Who Governs the Algorithm? Inside the New Delhi Declaration at AI Impact Summit 2026
- Joydeep Chakraborty
- 2 days ago
- 7 min read
The world is witnessing the birth of governance for a technology that evolves faster than laws can adapt. In such an era, prudent declarations become the buffer between ambition and anarchy.
India’s AI diplomacy signals that digital leadership is no longer confined to Silicon Valley or Beijing. That reality crystallised on 18–19 February, when the AI Impact Summit 2026 concluded in New Delhi with the adoption of the New Delhi Declaration on AI Impact. Endorsed by 89 countries and international organisations, the declaration did more than close a conference. It reframed the global conversation on who shapes artificial intelligence, and for whom.
The summit marked a decisive shift in the geography of technological influence, as for decades, the narrative around emerging technologies orbited two poles: American innovation and Chinese scale. Yet in New Delhi, a different vision took shape. The message was subtle but unmistakable: AI governance will not be written by a duopoly.
The stakes could hardly be any higher as AI is projected to contribute up to $15.7 trillion to the global economy by 2030, making it one of the largest economic transformations since industrialisation. Nations that master AI may set the terms of global competitiveness for decades ahead.
At the same time, generative AI adoption has grown faster than the internet did in the 1990s, signalling an unprecedented technological acceleration curve. We are witnessing the birth of governance for a technology that evolves faster than laws can adapt. In such an era, prudent declarations become the buffer between ambition and anarchy.
AI at a Global Crossroads
Artificial intelligence has leapt from research labs into daily life. It writes emails, diagnoses diseases, predicts climate patterns, and generates entire multimedia worlds in seconds. The pace is dizzying.
More than 50 countries have introduced or proposed AI-related regulatory frameworks in the past three years alone. Governments are racing to draft rules even as the underlying technology reinvents itself every few months.
Policymakers worry about misinformation, algorithmic bias, deepfakes, cybersecurity threats, surveillance misuse, autonomous weapons, and widespread job displacement. Trust has become the most valuable currency in the AI economy.
Without trust, adoption slows. Without adoption, innovation fragments. The summit convened against this backdrop of urgency, fragmentation, and opportunity.
But there was another uncomfortable reality in the room. Nearly 2.6 billion people globally remain offline, risking exclusion from AI-driven opportunities. Less than 10% of global AI research originates from the Global South. The digital divide is hardening into an intelligence divide.
India’s Strategic Bet: From Technology Taker to Rule Shaper
India’s decision to host the summit was not ceremonial. It was strategic.
India’s digital public infrastructure reaches over a billion people, offering one of the largest real-world testbeds for scalable AI deployment. From biometric identity systems to instant payments, the country has built population-scale digital rails that few democracies can match.
By bringing together 89 endorsing countries and institutions, India signalled its intent to move from technology adopter to rule shaper. It positioned itself as a bridge between advanced AI economies and developing nations seeking affordable, inclusive access.
During the summit’s exhibition, Prime Minister Narendra Modi personally tested new AI innovations, including AI-powered smart glasses developed by an Indian startup, generating palpable excitement among global delegates and highlighting India’s growing role as an AI innovator rather than just a consumer.
The optics mattered as they conveyed confidence. They also reinforced the idea that innovation ecosystems are expanding beyond traditional hubs.
Leaders like Emmanuel Macron publicly thanked India for hosting the summit, describing their visit as memorable and noting the high engagement of delegates across sessions and exhibitions. Such diplomatic gestures underscored the summit’s legitimacy and cross-regional resonance.
From Philosophy to Framework: “AI for All”
At the heart of the declaration lies a civilizational ethos: “Sarvajan Hitaya, Sarvajan Sukhaya”—Welfare for All, Happiness for All. It reframes AI as a public good rather than merely a commercial asset.
The declaration rests on three overarching principles:
First, democratized access to AI. Foundational models, computing power, and datasets should not be monopolised by a handful of corporations or countries. This is particularly urgent when less than 10% of AI research originates in the Global South.
Second, responsible and human-centric AI. Transparency, accountability, fairness, and explainability are treated as foundational design requirements rather than optional add-ons.
Third, AI for inclusive economic growth and sustainable development. The aim is not simply to automate profits but to amplify public services, productivity, and social mobility.
The declaration seeks to avoid two extremes, where one side risks unregulated acceleration, where innovation outruns ethics, and the other projects overregulation, where fear suffocates progress. The summit proposed a middle path of innovation with guardrails.
The Seven Pillars: Turning Vision into Architecture
The declaration organises its ambition into seven interlinked “Chakras” of action.
1. Democratizing AI Resources: Affordable access to foundational models and computing infrastructure stands at the forefront. Capacity-building partnerships aim to prevent AI capability from becoming a privilege of the wealthy.
2. Economic Growth and Social Good: AI is positioned as a driver of industrial modernisation and service delivery. From predictive healthcare to precision agriculture, practical use cases take centre stage. Several Indian startups attracted huge crowds at the summit.
