When Indian farmers are asked whether they want their children to carry on the family business of farming, their overwhelming response is often negative. Despite India being an agrarian economy, agriculture has lost its allure for many families that nurture hopes of their children leaving the village to seek better employment opportunities in urban areas. But what does the future hold for agriculture if a large portion of farming families move away from it? Globally, the agriculture sector is already grappling with challenges such as climate change, water scarcity, erratic rainfall, and land degradation, which collectively put immense pressure on production. As the population grows, it will be essential to implement sustainable agricultural practices to meet the rising demand for food.
The Three Pillars of Agricultural Sustainability
Sanjay Chaudhary, Professor and Associate Dean of the School of Applied Science and Engineering at Ahmedabad University, explains that achieving true agricultural sustainability depends on balancing three key elements: environmental sustainability, economic viability, and social equity. The efforts being made individually in each area often need greater integration, leading to unintentionally harmful effects on others. For instance, though many sustainable farming techniques have been developed, the economic stability of farmers has yet to be equally prioritised, resulting in many farmers leaving agriculture. This point was reinforced by Dr Trilochan Mohapatra, Chairperson, Protection of Plant Varieties and Farmers' Rights Authority, Government of India and the former Director General, Indian Council of Agricultural Research, during a recent Conference on “ GeneRative AI for Nurturing Sustainable Agriculture (GRAINS 2024)" at Ahmedabad University. The three pillars needed for ushering in agricultural stability are delineated below.
Environmental Sustainability: Approximately 60 per cent of applied nitrogen fertiliser goes to waste, causing avoidable environmental pollution and signifying unnecessary costs. Likewise, pesticide use needs to be precisely managed to minimise its ecological impact and protect farmers' income and health. Thus, rationalising the application of fertilisers and pesticides in terms of optimal timing and quantity can significantly reduce environmental harm.
Social Equity: Rural farming communities often lack access to basic services such as healthcare, education, and electricity, unlike urban areas where these amenities are readily available. In contrast to the romanticised perception of Indian villages, the reality is often harsh, pushing farmers to the economic margins. This inequality must be addressed urgently to enable farmers to achieve better living standards and be motivated to remain in agriculture.
Economic Viability: Economic independence remains a significant challenge for farmers, who often lack the necessary support to earn a sustainable income. Initiatives like debt relief and subsidies are a start, but they do not address the systemic issues that prevent farmers from thriving financially. This is exacerbated by social inequities. Shri Ravinkumar S, from Tata Consultancy Services, echoed this point in his talk at the Conference, underscoring the need for economic stability in agriculture. To address these challenges, Ravinkumar draws attention to the need for enhancing current risk-scoring models, minimising losses, and offering more tailored insurance products in accordance with the unique transitions in agriculture. Additionally, he urged financial institutions to re-assess credit assessment models in the light of new risks, such as those arising from climate change and regenerative farming practices. These include both physical and transitional risks that affect the farmers’ financial stability.
Professor Chaudhary discussed how Generative AI help balance these elements and that solutions must maintain equilibrium across all the three pillars; prioritising one over the others will hinder sustainable progress.
Generative AI: A Solution and the Balancing Factor in Agriculture
Generative AI and related technologies have the potential to transform agriculture into a more precise, efficient, and environment-friendly sector. Tools like sensors, automation, and robotics offer remarkable possibilities for automation in agriculture. Technologies like the Internet of Things (IoT) and blockchain enable precision in farming practices, optimising resources like water, fertilisers, and pesticides. This not only reduces waste and minimises costs but also leads to a healthier environment while boosting farmers’ incomes. Addressing the students on enhancing Indian agriculture, Dr Pratik Desai, CEO of Kissan.AI, USA, highlighted that AI-driven insights support effective management of temperature, water, leaf health, air quality, and vegetation, all of which are essential for adaptation to changing climates.
Dinesh Singh from Tata Consultancy Services (TCS) Research and Innovation at the Digital Food Initiative (DFI) further explained that unlike conventional AI, Generative AI does not just analyse data but also opens up new possibilities, acting as a “creative apprentice” to the farmer. Instead of replacing experienced farmers, Generative AI assists them by posing new questions and suggesting fresh strategies. This AI can convert complex data into language that farmers can understand, making technology more accessible and valuable on the ground. One of the unique strengths of Generative AI is its ability to provide tailored solutions. For instance, a diverse landscape with varying soil compositions, moisture requirements, and sunlight exposure, can be managed more effectively using Generative AI. Further, by integrating historical weather data with current climate models, Generative AI can simulate different crop scenarios to offer farmers climate-resilient options.
Fusing Generative AI and Indigenous Knowledge Systems
Generative AI holds immense potential to enhance and complement the deep, generational knowledge of farmers. This indigenous knowledge, rooted in an understanding of the soil, climate, and local ecosystems, is invaluable in agriculture. Generative AI builds on this foundation, democratising access to local insights and global data, enabling informed decision-making in farming based on current trends and future demands.
By simulating supply-demand curves, Generative AI also helps farmers adjust their planting schedules to help align them with optimal market prices, maximising profit and reducing crop waste in the process. Furthermore, AI can support sustainability by suggesting distribution strategies to minimise carbon footprints. Generative AI can also be employed to model and predict crop yields based on variables like weather, soil, and irrigation patterns. It assists in detecting crop diseases, identifying crop types, and spotting pests, making it a powerful tool for maintaining crop health.
In Conclusion
Professor Chaudhary emphasised the need for collaborative efforts to harness the full potential of AI in agriculture. Universities, research institutions, and industry must unite to investing in agricultural research and development for advancing AI applications both on and off the agricultural field. At the grassroots level, farmers must be made aware of available technologies to benefit from accessible solutions. Effective policy support is also required to drive technology adoption. Empowering youth in agriculture and motivating them to acquire the requisite skills are particularly important as today's agriculture needs young people with technological expertise, yet few technology and engineering graduates are returning to farming.
These deliberations were part of the recently organised “GeneRative AI for Nurturing Sustainable Agriculture (GRAINS 2024)” conference organised at Ahmedabad University. It brought together experts, including technologists, researchers, academicians, government officials, and industry specialists to discuss and explore the potential role of AI in agriculture and the need for making it accessible to all.