: talent, data, and research. Unless these issues are addressed properly, the country cannot expect to stay in the global AI race.

 

The country needs to attract, nurture, and retain cutting-edge, top-tier AI research talent to ensure that AI innovations for the world emerge from India. Similarly, it must build up digital public data to provide inputs for India-specific AI models and research.

 

Despite being one of the largest smartphone, internet, and digital transactions markets in the world, India has yielded the advantage to American and Chinese firms. The vast majority of the digital data footprint of Indians is locked within platforms owned by global tech firms. The experts have suggested that India must identify ways to proliferate multilingual data as well as other India-specific datasets. This can provide a differentiating factor for Indian large language models (LLMs) and small language models (SLMs) vis-à-vis their global counterparts.

 

India must aim to become a leader in both cutting-edge AI research and the development of India-specific applications of AI. By enabling sufficient AI infrastructure through various public and private initiatives; attracting, nurturing, and retaining top-tier AI research talent; and accelerating the availability of large volumes of India-specific datasets, India can truly become a leader in cutting-edge AI research.

 

This, in turn, will cause a proliferation of applications built on top of these enabling layers of infrastructure, top-tier research talent, India-specific data, and cutting-edge AI research.

 

Need for a centralised agency

 

One of the biggest hurdles in developing a domestic AI platform is the absence of a centralised government agency overseeing AI innovation.

 

A dedicated AI agency that collaborates with private IT firms could expedite the development of an indigenous AI platform by mobilising resources and streamlining investment. Given the modest annual budget allocation for the IndiaAI Mission, pooling capital from multiple stakeholders—including the government, private sector, and academia—is crucial for timely AI innovation.

 

Also read: AI reshaping the landscape of higher education

 

If India aims to transition from being a service provider to a global AI innovator, it must overcome critical challenges in infrastructure, funding, and research. Without these course corrections, India risks being left behind in a race that will define the future of economies, geopolitics and national security.

 

AI systems require massive amounts of data. India has one of the biggest data ecosystems in the world, with its 900 million internet users generating massive amounts of data. But our AI innovations are still stuck at a nascent stage, bogged down by resource constraints and lag way behind the global leaders in scale, innovation and research.

 

India has only 33 supercomputers and none of them is dedicated to AI. As a result, it holds only 2 per cent of the global AI computing power, while the USA and China have more than a hundred supercomputers each, many dedicated to AI use. 

 

Among the fastest 500 supercomputers in the world, India has only 6, with our top-ranked machine, AIRAWAT, placed at only 136th position in terms of speed and performance. The American companies continue to release large-scale, general-purpose foundation models trained on vast amounts of data that can be adapted to a wide range of downstream tasks

 

Risk-averse approach

 

According to the 2025 AI-Index, published by Stanford University, global private venture capital funding for AI start-ups touched $132 billion in 2024, of which the USA attracted $109 billion, followed by China at $9.3 billion and the UK at $4.5 billion.

 

India stood at the 12th position with only $1.2 billion in private AI investments. In total, from 2013 to 2024, India’s cumulative private AI investment was $11.29 billion — still less than what the US invested in a single year in 2024.

 

There are two reasons for this. First, the risk-averse start-up mind-set of domestic Venture Capital funds, which prefer quick solutions and returns over original innovation, which may carry a high risk of failure but also delivers much higher long-range returns.

 

Second, the government’s unwillingness to increase R&D expenditure, which remains among the lowest in the world, at only 0.6 per cent of GDP, compared to 2.7 per cent for China and over 3.4 percent for the USA.