OPINION | AI Impact Summit 2026: India at the centre of a changing AI world

India AI Impact Summit can shape global AI governance.

As New Delhi prepares to host the India AI Impact Summit in February 2026, the global Artificial Intelligence landscape stands at a defining juncture. While AI is reshaping economies and societies worldwide, its core capabilities remain concentrated in a small set of countries with vast compute infrastructure, capital flows, and mature innovation ecosystems.

Many developing countries now face a difficult paradox: rising automation pressures from AI versus expanding employment needs due to a rapidly growing population, without the digital or computational foundations required to shape the transition on their own terms.

This is a familiar story. Both the Industrial Revolution and the Internet era saw large parts of the world adopt technologies designed elsewhere. AI, however, could be different. Its norms, governance frameworks, and market structures are still being formed. The proverbial bus has not yet left the station.

India can stand apart at this moment. Though still a developing nation, the country enters the AI era with a more advanced digital public infrastructure than that of many developed countries, rapidly expanding digital capacity, and a policy approach that links technological progress to inclusion at scale. This ambition is backed by a credible record of delivery.

Globally, however, geopolitical tensions, rather than present needs, are shaping the contours of AI governance. Divergent approaches between the United States and China are pressuring countries to align with one bloc or the other. Europe’s ambitious regulatory frameworks are also influencing international supply chains. For the developing world, this environment risks reinforcing a new digital divide - one in which many countries become consumers, rather than co-creators of the systems that will determine their future.

India’s Approach

Against this backdrop, India offers a third way. The launch of the IndiaAI Mission in 2024 marked a decisive break from earlier technological cycles. Decision-makers committed early to building the institutional, computational, and policy foundations needed to shape the evolution of AI in real time, rather than merely adapting to it. Through public-private partnerships, national AI compute capacity has expanded rapidly, complemented by a discounted compute marketplace that lowers costs for startups, researchers, and public institutions. In parallel, the mission has supported indigenous foundation models, including multilingual and domain-specific systems for agriculture, health, education, justice, and financial inclusion.

Platforms such as AIKosh are enabling trusted cross-sectoral datasets, while Bhashini has enabled real-time translation and speech technologies across more than twenty Indian languages. Their integration into citizen-facing information and grievance redressal platforms demonstrates how AI can advance inclusion in a diverse society.

These experiences position India to advance an idea globally: that the benchmark for AI leadership is shifting. If recent years focused on who could build the most advanced models, the next phase is increasingly about who can convert AI capability into real-world impact - through trust, jobs, and measurable outcomes. India’s digital public infrastructure demonstrated that technology could scale inclusion; the same systems-thinking is now being extended to AI.

Bridging Global AI Governance

The India AI Impact Summit offers an opportunity to carry this momentum into the global arena by helping shape a governance approach that both guards against harm and bridges global divides.

Many countries, particularly those balancing innovation with limited regulatory capacity, are seeking practical frameworks that ensure accountability without stifling growth. A credible convergence would have to rest on these two pillars.

First, a shared management-system standard for AI governance: a certifiable, auditable framework that enables organisations to document, monitor, and continuously improve how AI systems are designed, deployed, and overseen. Such a standard would be valuable for public procurement, safety-critical applications, and international supply chains, creating a common baseline without forcing countries into the orbit of any single regulatory regime. To ensure it serves all countries and stakeholders equitably, it must be anchored in transparent, participatory processes, thereby preventing compliance pathways from becoming tied to a narrow set of proprietary tools, platforms, or commercial certifiers.

Second, a common risk management vocabulary and toolkit for AI, including generative systems that provide concrete, practical methods for identifying, assessing, and mitigating AI-related harms. This would provide policymakers, developers, and auditors with a consistent grammar for discussing safety thresholds, transparency requirements, evaluation procedures, and post‑deployment monitoring.

Together, these two elements could offer the global AI ecosystem the bridge it desperately lacks: a coherent operational architecture.

Guarding Against Predatory AI Practices

Yet governance cannot stop at standards alone and must also be a guard. As AI systems proliferate, predatory practices are becoming increasingly visible. Firms are offering free or heavily subsidised tools to rapidly gain market share, only to raise prices or tighten data controls, once dependence sets in.

At the same time, rising concerns about copyright, IP protection, safety, inclusion, and ethical compliance have led major proprietary platforms to require AI‑related compliance certifications before accepting types of AI‑generated content. While an unavoidable initial step, these certifications are often issued by a small number of vendors that also help shape these standards. This emerging model is not only a conflict of interest but also an exclusionary barrier, limiting participation by smaller firms, creators, and actors from the Global South.

For developing countries, the result can be a new form of digital dependency that undermines innovation, bargaining power, and strategic autonomy. Norm-setting, therefore, cannot become a gated domain. It must remain open, interoperable, and non-exclusionary by design.

The Summit is well placed to initiate a conversation on fair competition, transparent pricing, safeguards against lock-in, and open verification models. Countries should not be forced to choose between affordability today and autonomy tomorrow.

A Moment to Reimagine the Future

Global AI governance remains fluid. This uncertainty carries risks, but it also creates space for constructive leadership and a broader reimagining of how the world approaches AI. India can use this moment to advance a vision in which AI infrastructure is treated as a public good, safety is grounded in shared interoperable standards, and the Global South participates as a co-architect of the AI future.

India cannot shoulder this responsibility alone. But it is uniquely positioned to convene, bridge, and lead by example, showing that AI can be built not just for scale but for lasting societal impact. The world is watching, and India now has an opportunity.

(Chetan Aggarwal is a Public Policy professional and graduate from the Harvard Kennedy School.)

Views are personal, and do not represent the stand of this publication.