New Delhi, February 20, 2026 — As artificial intelligence continues to reshape economies and societies, leaders at the India AI Impact Summit 2026 delivered a clear message: the future of AI must be rooted in equity, inclusion, and public purpose.
At a high-level session titled “Building Public Interest AI: Catalytic Funding for Equitable Access to Compute Resources,” policymakers, philanthropic leaders, and global technology experts gathered to explore a critical question — not just how to expand AI infrastructure, but how to ensure it serves meaningful public-interest outcomes.
The session also marked the release of the working report “Opening Up Computational Resources for New AI Futures,” formally launched by Dr. Saurabh Garg, Secretary, Ministry of Statistics and Programme Implementation. The report examines how catalytic capital, innovative institutional models, and South–South collaboration can make advanced computing resources more accessible and affordable for emerging economies.
Beyond Infrastructure: Defining Purpose
A central theme of the discussion was that AI transformation cannot be measured solely by the number of data centers built or GPUs deployed. The more pressing issue is whether those resources are being used to solve real-world challenges in health, education, agriculture, and other critical sectors.
Speakers emphasized that expanding compute capacity without clearly defined public-interest objectives risks creating infrastructure that remains underutilized. Demand aggregation, shared digital infrastructure, mission-oriented governance, and ecosystem-wide skill development were identified as essential to translating computing power into tangible social and economic impact.
The conversation signaled a shift in thinking — from “build and they will come” to “build with purpose and deploy with accountability.”
Equity at the Core of AI’s Global Transition
Dr. Garg framed the AI revolution as a defining global moment, arguing that technological advancement must align with broader societal goals. He stressed that the true benchmark of AI progress will not be speed or scale alone, but whether its benefits are distributed fairly and inclusively.
As AI systems increasingly influence decision-making, productivity, and service delivery, ensuring equitable access to computational resources becomes fundamental. Without intentional design, disparities between high-income and developing nations could widen, limiting the Global South’s ability to fully participate in AI-driven growth.
The summit’s discussions underscored that equity is not a secondary consideration — it must shape the architecture of AI ecosystems from the outset.
Bridging the Gap Between Capacity and Impact
Another key concern raised during the session was the risk of a growing divide between infrastructure creation and real-world utilization. Building advanced computing facilities is only the first step. Ensuring that startups, researchers, public institutions, and social-sector organizations can meaningfully use those resources is the larger challenge.
Participants noted that institutional innovation is required to bridge policy, capital, and implementation. Transforming AI into a scalable service for consumers and creators is not merely a technological hurdle — it is a governance and coordination challenge. Market forces alone may not deliver inclusive access, particularly for mission-driven organizations that lack the resources to compete for high-end computing power.
In this context, catalytic funding — strategic public and philanthropic investment designed to unlock broader ecosystem participation — emerged as a critical lever.
Compute in Service of Development
Speakers repeatedly emphasized that computing power must be anchored to clearly articulated development outcomes. Access to GPUs and cloud infrastructure gains meaning only when directed toward solving concrete problems — improving agricultural productivity, strengthening public health systems, expanding educational access, or enabling local innovation ecosystems.
Clear use cases, participants argued, make governance frameworks more focused and sustainable. When compute demand is aligned with defined missions, the allocation of resources becomes more transparent, accountable, and impact-driven.
South–South cooperation was highlighted as another powerful mechanism. By sharing expertise, infrastructure models, and governance approaches across developing nations, countries can accelerate AI readiness without duplicating efforts.
Asia’s Skills Gap: The Missing Link
While infrastructure and funding dominate much of the AI conversation, summit participants identified skills as the decisive factor in unlocking AI’s full potential. Across Asia, a substantial gap exists between available computing resources and the technical capacity required to leverage them effectively.
Without targeted investments in training, workforce development, and research ecosystems, advanced compute infrastructure risks remaining underutilized. Expanding access to AI education — from foundational digital literacy to advanced machine learning capabilities — was seen as essential to building sustainable AI ecosystems.
Participants emphasized that skills development must occur alongside infrastructure expansion, not after it.
Toward AI as a Global Public Good
The session concluded with a forward-looking roadmap centered on three interconnected pillars:
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Catalytic Public and Philanthropic Capital – Strategic funding to lower barriers and stimulate inclusive participation.
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Shared and Interoperable Infrastructure – Collaborative models that reduce duplication and expand access.
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Mission-Driven Governance Frameworks – Policies that ensure AI deployment aligns with public-interest goals.
Together, these elements can help reposition AI not merely as a commercial technology, but as a global public good — one capable of advancing development, strengthening institutions, and empowering communities.
A Defining Policy Moment
The India AI Impact Summit 2026 highlighted a critical inflection point in the global AI journey. As nations race to build capacity, the deeper challenge lies in ensuring that technological power translates into equitable outcomes.
The message from New Delhi was unambiguous: scaling AI is not only about speed or innovation — it is about intention. The next phase of AI transformation will be defined not by who builds the largest systems, but by who ensures they serve the broadest public good.