Use case type
Provides crop, soil, weather, and field recommendations to support farm decisions. It helps growers improve yield, reduce input waste, and manage agricultural risks.
22
22
1
13 mo
Adoption over time
By case publish month · completed months only
16 cases documented across 37 months (Jul 23 – Jul 26), peaking at 2 in January 2024.
1 earlier case before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
10 shown from 22 use cases
A leading digital transformation & AI company developed Generative AI-powered Agriculture AI Agents to support farming operations using Microsoft technologies.
Land O'Lakes, a leading US agricultural cooperative, expanded its partnership with Microsoft to launch Oz, an AI-powered digital assistant built on Azure AI Foundry. Oz gives retail agronomists instant access to two decades of proprietary crop data, supporting rapid, informed decisions for cost-effective farming interventions. The alliance aims to relieve economic pressure on US farms facing rising input costs, margin squeezes, and climate-related challenges.The collaboration represents a broader modernization initiative, with the majority of Land O'Lakes' IT migrated to Azure Cloud and Copilot tools tailored to farm management. Additional digital platforms, like Digital Ag and Digital Dairy, enable farmers to track soil health, optimize herds, and align outputs with consumer demand.Oz is being positioned as a precision tool for agronomists and demonstrates how AI and cloud can advance food security, climate-resilient farming, and operational efficiencies in agriculture.
Microsoft Research Africa and India, in collaboration with Digital Green, developed Project Gecko to improve the adoption and effectiveness of generative AI for smallholder farmers in India and Kenya. The project addresses significant barriers for farmers, such as language, cultural context, and lack of digital infrastructure.At its core is MMCTAgent, a multimodal AI agent built with Azure AI Foundry, using the VeLLM platform to generate multilingual, culturally relevant content and advice. The agent processes queries via text, voice, or video, and responds with actionable guidance through those same modalities—optimized for low bandwidth and minimal computing resources.The system integrates community-sourced agricultural videos and knowledge provided by Digital Green, allowing the AI to surface advice in the farmer's language, with content referencing the specific steps relevant to their problem.Initial field results confirm improved usability, trust, and farming outcomes over generic AI products. The solution is designed to be extensible to healthcare, education, and retail, reflecting its potential as a blueprint for inclusive, domain-specific, agentic AI applications.
Bayer and Microsoft launched an adapted AI initiative for precision agriculture in the United States.The effort includes E.L.Y. (Expert Learning for You), a domain-specific generative AI model that helps agronomists and farmer-facing employees answer questions on agronomy, farm management, Bayer agricultural products, weather, crop health, and irrigation management.A specialized E.L.Y. Crop Protection small language model based on Microsoft Phi-3 is available on the Azure AI model catalog to support crop-protection decisions and sustainable agriculture.
Tavant has developed and launched advanced artificial intelligence agents using Microsoft Copilot Studio for the agriculture and food sectors. The solution features specialized agents such as a Sales Assistant and a Virtual Agronomist designed to automate critical sales processes and deliver rapid agronomic insights to farmers.These agents support workflow simplification, enable growers to make data-driven decisions, and ultimately enhance farm productivity and efficiency. The implementation demonstrates the power of AI-driven automation in improving real-time insight delivery and supporting essential business processes in the agriculture industry.
Map My Crop, in partnership with Microsoft, ADT Baramati, and Oxford University, deployed an AI-driven Satellite Crop Monitoring Platform that transformed traditional sugarcane farming practices in Baramati, Maharashtra, India.The solution included real-time remote sensing, AI-based agronomic advisory, and Variable Rate Application fertilizer mapping, enabling farmers to act on data-driven insights for better yield and resource management.The project compared AI-managed plots versus traditionally managed ones, showing substantial gains: onboarding over 1000 farmers in days, reducing input costs by 41%, improving yields from 70 to 120 tons/acre, and minimizing necessary farm visits by 75%.AI-powered analysis on the Microsoft platform provided direct recommendations for irrigation, nutrient use, and pest control, improving both operational efficiency and overall crop health. AI-predicted crop growth metrics like plant height, cane weight, and sucrose content showed consistent improvement.By integrating AI with remote sensing and precision agriculture, Map My Crop's platform demonstrated scalability, sustainability, and the potential for significant gains in productivity and profitability, serving as a replicable model for smart farming across India.
