By Vipul Prakash
The AI Impact Summit 2026 in New Delhi represents a major geopolitical and strategic shift regarding the technological landscape globally. Historically, international summits (e.g., Bletchley Park and Seoul) have focused on existential risks associated with AI and how to contain AI-Frontiers; however, the focus has now shifted from fear to action within the framework of AI.
We are no longer simply asking ourselves how we will survive AI; we are also defining how we will use AI for exponential economic growth. The “New Delhi Consensus”, a developmental deployable framework for AI that provides the foundation of a new AI-global infrastructure not dependent on a few companies, has been established.
This consensus was formally codified with the unveiling of the “MANAV” doctrine (Moral, Accountable, National sovereignty, Accessible, and Valid). By explicitly centring national sovereignty, asserting that data belongs to the nation and its people, India has signalled that machine intelligence will not be managed by a few corporations. Instead, it will be a shared global infrastructure based on the principles of People, Planet, and Progress.
$200-Billion Reality Check
This philosophical shift is backed by staggering capital. India is mobilising a $200 billion digital infrastructure push over the next 24 months. By procuring tens of thousands of GPUs and offering them to domestic innovators at a subsidised rate of approximately $0.78 (INR 65) per hour, the state is fundamentally altering the unit economics of AI.
This infrastructure wave is expanding rapidly. Google announced a $15 billion investment, including new direct subsea cables connecting India to the US and Australia to support the surging demand for AI compute. Simultaneously, three new indigenous AI models were launched at the summit, proving that the “sovereign AI” stack is moving from theory to deployment.
But what does this mean for the enterprise leader? When computing becomes heavily subsidised and widely accessible, data generation explodes. The competitive moat is no longer about who can afford to train a massive foundational model; it is about who can instantly make sense of the resulting data flood.
If your business cannot seamlessly unify fragmented data streams to extract real-time insights, cheaper compute will only lead to more noise. Furthermore, with 51% of India’s power capacity currently coming from clean energy, this next generation of infrastructure is being designed with sustainability and “Green AI” at its core. As Meta’s Chief AI Officer, Alexandr Wang, noted in his address, the future belongs to those who can master the four building blocks: talent, energy, data, and compute.
Embedded Regulation: The End Of Paper Compliance
Forget about old-school punitive or cumbersome paper-based compliance because India is establishing the world’s First “Techno-Legal” framework. Techno-Legal means regulation is built directly into the Digital Public Infrastructure (DPI). Trust, privacy, and consent are embedded directly into APIs and automated validation layers, not just written into legal contracts!
For global enterprises, this means exporting an AI model developed in the West, without local validation, is now an unacceptable go-to-market strategy. To survive and access the market, you need to work safely & securely within the framework of embedded regulations. Therefore, partnering with highly agile platforms focused on enterprise-level security, encrypted communication, and local adaptation is essential for your success in the Indian marketplace.
The Executive Playbook: Integrating With AI Commons
We must abandon the old playbook. As the “AI Commons” expands, offering shared datasets and open-source models as public goods, foundational AI capabilities will inevitably commoditise. Even OpenAI’s Sam Altman admitted that AI will “reset” the software industry, creating a sharp divide between those who cling to old value propositions and those who adapt.
The smartest leaders are not wasting capital trying to build proprietary foundational layers. Instead, they are executing three strategic shifts:
- Build on the Public Stack: Governments are providing the rails, compute, data exchanges, and open models. The winners will not recreate these; they will build the applications that run on top of them.
- Design for Complexity: The Global South is no longer just a market; it is the ultimate proving ground. If your system can navigate the fragmented, high-complexity data environments of sectors like Healthcare, Agriculture, and Logistics in India, it is battle-hardened for the rest of the world.
- Focus on Decision Intelligence: As access to models becomes universal, the differentiator is speed to insight. Value lies in the application layer, where domain expertise and decision intelligence create real differentiation.
The Infrastructure Of Intelligence
A major takeaway from the summit is that we are witnessing an important change in the advancement of AI as an essential element of modern society. The transition from AI being a novelty tool, used sparingly for limited applications, to a viable and integral part of the public sector and society as a whole has happened.
Organisations do not need yet another complicated tool that adds complexity to their day-to-day operations. Instead, they require infrastructure that simplifies overall business operations by automating manual processes and supporting decision-making processes quickly and with greater accuracy. The countries and organisations that evolve this new type of platform inclusively will dominate the growth of the global economy in the next decade. The last 10 years were defined by software as a platform; the next 10 will be determined by intelligent, secure, and scalable AI infrastructure as a platform. New Delhi has delivered the building blocks to support this evolution.
(The author is the Founder & CEO of FireAI)
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