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Introduction: India’s Rising Influence in AI
India is quietly becoming one of the world’s most influential players in artificial intelligence. Beyond the headlines about Silicon Valley or Western tech giants, it is the data contributed by countries like India that is driving the next generation of AI models. At the India AI Summit 2026, former NITI Aayog CEO Amitabh Kant underscored that India is contributing significantly more data to AI development than the United States, and that this data must translate into real benefits for the Global South. The discussion highlighted the urgent need for a framework that ensures AI is accessible, accountable, and equitable—mirroring India’s own success with Digital Public Infrastructure (DPI).
India Leads in Data Contribution to AI
Amitabh Kant revealed that India provides 33% more data than the United States to major AI platforms like OpenAI’s ChatGPT. This contribution positions the Global South not just as a passive data source, but as a central driver of AI evolution. Kant emphasized that while these large language models are increasingly sophisticated, their benefits must extend to the regions generating the data, rather than merely serving the interests of technology corporations concentrated in the West.
The Risk of Unequal AI Development
Kant warned that without robust frameworks like Digital Public Infrastructure, AI could exacerbate global inequalities. The evolution of AI must rest on three key pillars: accessibility, affordability, and accountability. Otherwise, there is a real risk of concentrating the power and benefits of AI in the hands of a few, leaving the majority of the population underserved. Drawing from the post-World War II economic growth of the West, he cautioned that progress alone does not guarantee equitable outcomes.
AI Beyond English: The Need for Multilingual Models
Highlighting disparities in AI training, Kant pointed out that models are predominantly English-centric, limiting their relevance for billions of people in the Global South. For AI to be truly inclusive, it must become natively multilingual, catering to diverse populations across languages, cultures, and economic contexts. This shift would allow AI to address grassroots challenges in education, healthcare, and agriculture more effectively.
Learning from India’s Digital Public Infrastructure
India’s DPI has transformed public services, enabling decades of development in just seven years. By creating an open, interoperable framework for identity, payments, and data exchange, the government has ensured that citizens can access services securely and at scale. Kant suggests that AI should adopt a similar approach: a base layer of digital public identity, coupled with private sector innovation, could democratize AI access while fostering competition.
Harnessing AI for Social Transformation
Kant’s vision goes beyond technology for profit. He proposed leveraging AI to drive social transformation at the grassroots level—addressing real-world problems in health, education, and agriculture. By aligning AI with the DPI blueprint, India could model a system where innovation serves society, not just corporate valuations.
Global Collaboration and Multistakeholder Dialogue
The AI Summit also highlighted the importance of multistakeholder collaboration. Kant participated alongside leaders from the UN, Sustainable Food Systems, and various think tanks. Together, they stressed the need for policies that ensure AI benefits are widely shared and that innovation aligns with sustainable development goals.
The Imperative of Equity in AI Investment
Kant’s caution is clear: unchecked AI investment risks a “highly unequal society.” Without intentional policy, the technology may widen existing disparities rather than reduce them. Ensuring equitable AI development requires proactive governance, multilingual capabilities, and a commitment to the Global South’s welfare.
What Undercode Say:
India’s role in the AI landscape is pivotal, yet underappreciated. Kant’s remarks reveal a strategic opportunity: the Global South is not merely a data supplier but can shape AI models to reflect its priorities. Currently, AI models are largely optimized for Western use cases, privileging English and high-resource environments. This misalignment risks perpetuating systemic inequalities unless countries like India actively develop indigenous AI models.
The Digital Public Infrastructure blueprint provides a proven template for how AI can be democratized. Open-source frameworks in DPI allowed India to scale identity verification, financial inclusion, and government service delivery in ways that were both secure and interoperable. Applying the same philosophy to AI could ensure that AI applications are accessible, affordable, and accountable for billions of users in low-resource settings.
Moreover, Kant’s warning about inequity underscores a broader economic concern. The West’s post-WW2 growth created wealth but also structural disparities; similarly, AI’s rapid commercialization may concentrate value among a few tech giants. Without intervention, the Global South risks remaining the data backbone while reaping minimal benefits.
Multilingual AI is not just a technical challenge; it is a social necessity. Billions of people are excluded from AI’s potential because models favor English or dominant languages. By investing in native-language datasets and training local models, India and other Southern countries can ensure AI reflects cultural and linguistic diversity, improving education, agriculture, and healthcare outcomes.
Kant’s emphasis on private sector collaboration layered atop public identity infrastructure points toward a hybrid model of innovation. Unlike closed corporate ecosystems, this approach allows competition while safeguarding public interest. The strategy could also mitigate risks of data monopolies, ensuring transparency and accountability in AI systems.
The Global South’s data contribution represents a strategic asset. If harnessed effectively, it can provide both competitive advantage and social equity. Countries like India have the capability to develop AI that serves societal needs, rather than merely commercial interests.
Yet challenges remain: regulatory frameworks are uneven, data privacy concerns persist, and AI literacy is limited. To convert data contributions into tangible benefits, the Global South must prioritize policy, infrastructure, and local model development simultaneously.
Investing in AI for societal transformation also aligns with sustainable development objectives. For example, AI-driven predictive analytics could optimize crop yields, identify health risks early, or personalize education at scale. These applications demonstrate how AI, guided by DPI principles, could accelerate development faster than conventional methods.
India’s approach could serve as a blueprint for other Southern economies. By combining open infrastructure, public-private collaboration, and multilingual capabilities, AI can move beyond profit-centric models to become a tool for inclusive growth.
Ultimately, Kant’s message is a call to action: the Global South must reclaim its role as an active participant in AI development. Doing so requires vision, investment, and governance that balances innovation with equity.
Fact Checker Results
✅ India is a major contributor of AI training data, surpassing the U.S. by 33% according to Kant.
✅ Digital Public Infrastructure (DPI) has accelerated India’s financial and service inclusion.
❌ Current large language models remain predominantly English-centric, limiting Global South accessibility.
Prediction
📊 Over the next five years, India is likely to spearhead the development of multilingual AI models tailored for the Global South. By leveraging its DPI experience, the country could create AI systems that enhance healthcare, agriculture, and education at scale. Collaboration between public frameworks and private innovators may set a global precedent for equitable AI, potentially reshaping the technology landscape beyond Western dominance.
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References:
Reported By: timesofindia.indiatimes.com
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