India’s “Emerging-Economy Model” for AI Policy

Since the latter half of the 2010s, countries around the world have been moving in earnest to formulate AI policies. Many governments in developed countries place emphasis on improving corporate productivity and strengthening international competitiveness, and the governments of the U.S and China are also engaged in AI development competition, as part of their broader battle for global dominance. In contrast, a distinctive feature of the Indian government’s approach is that the aim is to use AI to address social challenges and achieve inclusive growth. The prioritization of social problem-solving is not unique to India, as other emerging and developing countries share this orientation to varying degrees. In that sense, the Indian government’s approach to AI utilization can be characterized as an “emerging-economy model.”

Recently, a view has emerged that India’s dependence on foreign countries for AI technologies and infrastructure is undesirable from an economic standpoint. There is also a growing recognition that reliance on AI models developed overseas has inherent limitations in terms of addressing India’s social challenges. Against this backdrop, momentum is building within the Indian government to pursue “self-reliance” in the AI domain, and to promote the development of indigenous AI models.

To that end, the Indian government has introduced measures such as 1) providing computing resources, 2) preparing data necessary for AI training, 3) supporting multilingual capabilities, and 4) supporting the development of foundation models. For the time being, it is focusing in particular on 3) supporting multilingual capabilities, i.e., collection and translation of material in the numerous local languages spoken across India. This is intended to address the fact that a substantial number of people, especially those living in rural areas, understand only local languages.

Underlying the Indian government’s AI policy is the concept of digital public infrastructure (DPI). DPI refers to online infrastructure designed to make it easier for the public and private sectors to provide digital services, with Aadhaar, the personal identification number system, being a representative example. In AI policy as well, the government positions the infrastructure necessary for AI development as a form of DPI, and seeks to promote AI development in both the public and private sectors by building this infrastructure itself. In parallel to this, India is also working to strengthen, with AI, the DPI it has built to date. Specifically, it is deploying new multilingual and voice support capabilities and expanding existing biometric authentication systems.

Although India’s relatively weak R&D capabilities will make it difficult in the near term to achieve self-reliance in AI development and operation, it is certainly likely that advances will continue to be made in the use of AI to address social challenges. For such initiatives, understanding India’s on-the-ground realities and responding appropriately will be more important than R&D strength. If India succeeds in generating a wide range of AI solution use cases, and if these are subsequently adopted as model examples by other emerging and developing countries, we can envision a future in which India expands its global influence in the AI field through establishing a position in the world distinct from the U.S. and China.

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