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Data Brief

Mapping India’s AI Potential

Husanjot Chahal,

Sara Abdulla,

Jonathan Murdick,

and Ilya Rahkovsky

March 2021

With its massive information technology workforce, thriving research community and a growing technology ecosystem, India has a significant stake in the development of artificial intelligence globally. Drawing from a variety of original CSET datasets, the authors evaluate India’s potential for AI by examining its progress across five categories of indicators pertinent to AI development: talent, research, patents, companies and investments, and compute.

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Executive Summary

India is a vital strategic partner for the United States and a nation with considerable potential in artificial intelligence. As the Indian government moves forward with its plans to invigorate AI-based innovation and build AI-ready infrastructure, understanding the full scope of its AI capabilities—today and in the near future—becomes increasingly important. Drawing from a variety of original CSET datasets and primary source data, this paper presents an overview of India’s AI potential along five categories pertinent to the development of AI: 1) talent, 2) research, 3) patents, 4) AI companies and investments, and 5) cloud computing.

Key Takeaways:

  • Talent: Talent is a key factor for success for India. The stronger the talent pipeline, the better the research output, intellectual property (IP) creation, and the ability to attract equity investments. India produces almost twice as many master’s level engineering graduates as the United States, second only to China, yet less than one-third as many PhDs as the United States. Weaknesses in India’s higher education sector limit its ability to continue training a highly skilled AI workforce at scale, and causes Indian students to predominantly pursue PhDs in foreign countries, especially in the United States.
  • Research: India has a vast AI research community and is the fourth largest producer of AI-relevant scholarly papers since 2010. However, Indian AI researchers are less likely to collaborate with foreign authors in comparison to the other top 10 AI research-producing countries, to the detriment of the quality and impact of their research. Established AI research fields in India like speech and pattern recognition offer opportunities for Indian researchers to increase their outreach, especially with their counterparts in the United States; Indian AI researchers coauthor papers five times more frequently with U.S. researchers than any other country.
  • Patents: Patents are conceptualized as a measure of innovation. Even though the number of Indian-owned AI patents is very small in comparison to its AI research output, India ranks in the top 10 AI patent producing countries, having witnessed high growth in AI patent applications since 2012 driven by a rapid increase in AI-related inventions. The four largest categories for AI patents in India are personal devices and computing, business, telecommunications, and life sciences, which are collectively associated with more than 70 percent of India’s AI patents and indicate that Indian innovators have focused on applying AI to areas of traditional strength. India has come a long way in AI patenting in the past two decades, as its patent system has been updated and companies have started to see the benefit of using patents to protect their innovations. That said, India still has a long road ahead to catch up with China and the United States, currently the dominant sources of AI patents.
  • AI Companies and Investments: Private-market investment in India’s 361 privately-owned AI companies witnessed a steady growth between 2015 and 2018, after which it nearly tripled in dollar value. The percentage jump in India’s estimated investments in 2019 alone was higher than that of any country, including the United States and China. Among foreign investors in the Indian market, U.S. investors far outpace Chinese investors. Over half of all Indian companies applying AI to its product are active in business analytics, medicine, finance, and sales, retail and customer relations, and they attract more than 60 percent all equity funding given to Indian AI companies.
  • Cloud Computing: Since India does not have a domestic manufacturing capacity for AI chips, market cloud computing spending is a useful proxy for the country’s capacity to support its AI computing needs. India lags in cloud computing with a cloud adoption rate that ranks below the world average. But India also has one of the fastest growing cloud markets with rising demands for computing power that is expected to grow at double-digit rates. In order to make progress in this domain, a pragmatic and cost-effective path forward for India would be to build a domestic centralized AI-specific cloud infrastructure facility to facilitate the work of a broader spectrum of stakeholders in its AI ecosystem. Notably, the Indian AI strategy is moving in this direction.

Across all of these categories, the prevalence of India-U.S. interactions and widespread evidence of existing ties are hard to miss. Moving forward, any successful partnership between the two countries will rely on their ability to provide a healthy environment to educate and train future AI innovators, and provide low cost and accessible cloud infrastructure to advance innovation, while at the same time further strengthening research collaborations, IP cooperation, and investor ties.

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Mapping India’s AI Potential