Blitz Bureau
NEW DELHI: The future of technology in India is guided by a simple but powerful idea: the democratisation of artificial intelligence (AI). Latest technology should not remain limited to a few companies, institutions, or countries, emphasises the Government.
It must be developed and used in a way that benefits every citizen, supports public welfare and collective well-being. This vision of AI for humanity places people at the centre of technological progress, ensuring that innovation serves society rather than the other way around.
Realising this vision requires AI to function reliably at scale and integrate seamlessly into everyday life across healthcare, education, agriculture, finance, and public services. Such population-scale impact is made possible through a strong and integrated AI stack, which brings together the tools, systems, and infrastructure needed to build, deploy, and operate AI applications effectively.
AI stack: Layers enabling scale
An AI stack is the complete set of tools and systems that work together to build and run AI applications. These applications range from everyday tools such as virtual assistants like Siri and Alexa, and personalised recommendations on platforms like Netflix and Spotify, to advanced systems used in healthcare diagnostics, financial fraud detection, and transportation.
The AI stack brings together hardware, software, and platforms that help collect data, train AI models, and use them in real life, ensuring AI works smoothly from start to finish.
The AI stack is made up of five layers, each playing a critical role. The AI stack makes artificial intelligence work in the real world, from the apps people use every day to the data, computing power, networks, and energy that run behind the scenes. Together, these layers ensure AI solutions are scalable, reliable, and capable of delivering impact at population scale.
The application layer
The application layer represents the user-facing component of the AI stack. It includes AI-powered apps and services such as health diagnostic tools, farming advisory platforms, chatbots, and language translation applications. This layer turns complex AI processes into simple, user-friendly services that people can easily use.
Indian start-ups are developing AI applications tailored to local languages, contexts, and sector-specific needs, accelerating adoption across the economy.
In agriculture, AI-powered advisory tools are improving sowing decisions, crop yields, and input efficiency, with select state-level deployments such as Andhra Pradesh and Maharashtra, reporting productivity gains of up to 30–50 per cent.
In healthcare, AI applications are enabling early detection of tuberculosis, cancer, neurological disorders, and other conditions, strengthening preventive and diagnostic care.
In education, 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, the Indian Meteorological Department (IMD) uses AI for advanced forecasting of rainfall, cyclones, fog, lightning, and fires, with tools such as Mausam GPT supporting farmers and disaster response.
In essence, the application layer is where AI delivers real value by translating advanced capabilities into accessible, user-centric services. When deployed at scale across priority sectors, it enables AI to move beyond experimentation and become embedded in everyday decision-making and service delivery. This widespread adoption is what ultimately determines the social and economic impact of AI.
General trend in adoption
AI delivers transformative impact when applications are adopted at scale, much like the internet and mobile technologies. AI applications are increasingly deployed across sectors including agriculture, healthcare, education, manufacturing, transport, governance, and climate action.
India is pursuing an “AI diffusion” strategy, leveraging AI across sectors at population scale. Across the country, AI-enabled applications are helping farmers make informed decisions, supporting clinicians in early diagnosis, and enhancing the efficiency of public service delivery.
Further, by prioritising real-world use cases and large-scale adoption, the application layer ensures that AI delivers tangible benefits and directly improves citizens’ lives.