For instance, one attendee noted how AI-enabled smart glasses could interpret surroundings and translate multiple languages in real time, while AI bots autonomously delivered medicines in hospital settings. These innovations moved beyond theoretical demos into real-world use cases.
3. Secure and Trusted AI: Impact assessments for high-risk systems, bias mitigation frameworks, and user protections form the backbone of this pillar. Trust is not treated as a slogan but as infrastructure.
4. AI for Science: Cross-border research collaborations aim to accelerate climate modelling, health innovation, and disaster prediction. Scientific cooperation may prove to be the least politically contentious and most impactful area of AI diplomacy.
One of the most talked-about exhibition shows at the summit was an AI demonstration involving ‘Sushruta Samhita’, a centuries-old Indian medical text. Using AI, the manuscript was digitally enhanced, made readable, converted into machine-readable text, and then interpreted by an AI avatar, which even translated it into modern languages. Here, ancient knowledge met machine intelligence to convert culture into code.
5. Access for Social Empowerment: AI deployment in education, governance, agriculture, and climate resilience is prioritised for underserved communities. With 2.6 billion people still offline, inclusion remains both a moral and strategic imperative.
6. Human Capital Development: Workforce disruption looms large. Reskilling and AI literacy programs are framed as national security priorities. Automation without preparation would widen inequality.
7. Resilient, Efficient, and Innovative Systems: Energy-efficient AI infrastructure and cybersecurity resilience are embedded in the blueprint. As AI models grow more computationally intensive, sustainability becomes non-negotiable.
Beyond Words: Concrete Platforms and “Soft Deals”
Unlike many multilateral gatherings that produce aspirational communiqués, this summit launched operational initiatives.
The Charter for the Democratic Diffusion of AI aims to foster affordable access and locally relevant ecosystems. The Global AI Impact Commons seeks to replicate successful AI use cases across countries. A Trusted AI Commons offers tools and benchmarks for secure deployment. An International Network of AI for Science Institutions formalises research collaboration.
The AI Workforce Development Playbook and Reskilling Principles provide structured guidance for labour market adaptation. Guiding Principles on Resilient and Efficient AI Systems align innovation with sustainability.
These initiatives are voluntary and non-binding. Yet they function as structured “soft deals.” In global governance, soft law often precedes hard regulation.
There was also alignment on risk-based governance and interoperability of standards. Regulatory fragmentation can stifle innovation. Interoperability can preserve sovereignty while enabling trade and collaboration.
A Summit That Felt Personal
Beyond policy papers and plenary speeches, the summit had a human pulse. The summit was a social moment for young professionals. One young attendee shared how networking at the event, connecting with peers and industry figures, felt like a turning point in his career aspirations.
This generational undercurrent mattered as AI governance is not only about ministers and CEOs. It is about students, engineers, and entrepreneurs imagining futures that did not exist five years ago.
In exhibition halls, conversations were animated as delegates leaned over prototypes, and translators switched seamlessly between languages. Smart glasses flickered to life while AI bots rolled through simulated hospital corridors.
The atmosphere was less defensive than many expected. Instead of competing narratives, there was cautious collaboration. Trust, again, was the invisible thread. In a world of geopolitical friction, the willingness of 89 nations to endorse shared principles signalled diplomatic maturity.
The Gaps That Still Demand Attention
Yet declarations do not implement themselves. Most commitments lack detailed timelines, funding models, and measurable performance indicators. Financing mechanisms for computing infrastructure and training programs remain underdeveloped.
Regulatory harmonisation is still partial because cross-border data governance, liability standards, and AI certification frameworks require deeper alignment.
Private sector accountability remains an open question. Much of AI innovation is corporate-driven; ethical commitments must translate into enforceable norms.
Monitoring and review systems were proposed, but enforcement structures need clarity. Without transparent reporting, momentum may dissipate. These gaps are not fatal flaws. They are reminders that governance is iterative.
A Blueprint in Motion
The New Delhi Declaration may be remembered as an early blueprint for cooperative AI governance in an era of technological acceleration. Its significance lies in norm-setting as it embeds inclusivity and human-centric design into the global AI lexicon.
The summit broadened AI governance beyond security anxieties. By linking AI to sustainability, public services, and social empowerment, it reframed the debate around development.
In doing so, it addressed a structural imbalance. When less than 10% of AI research originates from the Global South, global rules risk reflecting narrow interests. Broader participation recalibrates legitimacy.
A Foundation, Not a Finale
The conclusion of the AI Impact Summit 2026 represents more than a diplomatic milestone. It reflects a recognition that artificial intelligence requires shared stewardship.
AI is too powerful to be left solely to markets and too transformative to be confined within national borders. If democratised wisely, AI could become history’s most powerful equaliser. That possibility now rests on implementation.
The summit marked a decisive shift in the geography of technological influence and AI diplomacy. Whether this shift endures will depend on sustained political will, financing, and institutional follow-through.
As AI reshapes economies and societies, nations that master AI may set the terms of global competitiveness for decades. The question is no longer whether governance is necessary. It is whether it can keep pace. In New Delhi, 89 nations chose cooperation over fragmentation. In an age where algorithms evolve faster than legislation, that choice may prove decisive.