Safaricom partnered with Opportunity International to develop FarmerAI, an AI-powered chatbot for smallholder farmers in Kenya's rural regions.This chatbot, designed with human-centered principles, leverages generative AI to provide localized advice on weather, pest management, fertilizer application, and market prices.Accessible via SMS and WhatsApp through Safaricom’s DigiFarm platform, FarmerAI eliminates the bottleneck of traditional field agent networks, enabling farmers to receive timely, actionable insights.The service began as a pilot during the potato crop cycle, enrolling up to 1,000 farmers and engaging with them to ensure solution responsiveness and usability.FarmerAI also helps farmers access digital financing services and strengthens economic resilience in remote communities.The solution supports increased crop yields, food security, and improved farmer incomes by bridging the digital divide.Collaboration between Safaricom and Opportunity International demonstrates the impact of technology in agriculture and underscores their commitment to equitable knowledge distribution for underserved populations.The project has received positive feedback for its accessibility and ongoing digital engagement with end-users.Results highlight increased access to actionable farming knowledge, empowerment of smallholder farmers, and strengthened rural digital connectivity.
Bayer, a leading life science company, leveraged Microsoft Azure AI Adapted Models to transform crop protection practices in agriculture. The company developed the E.L.Y. Crop Protection model using Azure AI Studio, targeting real-world agricultural needs for sustainable chemical use, compliance, and tailored agronomic insights.This specialized small language model (SLM) was trained on thousands of crop protection label questions, delivering region- and crop-specific decision support for agricultural partners and enterprises. Deployed through the Azure AI Model Catalog and Copilot Studio, the model provides customizable, responsible AI solutions.The approach ensures scalable support for farms of all sizes, reinforcing responsible usage and regulatory compliance. Microsoft Cloud and a robust ecosystem of partner integrations expand the reach and capability of Bayer's solution, while also maintaining data security and customization.The collaboration enables tailored innovations for operations globally, setting a new benchmark in digital agriculture. With access to a broad range of Azure AI tooling and Copilot Studio, Bayer empowers others in the agrifood chain to implement advanced digital solutions.Bayer's E.L.Y. Crop Protection model exemplifies a responsible, real-world use of generative AI in industry, showing improvement in accuracy, efficiency, and operational reach of crop protection.
Farmer.Chat is a generative AI-powered chatbot for smallholder farmers that delivers localized agronomic advice through retrieval-augmented generation, multilingual support, and multimodal inputs across WhatsApp, Telegram, and mobile apps.The platform integrates structured and unstructured agricultural knowledge, external services such as weather and disease diagnostics, and user feedback loops to improve response quality and trust.It has been deployed across Kenya, India, Ethiopia, and Nigeria and has handled more than 300,000 queries for over 15,000 users.
Kenya Agriculture and Livestock Research Organisation (KALRO), in partnership with TomorrowNow.org and Tomorrow.io, has piloted AgriAdvisor, an AI-driven copilot designed for small-scale farmers in Kenya. The copilot leverages generative AI to provide localized agronomy and weather advice, supporting farmers in both English and Swahili. Accessible via multiple digital channels, this solution targets gaps in real-time agricultural information for rural farmers. The implementation demonstrates the capabilities of Microsoft Copilot in addressing language, access, and contextualization issues for emerging markets. While detailed business metrics are not stated, the impact is positioned around improved on-farm decision making and sustainable productivity gains. The project is rooted in Microsoft Research Lab Africa's ongoing push for scalable, AI-based market interventions.AgriAdvisor demonstrates a technology approach tailored for localized, actionable knowledge delivery, making it easier for farmers to access best practices without direct expert intervention.
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