Essay: AI in Agriculture: Opportunities, Challenges, and the Way Forward
Artificial Intelligence (AI) cannot replace farmers; however, farmers who adopt AI are likely to replace those who do not. This statement captures the transformative potential of AI in Indian agriculture. According to the Economic Survey, agriculture contributes nearly 16% to India’s GDP and supports more than 46% of the population. Despite its critical importance, the agricultural sector continues to face persistent challenges such as labour shortages, erratic climatic conditions, pest and disease attacks, and low productivity. In this context, the adoption of Artificial Intelligence (AI) has emerged as a powerful tool to enhance productivity and move towards the goal of doubling farmers’ income.
AI-driven precision agriculture enables data-based decision-making by analysing information obtained from satellites, sensors, and weather stations. This data helps farmers optimise the use of inputs such as water, fertilisers, and pesticides, thereby improving efficiency. For instance, Microsoft’s Project Farm Vibes demonstrated that AI tools can increase crop productivity by 20–30%, conserve water by nearly 40%, and enhance farmers’ profit margins by 30–45%. Similarly, the Indian Council of Agricultural Research (ICAR) has developed automated irrigation systems that supply water only when required, significantly reducing water wastage. AI-based platforms such as the Plantix app and the National Pest Surveillance System help detect pest and disease outbreaks at an early stage and recommend timely control measures. The use of drones for pesticide spraying, monitoring soil moisture, and tracking market prices further illustrates how AI is transforming Indian agriculture.
Despite its immense potential, AI adoption in agriculture faces several constraints. The foremost challenge is the high initial cost of AI-based tools, which makes them unaffordable for small and marginal farmers, who constitute nearly 86% of India’s farming community. Moreover, operating AI systems requires technical skills, yet rural India faces an acute shortage of trained personnel. Inadequate internet connectivity and unreliable power supply further limit the effective deployment of AI technologies in rural areas.
To address these challenges, a multi-pronged approach is required. Through cooperative and contract farming, farmers can pool resources and collectively invest in AI tools such as drones. Institutions like Krishi Vigyan Kendras (KVKs) and the Agricultural Technology Management Agency (ATMA) can play a crucial role in capacity building and training farmers to operate AI-based technologies. Access to affordable credit and subsidies is also essential. For example, the government provides a capital subsidy of up to ₹7.5 lakh or 75% for drone purchases through Custom Hiring Centres, while under the Namo Drone Didi Scheme, women SHGs are offered 80% subsidy or ₹8 lakh for drone adoption.
Globally, initiatives such as the WEF’s AI4AI programme, implemented in collaboration with the Telangana government through the “Sagu Bagu” initiative, have demonstrated tangible benefits. Under this programme, chilli crop productivity increased by 8%, while farmers’ profits rose by 21% compared to traditional practices.
In conclusion, the AI market in agriculture is expected to grow from 13% in 2023 to 30% by 2028, with a CAGR of 18%, highlighting its transformative potential. However, addressing challenges related to skills, infrastructure, and credit is essential. By promoting cooperative farming, strengthening capacity building, and empowering women through SHGs, AI can be effectively leveraged to enhance farm productivity, increase incomes, and help realise India’s aspiration of becoming a Viksit Bharat by 2047.