Artificial Intelligence (AI)-powered mobile agents are rapidly emerging as a game-changing technology for Pakistan’s agricultural sector. With over 60 percent of Pakistan’s rural population directly or indirectly dependent on agriculture, AI-based advisory systems can bridge longstanding gaps in extension services, improve productivity, and enhance farmers’ incomes. Through smartphones, farmers can now access real-time, localised, and data-driven guidance without relying solely on traditional extension workers or costly private consultants.
- Instant disease and pest diagnosis
Crop losses from pests and diseases remain a major challenge in Pakistan. AI-powered image recognition technology now enables farmers to simply photograph an affected leaf, fruit, or plant with their mobile phones. The AI system analyses the image within seconds and identifies the disease, nutrient deficiency, or pest infestation.
For example, diseases such as cotton leaf curl virus, whitefly, wheat rust, rice blight, citrus canker, mango anthracnose, tomato leaf miner, and others can be detected at an early stage. The system then recommends suitable control strategies, including appropriate pesticides, biological controls, dosage, and timing. This support enables early disease detection, which minimises crop losses, optimises pesticide use, reduces production costs, improves crop quality and yields, and promotes environmentally sustainable farming practices.
- Hyper-local weather and irrigation forecasting
Weather variability has increasingly threatened agricultural productivity in Pakistan. AI agents combine data from satellites, weather stations, soil sensors, and historical climate records to produce highly localized forecasts. Farmers can then receive specific recommendations for their fields on topics such as irrigation scheduling, rainfall predictions, heatwave and frost alerts, humidity and disease-risk forecasts, and harvest planning.
For example, a wheat farmer in Punjab can receive alerts about upcoming rainfall and delay irrigation, saving water and lowering energy costs. Likewise, cotton growers can skip pesticide applications before rain. Therefore, AI will improve water management, lower irrigation costs, increase climate resilience, and improve crop yields and resource use.
- Multilingual AI chatbots for farmer advisory services
One of the key strengths of AI mobile agents is their ability to communicate in local languages such as Urdu, Punjabi, Saraiki, and other regional languages and dialects. Farmers can interact through voice commands or text messages, making the technology accessible even to those with limited literacy. For example, a farmer might ask, “When should I sow maize?”, “How much urea should I apply to wheat?”, or “What is causing yellowing in my rice crop?”
The AI chatbot then provides instant, region-specific recommendations based on crop stage, soil conditions, and local weather forecasts. This democratizes access to agricultural knowledge, reduces reliance on intermediaries, and strengthens decision-making at the farm level. It also encourages the adoption of modern, climate-smart farming practices.
- Precision nutrient and fertiliser management
AI systems can analyse soil-test results, cropping history, and yield targets to recommend precise fertiliser requirements. Instead of blanket fertiliser applications, farmers receive customised nutrient management plans.
This is particularly important in Pakistan, where excessive or imbalanced fertiliser use often increases production costs while lowering nutrient-use efficiency. The direct benefits include improved fertiliser efficiency, reduced input costs, higher crop yields, and better soil health and long-term sustainability.
- Yield prediction and farm economics
Modern AI platforms can estimate expected yields based on crop growth, weather conditions, satellite imagery, and management practices. These predictions help farmers make informed marketing and financial decisions before harvest. AI tools can also track farm expenditures, calculate production costs, estimate profitability, and compare crop options for future seasons.
For example, a sugarcane or wheat farmer can assess expected returns and decide whether to sell immediately after harvest or store the produce for better market prices. As a result, AI contributes to improved farm profitability, better financial planning, reduced market risks, and more informed investment decisions.
- Market intelligence and price forecasting
Agricultural markets in Pakistan often experience significant price fluctuations. AI-driven platforms can monitor wholesale markets, commodity exchanges, and supply–demand trends to provide real-time market intelligence. Farmers can receive updates on current commodity prices, expected price trends, nearby buyers and processors, and optimal selling periods.
This helps farmers negotiate better prices and reduces exploitation by middlemen. Consequently, the direct impacts include increased farmer incomes, improved market access, stronger bargaining power, and more efficient agricultural value chains.
- Supporting farmers support services
AI mobile agents can enhance farmers’ support services by delivering timely, personalised recommendations to thousands of farmers simultaneously. Public- and private-sector field services, as well as farmers themselves, can use AI platforms to disseminate and access pest outbreak alerts, crop advisories, water conservation guidelines, and disaster preparedness messages. These tools help to increase the outreach of extension services, enable faster information dissemination, improve policy implementation, and strengthen agricultural resilience.
- Conclusion
AI mobile agents can transform Pakistan’s agriculture by delivering personalised, real-time, location-specific guidance to farmers’ smartphones. Using data analytics, satellite imagery, and machine learning, they can support the full crop cycle from land preparation and seed selection to harvesting and post-harvest management.
AI-powered diagnostic tools can detect crop diseases and pests early from phone images and recommend targeted treatments, cutting yield losses and pesticide misuse. Precision nutrient systems can suggest fertiliser plans based on soil, crop type, and climate, improving efficiency and lowering costs. Hyperlocal weather forecasts and climate alerts help optimize irrigation, planting, and harvesting while reducing vulnerability to extreme events. These agents can also provide market intelligence, advise on when and where to sell, and connect farmers with buyers and digital marketplaces. With local-language voice and chat interfaces, they can support smallholders with limited literacy, enabling data-driven decision-making, higher productivity, and stronger rural livelihoods.
- Way forward
The private sector in Pakistan has a significant lead in this area. The Government of the Punjab is also making serious efforts to digitalise agriculture, and a number of mobile applications and IT-based services have been introduced to support more than 6 million registered farmers.
In particular, digitalisation of agriculture is being promoted through various platforms that provide farmers with information on weather, market prices, advisory services, and access to subsidies.
All farmer-support services, subsidies, and development programmes are being progressively automated, ensuring more transparent, timely, and efficient delivery. As these digital systems continue to expand and improve, substantial gains in productivity, resource management, and farmers’ incomes are expected to become evident in the coming months and years.
Copyright Business Recorder, 2026
The writer is an Executive Member, Punjab Agriculture Research Board, Punjab