
At the AI Impact Summit in New Delhi, Prime Minister Narendra Modi unveiled what he called the M.A.N.A.V. vision for artificial intelligence — moral, accountable, national, accessible and valid. It was a speech rich in symbolism and strategic intent. India, he argued, does not fear AI; it sees opportunity. It does not seek dominance; it seeks democratization. It does not want technological colonialism; it wants sovereignty with inclusivity.
On stage were leaders such as Emmanuel Macron and Luiz Inácio Lula da Silva, alongside technology executives including Sundar Pichai and Sam Altman. The optics were deliberate. India was positioning itself as the democratic voice in an AI world increasingly defined by American corporate power and Chinese state-driven industrial strategy.
Pichai, in particular, added a layer of emotional symbolism. Recalling his student days, he said he often took the Coromandel Express from Chennai to IIT Kharagpur, passing through Visakhapatnam — then “a quiet and modest coastal city brimming with potential.” “I never imagined Visakhapatnam would become a global AI hub,” he said. Today, he announced, Google’s full-stack AI hub in that very city as part of its $15 billion investment in India — housing gigawatt-scale compute and a new international sub sea cable gateway would deliver jobs and cutting-edge AI capabilities across the country.
The message was powerful: global capital validating India’s AI rise. Yet the summit also exposed the widening gap between hype and structural reality.
India today is one of the largest AI user markets in the world. Its 1.4 billion citizens rely deeply on digital infrastructure provided by foreign platforms — primarily Google, Microsoft and Meta. It is difficult to imagine the economic and social paralysis that would follow if YouTube, Android services, cloud infrastructure or major social media platforms were suddenly withdrawn. India is among their largest markets, generating billions in advertising, subscription and data-driven revenues. Yet the core technological layers — GPUs, advanced semiconductors, frontier models — remain largely outside Indian ownership.
This dependency has prompted calls for more aggressive policy responses. One suggestion gaining quiet traction is the idea of a stronger digital tax regime. If India does not own the GPUs, the chips or the core models, the argument goes, it must at least capture a fair share of the value generated from its data and user base. A digital tax could be framed not as protectionism, but as reinvestment capital — a mechanism to fund domestic compute clusters, semiconductor initiatives and sovereign research programs.
The contrast with China is frequently invoked in this debate. Beijing did not allow American search engines and social networks to dominate its domestic market during the first wave of the internet revolution. It built domestic equivalents and protected them through regulatory firewalls. In the current AI wave, China has again pursued vertical integration — investing in rare earth supply chains, semiconductor fabrication, data centers and foundational AI research. Companies such as Unitree Robotics, whose Unitree Go2 robotic dog was controversially displayed at the summit expo under the label “Orion,” represent not merely startups but components of a broader industrial strategy.
India’s model has been different — open markets, global integration, and a focus on services and SaaS. But SaaS dominance in a pre-AI era may not guarantee relevance in a post-AI world. As generative AI begins to automate coding, workflow management and enterprise solutions, many application-layer companies face margin compression. Unlike China with ByteDance’s TikTok or the United States with YouTube, India does not possess a globally dominant consumer tech brand at comparable scale. Its strength has been backend services, not platform ownership. If AI collapses the value of application wrappers built atop foreign models, India’s current comparative advantage could narrow significantly.
Another structural vulnerability is brain drain. A disproportionate number of leading AI researchers and engineers of Indian origin work in American firms and research labs. While this diaspora influence enhances India’s soft power, it also reflects a domestic ecosystem that has not yet retained frontier talent at scale. When the core breakthroughs happen in Silicon Valley rather than Bengaluru, sovereignty becomes aspirational rather than operational.
These tensions surfaced dramatically in the controversy surrounding the summit expo. The Opposition Leader Rahul Gandhi described the event as a “disorganised PR spectacle,” accusing the government of allowing Indian data to be showcased while Chinese hardware was presented as domestic innovation. He argued that instead of leveraging India’s talent and data power, the government had reduced AI to optics, even inviting mockery from foreign media. Whether exaggerated or not, the symbolism was politically potent: in a domain framed around sovereignty, authenticity matters.
Yet dismissing the summit entirely as spectacle would also be simplistic. India does possess foundational assets that few nations can match: scale, digital public infrastructure, a vast multilingual dataset, and geopolitical positioning between the United States and China. Aadhaar-linked systems, UPI’s payments architecture and digital governance layers create a test-bed environment for AI deployment at population scale. Few democracies can integrate AI into welfare delivery, financial inclusion and public services as rapidly.
The central question, then, is not whether India is leading AI today. It clearly does not control the foundational layers at the scale of the United States or China. Nor does it have the industrial depth that Beijing built over decades through coordinated state policy. The real question is whether India can convert its demographic scale and digital footprint into long-term technological autonomy.
Modi’s MANAV framework articulates a moral and strategic ambition — sovereignty without isolation, democratization without dependency. Pichai’s Visakhapatnam announcement underscores both the promise and the paradox: global investment flowing in, yet foundational infrastructure still foreign-owned. Sovereignty in AI is measured not by summit declarations, but by ownership of compute, chips, research and platforms. If India remains reliant on American cloud infrastructure and imported GPUs, the rhetoric of independence will face credibility tests. If domestic initiatives — semiconductor manufacturing, sovereign language models, and public-private R&D collaborations — scale meaningfully, the narrative could solidify into substance.
Hype is not inherently deceptive; it is often a political tool to mobilize investment and confidence. But hype must be matched with institutional follow-through. A digital tax regime, serious capital infusion into domestic compute, retention of AI talent, and creation of globally competitive consumer platforms would signal that the ambition is structural, not symbolic.
India stands at an inflection point. It can continue as the world’s largest AI user market — influential, visible and profitable for foreign firms — or it can leverage this moment to deepen industrial capacity and strategic autonomy. The MANAV speech set the tone. The coming decade will determine whether it becomes a blueprint for sovereignty or a chapter in political theatre.



