E-Paper
India’s moment to re-engineer AI for human impact
This article is authored by Suman Chakraborty, director, IIT Kharagpur.
The India AI Impact Summit 2026 arrives at a rare inflection point. Artificial Intelligence (AI) has crossed the threshold from promise to pervasiveness, yet the question before us is no longer what AI can do, but for whom, at what cost, and with what accountability. By hosting the world’s first major global AI summit in the Global South, India is not merely convening a conversation, it is reframing the grammar of AI itself: from scale to significance, from benchmarks to human benefit.
Anchored in the three sutras—People, Planet, Progress—and operationalised through seven chakras spanning human capital, inclusion, safe AI, science, sustainability, and economic growth, the Summit signals a decisive shift. This is not an AI showcase driven by computational bravado alone; it is a blueprint for AI as a development instrument, designed to work under real-world constraints of data sparsity, infrastructure asymmetry, linguistic diversity, and affordability.
India’s AI journey is structurally different from that of advanced economies. Our scale is vast, our margins thin, and our diversity unparalleled. These constraints force innovation to be frugal, interpretable, multilingual, and robust. In effect, India is stress-testing AI under the toughest possible conditions. Solutions that succeed here, across rural health care, agriculture, governance, and education, are inherently global, portable to other regions of the Global South and beyond.
The Summit’s emphasis on translating global principles of responsible AI into practical, interoperable governance frameworks is particularly timely. Trustworthy AI cannot remain a theoretical construct embedded in policy documents; it must be engineered into algorithms, datasets, validation pipelines, and deployment protocols. This is where academia has a pivotal role, not as passive commentators, but as system architects of credibility.
My own work in applied AI for medical technologies sits precisely at this intersection of rigour and relevance. In resource-constrained healthcare systems, the central challenge is not accuracy alone, but deployability at scale. An AI model that performs well in a tertiary hospital but fails in a district clinic or in an extreme resource-constrained setting, due to poor imaging quality or missing metadata, is not innovation—it is exclusion.
Over the past decade, our research has focused on physics-informed and data-efficient AI models for diagnostics, systems that embed domain knowledge of physiology, fluid dynamics, and transport phenomena into learning architectures. This approach reduces dependence on massive labelled datasets and enhances interpretability, robustness, and regulatory confidence. In applications ranging from low-cost respiratory diagnostics to AI-assisted imaging and point-of-care screening tools, the goal has been consistent: Clinical-grade intelligence at population-scale affordability.
The Summit’s strong focus on AI in health care, spanning remote diagnostics, medical imaging, disease forecasting, and personalised therapies, resonates deeply with this philosophy. India’s health care AI must be judged not by leader board metrics, but by metrics of access: reduced time-to-diagnosis, lower cost per test, and measurable improvements in outcomes across underserved populations.
One of the most consequential, yet under-discussed, themes of the Summit is the Chakra of Science. AI is rapidly reshaping how discovery itself is conducted, but access to compute, data, and reproducibility remains deeply unequal. Indian academia must step forward as a neutral, trusted intermediary, curating open datasets, validating algorithms across demographics, and training a new generation fluent in both AI and ethics.
Institutions like IIT Kharagpur are already evolving into living laboratories where AI research, startups, public platforms, and policy co-design coexist. This convergence is essential. Trustworthy AI ecosystems cannot be assembled sequentially; they must be co-created, from the whiteboard to the ward, from code to community.
What distinguishes the India AI Impact Summit is its insistence on outcomes. Regional AI conferences, global impact challenges such as AI for All and AI by Her, youth initiatives like YUVAi, and the AI Compendium collectively ensure that ideas do not dissipate after plenaries—they compound into pipelines.
The deeper message is clear: India does not seek to dominate AI by owning the largest models, but by shaping the most meaningful ones. Models that are energy-aware, bias-audited, regulation-ready, and socially embedded.
As we move toward 2047, India’s AI leadership will be defined not by technological sovereignty alone, but by moral and developmental credibility. If we succeed, AI will no longer be seen as an abstract force to be regulated after the fact, but as a public-good infrastructure, engineered with intent, deployed with empathy, and governed with wisdom.
The India AI Impact Summit 2026 is thus not an event. It is a statement: that the future of AI will be written not only in lines of code, but in lives improved.
This article is authored by Suman Chakraborty, director, IIT Kharagpur.
