In debates about how the world should govern artificial intelligence, three models dominate the conversation: Europe’s precautionary rules-first approach, the United States’ light-touch innovation posture, and China’s state-alignment framework. India rarely features as a fourth. It should. Dr. Yogendra makes the case in this essay that India has not been waiting for a seat at the table. It has been building its own, through infrastructure that predates comparable efforts anywhere in the world, governance thinking calibrated to a scale no external framework was designed for, and a geopolitical ambition already reshaping how AI gets adopted across the Global South.

India’s structural complexity

India’s AI adoption journey must account for its hundreds of languages and spoken dialects, considerable socioeconomic variation, deep rural-urban divides, a wide range of sectoral use cases, uneven connectivity, and the digital divides these factors create. With the right understanding of cultural nuance, each of these differences presents a genuine opportunity for AI. Approaches designed for relatively homogeneous, highly industrialized economies such as Europe’s or the United States’ are unfit for AI adoption and governance in India’s context. India must develop its own framework and its own terms of engagement for either to be purposeful here.

India’s AI ambition

Alongside its scale and complexity, India carries an ambitious appetite for growth. As articulated through the three sutras of the recently concluded AI Impact Summit (people, planet, progress), that growth must be socially responsible and inclusive. These are the AI table stakes in India.

As one of the fastest-growing digital economies, India expects AI to touch, shape, and potentially transform finance, healthcare, agriculture, and informal labor markets. External frameworks such as Europe’s risk constraining innovation; laissez-faire models such as the United States’ may fail to protect workers and consumers adequately. India cannot slow down innovation, but it cannot leave its citizens behind either. Enabling local AI innovation also unlocks India-specific opportunities: multilingual AI development, broader accessibility, and low-cost deployment.

The strategic groundwork for this direction has been built steadily over the past several years.

India’s digital systems pioneer advantage

India’s well-developed digital public infrastructure (DPI), the “India Stack,” predates comparable efforts worldwide, making India a genuine pioneer in large-scale digital systems thinking.

The modular ecosystem is built on open standards and protocols, with layers of identity (Aadhaar), payments (UPI), paperless verification (DigiLocker), and consent. It is public infrastructure overlaid with private innovation, and it is operational, not conceptual. It already powers daily life in India across verification, payments, and data sharing.

Startups, businesses, and government departments can all build on it, sometimes in collaboration. The MahaVISTAAR app, a voice-first, text-enabled bilingual advisory platform in Marathi and English, delivers timely, crop- and location-specific guidance to farmers. It is an illustrative example of this thinking in practice.

India’s AI diffusion journey

Amul, a global exemplar and a cooperative of over 3.6 million dairy farmers, has created a digital assistant named SarlaBen to serve its members. Built using decades of organizational data and supplemented with ISRO satellite imagery, SarlaBen uses the Bhashini multilingual framework for dialectal support and provides round-the-clock guidance on cattle health and relevant government programs via app or voice call. It is a distinctly Indian story, one that shows how India’s AI journey is being shaped by its entire ecosystem of developers, innovators, and users to open new possibilities for that same ecosystem.

The contrast with other markets is instructive. In Europe, deploying an AI chatbot or foundation model requires explaining data use and implementing safeguards under the EU AI Act. In China, offerings are reviewed for security issues and must align with state policy. In the United States, the model is closer to deploy first and address problems such as biases and hallucinations afterward. India’s approach is calibrated to its own context, shaped by imagination, built on available data, and oriented toward improving lives at scale.

Geopolitical leverage

Dominant frontier model vendors including Google, Perplexity, and OpenAI have offered free access to their premium tools in India, a loss-leader strategy that signals their interest in a massive market. Their approach to dominance runs through investment in reasoning and multimodality, and through encouraging others to build on their tightly controlled proprietary platforms. This risks locking in smaller local innovators and reducing the strategic value of Indian user data, which represents a significant store of digital sovereignty.

India’s DPI, by contrast, is built on open standards and protocols. As of February 2026, UPI is live in over eight countries, and India has signed DPI cooperation agreements with 23 nations, including six in Africa, for broader adoption of the India Stack framework. The scale of ambition and the underlying philosophy could not be more different.

India is not a passive participant in the global AI conversation. Its playbook is quietly shaping international AI norms, with particular attention to the interests of nations across the Global South.

How the three models compare

Where this leads

Whether India can afford to be a rule-taker is not the operative question. India is redesigning the playing field, and it is offering the world a playbook built on a fundamentally different worldview, one that is inclusive, dynamic, and oriented toward protecting strategic and sovereign autonomy.

It is not inconceivable that the next iteration of SarlaBen is vision-enabled and multilingual. Smart glasses with reduced edge-compute costs may not even require a feature phone. Visual inspection could then bring the full depth of SarlaBen’s guidance to a farmer assessing her herd’s health in real time. The ambition that produced the India Stack is the same ambition now shaping what AI can mean for a billion people.