Global AI Impact Summit: India's vision for democratisation of AI

New Delhi is set to host the Global AI Impact Summit, highlighting India's vision for democratising AI. The focus is on 'AI for Humanity,' using a comprehensive AI stack to drive innovation in healthcare, education, and agriculture for all.

With New Delhi set to host the Global AI Impact Summit next week, India's vision for the future of technology is guided by a simple yet powerful idea: democratisation of AI. The Summit would bring to focus this vision of AI for Humanity, which places people at the centre of technological progress, ensuring that innovation serves society rather than the other way around.

In order to realise this vision and for it to function reliably at scale and integrate seamlessly into everyday life across healthcare, education, agriculture, finance, and public services, India's strong and integrated AI stack, brings together the tools, systems, and infrastructure needed to build, deploy, and operate AI applications effectively.

India's Five-Layered AI Stack

India's full AI Stack represents the vision of democratising technology. The five-layered pyramid represents the complete set of tools and systems for building and running AI applications, bringing together hardware, software, and platforms to collect data, train AI models, and deploy them in real-world use, ensuring AI works smoothly from start to finish.

Application Layer

Indian startups have innovatively adopted to make the user interface of AI tailored to local languages, contexts, and sector-specific needs, accelerating adoption across the economy. In agriculture, AI-powered advisory tools have reported producing gains of up to 30-50 per cent after deployment in states such as Andhra Pradesh in Maharashtra. In healthcare, AI applications are enabling early detection of tuberculosis, cancer, neurological disorders, and other conditions, strengthening preventive and diagnostic care. In education, the National Education Policy 2020 integrates AI learning through CBSE curricula, DIKSHA platforms, and initiatives such as YUVAi, equipping students with practical AI skills. In justice delivery, e-Courts Phase III deploys AI and ML for translation, case management, scheduling, and citizen-facing services, improving efficiency and transparency through vernacular access. In weather and disaster management, IMD uses AI for advanced forecasting of rainfall, cyclones, fog, lightning, and fires, with tools such as Mausam GPT supporting farmers and disaster response.

AI Model Layer

Oft known as the brain of AI, this is where models are trained on data to recognize patterns, make predictions, and take decisions. Under the IndiaAI Mission, 12 indigenous AI models are being developed to address India-specific use cases. To support sovereign model development, startups receive subsidised compute access, with up to 25% of compute costs supported through a mix of grants and equity, lowering entry barriers and accelerating domestic innovation. BharatGen is developing India-centric foundation and multimodal models, ranging from billions to trillions of parameters, to support research, startups, and public-sector applications. IndiaAIKosh serves as a national repository for datasets, models, and tools; as of December 2025, it hosts 5,722 datasets and 251 AI models, with contributions from 54 entities across 20 sectors. Indian startups are building full-stack and domain-specific AI models aligned with Indian languages, healthcare needs, and public service delivery, for example Sarvam AI is developing large language and speech models for Indian languages to support voice interfaces, document processing, and citizen services. Bhashini, under the National Language Translation Mission, hosts 350+ AI models covering speech recognition, machine translation, text-to-speech, OCR, and language detection, strengthening multilingual access to digital services.

Computer Layer

Known as the muscle of AI, it provides the computing power required to train and run AI models. This power comes from advanced processing chips such as NVIDIA's Blackwell Graphics Processing Unit (GPU), Google's Tensor Processing Units (TPUs), and Neural Processing Units (NPUs), which allow AI systems to operate efficiently and at scale. It's importance makes it critical for AI development. India has made strides in this area via ₹10,300+ crore allocated over five years for IndiaAI Mission. The IndiaAI Compute Portal works on compute-as-a-service model. It offers shared, cloud-based access to 38,000 GPUs and 1,050 TPUs at subsidised rates under Rs.100, significantly lowering entry barriers for startups and smaller organisations. A secure national GPU cluster with 3,000 next-generation GPUs is being set up for sovereign and strategic AI applications. The India Semiconductor Mission, with an outlay of ₹76,000 crore, has approved 10 semiconductor projects, including chip fabrication and packaging units. Indigenous chip design initiatives such as SHAKTI and VEGA processors are strengthening India's domestic capabilities in AI hardware. India is also developing custom AI chips and strengthening its semiconductor ecosystem, with 10 approved semiconductor projects, including fabs and ATMP units. The National Supercomputing Mission has deployed over 40 petaflops of computing capacity across IITs, IISERs, and national research institutions. Flagship systems such as PARAM Siddhi-AI and AIRAWAT provide AI-optimised supercomputing for applications including natural language processing, weather prediction, and drug discovery.

Data Centres and Network Infrastucture Layer

The home and the highway of AI- this refers to the data centres where AI systems are stored and operated. In India, nationwide optical fibre network supports high-speed data movement for cloud and AI services. 5G services have been rolled out in all States/ UTs across the country and are available in 99.9% of the districts in the country with a population coverage of 85%.

Energy Layer

This is what keeps the entire AI stack running. As AI data centres consume large amounts of electricity. Clean and affordable energy is therefore essential to support the sustainable growth of AI infrastructure. India met a record peak power demand of 242.49 GW in FY 2025-26, with national energy shortages reduced to just 0.03%, ensuring uninterrupted electricity for AI data centres, and high-performance computing facilities. Total installed power capacity reached to 509.7 GW, providing the scale required to support energy-intensive AI workloads. (As of Nov 2025). Additionally, the Sustainable Harnessing and Advancement of Nuclear Energy for Transforming India (SHANTI) Act positions nuclear power as a stable, round-the-clock source of clean energy for AI and data centres. The Act enables private sector participation and accelerates the deployment of Small Modular Reactors (SMRs) and micro-reactors.

Building a robust AI stack is both a technological priority and a social commitment for India. By strengthening every layer, including applications, AI models, compute, digital infrastructure, and energy, India is enabling the democratisation of AI and ensuring that its benefits reach citizens at population scale. Through affordable access to compute, indigenous model development, secure data infrastructure, and sustainable energy systems, India is creating an AI ecosystem that is scalable, resilient, and future-ready.

India-AI Impact Summit Details

The upcoming India-AI Impact Summit, the first-ever global AI Summit to be hosted in the Global South, from Feb 16-20, will be anchored in three guiding "sutras" of People, Planet and Progress and structured around seven key "chakras," Ministry of External Affairs (MEA) spokesperson Randhir Jaiswal said on Thursday.

The India-AI Impact Summit will be held from February 16 to 20 at Bharat Mandapam, New Delhi, marking the first global AI summit to be hosted in the 'Global South'. Designed as a five-day programme covering policy, research, industry, and public engagement, the Summit is expected to bring together global leaders, policymakers, technology companies, innovators, and experts to deliberate on AI's role in governance, innovation, and sustainable development. It aims to foster dialogue on responsible AI governance, innovation ecosystems, digital public infrastructure, climate-conscious technology and equitable access to emerging technologies. The Summit is envisioned as a pivotal global platform to shape a future-oriented agenda for inclusive, responsible, and impactful AI, and it aims to move beyond high-level discussions to deliver tangible outcomes that support economic growth, social development, and the sustainable use of AI. (ANI)

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