India is at a critical juncture in its technological journey, where artificial intelligence (AI) is no longer a futuristic concept but an evolving force with transformative potential. The country’s AI landscape is witnessing rapid development, underpinned by the government’s inclusive and strategic approach through initiatives like “AI for All.” These efforts are now converging with real-world challenges—most prominently in agriculture, a sector that sustains nearly half the population. By aligning digital intelligence with ground realities, India is poised to unlock the next frontier of national development.
The framework: building an inclusive AI ecosystem
The foundation of India’s AI ambitions rests on a robust policy framework and a growing ecosystem that blends state support with private innovation. The government has launched a comprehensive suite of initiatives under the “IndiaAI” umbrella. The IndiaAI Mission, IndiaAI Compute, IndiaAI FutureSkills, IndiaAI Startup Financing, IndiaAI Innovation Centre, IndiaAI Datasets Platform, and the IndiaAI Applications Development Initiative represent an all-encompassing strategy to democratise AI development and deployment. These initiatives focus not only on accelerating innovation but also on ensuring equitable access across diverse socio-economic segments, thereby making AI a tool for inclusive growth.
Complementing this public framework is the private sector’s drive toward indigenous innovation. Startups like Krutrim and Sarvam AI are leading India’s foray into large language models (LLMs). Krutrim, for instance, has developed a foundational LLM trained on a diverse corpus of Indian languages and culturally rooted datasets, enabling contextualised, accurate language generation. It recently launched “Kruti,” an AI assistant that demonstrates agentic intelligence, showcasing how AI can be tailored to India’s unique linguistic and cognitive diversity.
Sarvam AI, on the other hand, is focused on building a “full-stack” generative AI ecosystem for Bharat. Its offerings, such as the Sarvam-M model, are designed to serve India’s multilingual population and address real-life challenges through voice, text, and image-based interactions. For the first time, India is developing foundational AI models entirely on domestic infrastructure—a monumental step toward Atmanirbhar Bharat (self-reliant India). These models do not merely signify technical prowess; they also mark India’s claim to strategic autonomy in one of the century’s most consequential technological arenas.
Geopolitical and infrastructure hurdles
Despite these strides, India’s AI journey is not without hurdles. A key concern is market access to advanced semiconductors, crucial for running AI systems at scale. India currently resides in Tier-II status for chip exports, limiting its ability to procure high-end chips due to quantity caps. This is especially concerning as global demand for graphics processing units (GPUs)—the workhorses of AI—continues to outpace supply. Moreover, the cost of acquiring and maintaining GPU infrastructure remains prohibitively high for most Indian entities.
Geopolitical uncertainties, especially U.S. export controls on advanced semiconductor technology, could further complicate access. Given this context, it becomes imperative for India to explore domestic chip manufacturing capabilities and possibly establish a substantial fund of funds to support AI infrastructure investment. A long-term strategy that includes fabrication units, IP development, and robust supply chains could help India insulate itself from external shocks and maintain momentum in its AI growth trajectory.
Agriculture: The true testbed for AI in India
While AI’s potential cuts across various sectors—from healthcare and education to urban development and public safety—its most immediate and meaningful application may lie in agriculture. With 46.1% of India’s workforce engaged in agriculture and allied activities, this sector presents an unparalleled opportunity to showcase the power of AI in solving real-world problems.
Indian farmers face a complex web of challenges: climate change, shrinking landholdings, degraded natural resources, low productivity, and volatile market dynamics. These issues disproportionately affect smallholders, who form the backbone of rural India. Their marginal productivity not only undermines their own income stability but also puts national food and nutritional security at risk.
Enter AI, with its capacity to analyse vast datasets, predict outcomes, and deliver personalised recommendations. AI can be a game-changer in agriculture, helping farmers adopt precision farming, optimise inputs, and adapt to changing weather patterns. It can provide real-time crop health diagnostics, market price forecasting, pest detection, and irrigation management—all tailored to local soil, weather, and socio-economic conditions.
ITC MAARS: Pioneering “Phygital” agriculture
An exemplar of this transformative potential is ITC MAARS (Meta Market for Advanced Agricultural Rural Services)—a pioneering platform that blends physical reach with digital intelligence to empower farmers. Developed by the diversified conglomerate ITC, MAARS provides AI-powered personalised crop advisories, image-based diagnostics, input planning, and real-time access to markets. By bridging the digital divide through a “phygital” model, MAARS ensures that even farmers in remote areas can benefit from cutting-edge agricultural technologies.
The scale of this transformation is notable. Over 2 million farmers across 2,050 farmer producer organisations (FPOs) in 11 Indian states are already reaping the benefits of this initiative. The platform not only boosts productivity but also supports national missions like “More Crop, Per Drop” and the goal of doubling farmers’ incomes. It proves that AI, when appropriately integrated, can deliver scalable, sustainable, and inclusive agricultural transformation.
Language, access, and personalisation: Key to Bharat’s AI success
One of the fundamental challenges in deploying AI at scale in India is linguistic diversity. With 22 scheduled languages and hundreds of dialects spoken across the country, AI platforms must be hyper-personalised and conversational to ensure accessibility. This is where LLMs trained on Indian languages, like those from Krutrim and Sarvam AI, play a crucial role.
By enabling natural language interaction in regional tongues, these models can make farming knowledge more accessible. A farmer in rural Odisha or Assam should be able to ask questions about crop disease in their local language and receive accurate, actionable responses. This humanised AI experience is essential for adoption and impact at the grassroots level.
The broader vision: AI for public good
India’s AI revolution is not limited to agriculture. From telemedicine and e-learning platforms to smart urban planning, financial inclusion, and environmental sustainability, AI is poised to redefine governance and service delivery. Consider AI-enabled logistics networks that can reduce spoilage in food supply chains or AI-driven mobility systems that optimise traffic flows in congested cities. In each case, the goal remains the same: to make services more intelligent, more inclusive, and more effective.
This multi-sectoral vision aligns with India’s aspiration to become a global AI leader with a human-centric approach. The emphasis is not just on innovation but on ensuring that innovation serves the larger public good, especially the underserved and marginalised. This is where India’s demographic dividend—a young, tech-savvy population—can act as a multiplier. The digital generation is already plugged in, ready to harness AI tools for productivity and social mobility.
Towards an AI-enabled Bharat
The convergence of policy, innovation, infrastructure, and societal need makes this a unique moment for India. By investing in indigenous AI capabilities and ensuring inclusive deployment, the country can transition from a consumer of foreign technologies to a producer of globally relevant AI solutions. The path ahead demands a sustained commitment—one that includes public-private partnerships, infrastructure scaling, ethical governance, and international cooperation.
As a nation, India has some of the brightest minds and most vibrant entrepreneurial ecosystems in the world. The ongoing efforts in building foundational AI models, establishing self-sufficiency in compute infrastructure, and applying AI to key developmental sectors like agriculture show a clear intent to lead.
In the final reckoning, AI in India is not just about automation or algorithms—it is about aspiration. It is about giving farmers better tools to farm, students better ways to learn, doctors better diagnoses to heal, and citizens smarter governance to live with dignity. If cultivated wisely, AI will not just be a technology India adopts—it will be a force India shapes to transform Bharat.
Dipak Kurmi
Tuesday, August 26, 2025