FARMING in South Asia is standing at a crossroads: rising populations, erratic weather and a deep digital divide. As reported by Food and Agriculture Organisation (2017) in ‘The future of food and agriculture: trends and challenges’, global food demand is expected to rise by 60 per cent by 2050, placing unprecedented pressure on agriculture to produce more with fewer resources. This challenge is nowhere more urgent than in South Asia, which is one-fourth of the world’s human habitat and one of the most climate-risky agricultural communities in the world. According to the World Bank collection of development indicators (2023), about 41.93 per cent of South Asian employment depends on agriculture for economic stability and food security. However, South Asian agricultural sectors are dependent on a traditional system, which mainly increases the possibility of vulnerability to climate change, resource depletion and outdated practices. For these reasons, using artificial intelligence in the agricultural sector is no longer a futuristic luxury but a strategic necessity, both as a productivity enhancer and as a pathway toward sustainable farming that conserves natural resources and uplifts rural communities. As stated by the Food and Agriculture Organisation, over 70 per cent of freshwater in South Asia is used for agricultural purposes. However, most freshwater is not used efficiently. This issue urgently calls for a specific and data-driven solution- those areas where AI can play a vital and transformative role in effectively solving the problem.
Artificial intelligence is transforming agriculture from the ground up. From weather forecasting to demand forecasting, risk profiling, AI image recognition, AI soil data modelling, route optimisation, price prediction algorithms-AI system can analyse large-scale data and provide information to the farmers for more thoughtful planning, easier loan access, reduced post-harvest loss, reduced chemical use, efficient logistics, transparent pricing, energy efficient farming and so on which was not possible previously. Those AI technology systems are also used to monitor crop health, like Krishi Network, which serves this facility that farmers can use a smartphone camera to take a picture, recognise the health of the crop or disease and find a solution to diagnose. So, using AI technology is not difficult to handle, but it needs proper instruction. Dr Rozy Dhanta and Marizvikuru Mwale stated at Transforming Agriculture With Modern AI: Harnessing Artificial Intelligence to Revolutionise Farming, ‘AI is transforming how farmers plan, plant, irrigate, fertilise and protect their crops — enabling data-driven agriculture that is smarter, not harder.’
Now the burning question is: What makes artificial intelligence in agriculture sustainable? First and foremost, the use of AI technology is fascinating. However, its long-term sustainability depends on its implications of responsibility and its inclusive application, such as consistent practice by reducing dependency on predictive work. Then again, sustainable AI use intends to increase productivity and ensure efficient use of natural resources like water, land and soil. Moving forward, AI reduces the dependency on prediction, enabling consistent data-driven decisions. As a result, farmers can make informed, reliable decisions that positively affect the stability of productivity and farmers’ income by minimising the overuse of water, fertiliser and chemicals and ensuring future farming viability. Sequentially, climate adaptability, like AI, helps farmers by informing them of climate risk and suggesting resilient crop varieties for avoiding floods, droughts, or unpredictable seasons. Following this, AI simplifies complex data and offers mobile-based applications that empower smallholder farmers into the digital fold, promoting economic fairness by narrowing the rural-urban divide.
How is AI transforming people’s lives in South Asia, not theoretically, but in reality? In Bangladesh platform like iFarmer, Krishi Bazar, Krishi Network, Smart Fertiliser, AgroShift are empowering farmers through risk profiling, predictive analytics, demand forecasting, AI image recognition, predictive alerts, AI soil data modelling, route optimisation and price prediction algorithms that ensuring easier loan access, more thoughtful planning, reduce post-harvest loss, improved yield, reduced pesticides misuse, reduced chemical waste, higher farmer profit margin, efficient logistics, energy efficient farming, water conservation, transparent pricing and so on. Furthermore, Krisha Patel (2025) pointed out in ‘Top 10 Best Agritech Startups in India 2025 | Revolutionizing Agriculture’ in India, platforms like Cropin, Fasal, DeHaat, AgNext and Ninjacart empower precision agriculture, traceability and supply chain optimisation, contributing to the efficient use of natural resources and better sustainability. Moreover, in Pakistan, Ricult uses Farmdar AI technology for credit scoring, forecasting, a model for farm-level decision making and satellite-driven precision farming. Meanwhile, Sri Lanka Govi Mithuru, Agrithmics, AiGrow, SenzAgro, FarmAgg and Spectrify AI enable farmers through AI-enhanced mobile farming advisory, harvest and cultivation notification. Moreover, AI firms like Smart Krishi, IFA Krishi, aQysta, Ficus Biotech Pvt Ltd and ICTforAG are helping farmers by providing location-based crop advisory and livestock disease prediction in Nepal. Then Afghanistan has National Horticulture & Livestock Project, Afghanistan Value Chains: Crops (USAID/DAI), Boustan Sabz and Afghan Agro Service for technological use in the agricultural sector, which include improved production, marketing innovation, eco-friendly methods and value-added strategies. These real-world examples show that AI in agriculture increases productivity and reshapes agriculture into a more resilient, environmentally friendly and inclusive system.
Though these AI agri-tech firms show much promise, they face notable obstacles. One of the main barriers is the digital literacy gap, because of this, farmers cannot operate those AI tools effectively. Dr Shahana Esmh pointed out in a 2022 report, ‘Without digital literacy, AI tools are useless to rural farmers who cannot interpret or trust what the technology is telling them.’
Infrastructure limitations, such as poor internet connection and a lower smartphone usage rate, are another barrier. The cost and accessibility of advanced AI tools are other concerning issues. Lastly, policy and privacy are other ethical and potential exploitation risk concerns. So, AI may benefit a few people without careful interference, leaving behind others.
In order to utilise AI’s sustainable potential in agriculture, South Asian countries should adopt a multidimensional strategy that ensures inclusive, affordable and long-term benefits. The government should consider subsidizing AI tools for small and marginal farmers so that these technologies reach the places most needed. Adding AI to existing agriculture extension services and training activities will increase farmers’ digital skills and confidence. Public-private partnerships should be encouraged to create and spread AI solutions to meet local needs. Besides, it is also important to create clear policies to use responsible data and ensure environmental rules. Open-source and encourage the AI ​​model to be locally suited, especially in rural areas, will increase its acceptance and effectiveness. Also, by setting up a ‘farmer innovation centre’, the pilot test of AI tools in the real agricultural environment will be more effective, from the laboratory to the field. Pandey and Mishra raised their voice in Towards sustainable agriculture: Harnessing AI for global food security that ‘Through the utilisation of artificial intelligence technologies, it is possible to optimize agricultural practices, thereby increasing production, enhancing resource management, mitigating post-harvest losses and fostering the development of more sustainable and resilient food systems.’
The importance of AI in agriculture is not just about producing more, but producing better for the betterment of people, planet, and future generations. In a region like South Asia, agriculture is a livelihood and lifeline, so operating through sustainability at every step from the soil to the software is important. If we can ensure that this technology benefits not only some people, it will not just revolutionise the agricultural sector, a sustainable food future for the entire region can be ensured.
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Kazi Md Samiul Hoq is a BBA student at North South University.
