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Artificial Intelligence (AI) In Agriculture Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The artificial intelligence (AI) in agriculture market has undergone substantial expansion in recent years. It is anticipated to expand from $2.71 billion in 2025 to $3.37 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 24.5%. The historical growth of this market can be linked to factors such as rising food demand, the initial embrace of farm automation, progress in sensor technologies, the advancement of precision agriculture, and the requirement for enhanced crop productivity.
The artificial intelligence (AI) in agriculture market is anticipated to experience significant growth in the upcoming years. It is projected to reach $8.23 billion by 2030, at a compound annual growth rate (CAGR) of 25.0%. This expansion during the forecast period can be attributed to the increasing adoption of smart farming practices, efficiency requirements driven by climate change, the proliferation of agri robotics, government support for digital agriculture, and heightened investment in agri-technology. Prominent trends within this period include precision farming technologies, AI-driven crop monitoring systems, autonomous agricultural machinery, predictive yield analytics, and smart resource management solutions.
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Artificial Intelligence (AI) In Agriculture Market Demand Drivers: What Is Fueling Industry Growth?
The growth of artificial intelligence (AI) in the agriculture market is expected to be driven by the increasing necessity for enhanced food production to ensure food security. Food security involves the ready availability, accessibility, and proper utilization of food that satisfies people’s dietary needs and preferences for an active and healthy life, guaranteeing everyone has access to sufficient safe, nourishing food. AI is capable of optimizing agricultural operations, improving crop yields, and processing large volumes of data such as weather patterns, soil conditions, and crop health to provide farmers with real-time intelligence and precise guidance. This technology enables better choices in irrigation, fertilization, pest control, and harvesting, resulting in higher productivity, less waste, maximized food output, and global food security. For instance, in April 2025, the United States Department of Agriculture, a US-based government department, projected that the 2024/25 global rice production forecast would increase by 3.1 million tons, reaching a record 535.8 million (milled basis), which is nearly 3% larger than the preceding year. Therefore, the demand for increased food production for food security is stimulating the expansion of AI in the agriculture market.
Artificial Intelligence (AI) In Agriculture Market Categorization By Product Type And Application
The artificial intelligence (AI) in agriculture market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Technology: Machine Learning, Predictive Analysis, Computer Vision
3) By Deployment: Cloud, On-Premise, Hybrid
4) By Application: Precision Farming, Agriculture Robots, Livestock Monitoring, Drone Analytics, Labor Management, Other Applications
Subsegments:
1) By Hardware: Sensors, Drones, Imaging Systems, Robotics, Automated Equipment
2) By Software: Data Analytics Platforms, Farm Management Software, AI-Based Prediction Tools, Image Processing Software
3) By Services: Consulting Services, System Integration Services, Maintenance And Support Services
Artificial Intelligence (AI) In Agriculture Market Transformation Trends: Which Innovations Are Driving Change?
Major entities operating within the artificial intelligence (AI) domain in the agriculture market are prioritizing the development of product innovations, including revolutionary platforms designed to improve yield predictions, refine decision-making processes, and promote environmentally sound farming practices. A ‘groundbreaking platform’ refers to an inventive system or technology that redefines established practices within its field, setting new standards and stimulating subsequent advancements. Such platforms frequently address previously unmet needs and introduce novel solutions. For instance, in September 2024, Helios AI, a US-based software company, unveiled CommodiTrack, an advanced platform by Helios AI that integrates comprehensive climate risk data and predictive analytics to bolster the resilience of the agrifood supply chain. It provides users with actionable insights, enabling them to swiftly respond to market volatility and disruptions.
Artificial Intelligence (AI) In Agriculture Market Company Landscape And Strategic Competition
Major companies operating in the artificial intelligence (AI) in agriculture market are Google LLC; Microsoft Corporation; IBM Corporation; Bayer AG; John Deere; Oracle Corporation; CNH Industrial N.V.; Wipro Limited.; Valmont Industries Inc.; Raven Industries Inc.; Climate LLC; Granular Inc.; Ag Leader Technology Inc.; FarmWise Labs Inc.; Taranis; Ceres Imaging; AgEagle Aerial Systems Inc.; PrecisionHawk; Descartes Labs Inc.; Farmobile LLC; AppHarvest; Farmers Edge Inc.; Iron Ox; Prospera Technologies; aWhere Inc.; Agribotix; Abundant Robotics; Agworld; Harvest Croo Robotics; Gamaya SA; Tule Technologies
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Artificial Intelligence (AI) In Agriculture Market Geographic Analysis: Where Is Demand Growing The Fastest?
North America was the largest region in the artificial intelligence (AI) in agriculture market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI) in agriculture market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.