India needs to find its Moore’s law of growth by investing in AI innovation

India’s industrial leaders should leverage their experience from the IT services industry to drive a larger-scale push for AI innovation.

By Prayank Swaroop 

On the first day of his presidential tenure, Donald J Trump Jr, the 47th President of the United States, unveiled a staggering $500 billion plan for ‘Stargate’—a super-company designed to showcase America’s artificial intelligence (AI) strength. While bold in scope, the venture has generated immense attention and discussions about the future of AI as one of the most transformative technologies since the internet.

Soon after, China’s DeepSeek made waves by introducing its own AI model, R1, built at a mere $6 million—a fraction of what OpenAI has spent on R&D. The model’s cost-effective development is attributed to China’s government-backed research programme, which is aimed at challenging the global tech supply chain. This highlights the stark differences in AI investments globally.

India, in contrast, lags behind. The country’s AI mission is supported by just over $1 billion in government funding—significantly smaller than the investments being made by the US and China. With India projected to become the third-largest economy by the end of the decade, its rise to global leadership in AI innovation is crucial. However, India’s current investment in AI is far from sufficient to challenge established giants.

The US already leads the world in technological innovation, while China is emerging as a key player. For India to catch up, it must substantially increase investments in R&D, particularly in AI. The debate should not merely focus on India’s need to engage in AI, but rather on ramping up its efforts to assert itself in the global innovation race.

A useful model for India would be Moore’s Law, which revolutionised the global semiconductor industry. Proposed in 1965 by Intel co-founder Gordon Moore, the law predicted that the number of transistors on integrated circuits would double every two years. This idea guided the US semiconductor industry for decades, laying the foundation for companies like Intel, Nvidia, AMD, and Qualcomm. Today, over 70 percent of the global chip industry’s $588 billion revenue is generated in the US.

Moore’s Law shaped the US into a technological powerhouse and provides valuable lessons for India. India’s tech sector, including IT services and electronics, is projected to generate $850 billion in revenue by 2030—just 12 percent of the $7 trillion economy goal. While India has made progress in various fields, this figure is insufficient to transition from a consumption-driven economy to an innovation-driven one within this decade.

India’s early moves include a $1.2 billion AI Mission, focused on building central cloud computing infrastructure to lower AI research costs. The Anusandhan National Research Foundation (ANRF) is also creating a $5.8 billion corpus to fund tech research initiatives. Private companies such as Adani, Reliance, and Tata are investing in R&D, with support from large conglomerates aiming to compete with global players.

Despite these efforts, India’s AI push has been slower than that of its global counterparts. The US remains dominant due to its culture of investing in long-term research at top universities. For example, the US government allocated $201.9 billion in federal funding for R&D this fiscal year, an increase of 4 percent from the previous year. In contrast, India’s cabinet budget included $11.5 billion in interest-free loans for startups, spread across several years—less than 1/100th of the US’s R&D budget.

The US’s large-scale government funding has fostered a culture of R&D in private corporations. Alphabet, Google’s parent company, spent $12.5 billion on R&D in the September quarter alone, representing over 14 percent of its quarterly revenue. This figure exceeds India’s entire deep-tech startup fund. Tata Consultancy Services (TCS), India’s largest tech firm, spent just $320 million on R&D in FY24—less than 0.6 percent of Alphabet’s annual R&D budget.

Even India’s premier research institutions show significant disparity. The Indian Institute of Science (IISc) received just $80 million in research grants last fiscal year. In contrast, Stanford University in California allocated $1.5 billion—a difference of nearly 19 times.

Such disparities won’t be addressed overnight, but it’s crucial to begin taking the right steps. Establishing a Moore’s Law-inspired approach to research could help India set measurable targets, enabling both academic institutions and private enterprises to double their research investments annually. This would establish clear goals for developing commercial products and applications to justify the R&D spend.

One notable example of the power of R&D funding is the groundbreaking Stanford University project that led to the 2017 paper “Attention is All You Need,” funded by Google. This project gave birth to generative AI, which is now revolutionising the tech landscape. The lead author, Indian-origin Ashish Vaswani, is now the CEO of Essential AI. Vaswani’s journey was made possible by federal grants and Google’s substantial R&D investments, showing how such funding can create transformative innovations.

In India, however, fundamental research investments are not enough to fuel similar breakthroughs. This highlights the importance of Moore’s Law-inspired guidelines. India’s industrial leaders should leverage their experience from the IT services industry to drive a larger-scale push for AI innovation. India, often considered a hub for global research talent, can tap into its human capital to lead in AI.

By adopting a systematic, targets-driven approach to R&D funding, India could accelerate its progress in foundational AI research, much like China has done. This would require channeling funds effectively and establishing a structure that sets both short- and long-term goals for R&D.

India must take the recent moves by Stargate and DeepSeek as a wake-up call to create a framework that aligns with its ambitions for global economic leadership. India’s path to becoming a global AI leader will require significant and sustained investment in research, a focus on long-term goals, and collaboration between government, industry, and academia.

(Prayank Swaroop, Partner, Accel.)

Views are personal, and do not represent the stance of this publication.