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The U.S. artificial intelligence in agriculture market is projected to reach $6.63 billion by 2035, while Europe is expected to grow to $6.08 billion, driven by precision farming, AI-powered crop monitoring, government digital agriculture initiatives, and sustainable farming programs under the European green deal.

Austin, July 01, 2026 (GLOBE NEWSWIRE) — The Artificial Intelligence in Agriculture Market size was valued at USD 2.78 Billion in 2025 and is expected to reach USD 24.55 Billion by 2035, growing at a CAGR of 24.34%.

The global AI in agriculture market is seeing transformational growth as food production systems face unprecedented pressure from climate variability, labour shortages, population growth and natural resource constraints. Technologies such as machine learning, computer vision, predictive analytics, robotics and natural language processing enable farmers to leverage data from satellites, drones, IoT sensors and weather stations to make precise, data-driven decisions.

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Generative AI Farm Advisory Integration and Carbon Credit AI Verification to Augment Market Expansion Globally

The most commercially viable near-term opportunity is building a generative AI farm advisory platform where natural language farmer interfaces remove the digital literacy barriers that traditional precision agriculture software requires. Carbon credit programme AI verification creating demand for AI soil monitoring platforms with measurement, reporting and verification capability at farm scale economics. Each carbon credit programme adopting AI based MRV creating sustained recurring revenue sustaining long term market expansion globally.

Segmentation Analysis:

By Offering, Software Dominated the Market; Hardware Segment to Register the Fastest CAGR Globally

Software accounted for the largest share of the market in 2025, with revenues approaching 55% as these farm management information systems combine AI analytics with field mapping, financial tracking, and compliance documentation, providing comprehensive platform utility that sustains subscription relationships. The progressive commoditization of AI-enabled edge computing, drone platforms and IoT agricultural sensors will reduce capital cost barriers across farm operations globally, with the hardware expected to register the highest CAGR in the forecast period 2026-2035.

By Technology, Machine Learning & Deep Learning Dominated the Market; Computer Vision Segment to Register the Fastest CAGR Globally

Story Continues

Machine Learning & Deep Learning Dominated the Market by Technology owing to proven effectiveness in yield prediction, disease risk forecasting, soil nutrient modelling, and precision irrigation scheduling, with compounding accuracy improvements generated by each growing season. The highest CAGR is projected to be registered by computer vision from 2026 to 2035, owing to the proliferation of high-resolution drone cameras, robotic platform vision systems, and automated sorting lines that require visual inspection instead of manual grading worldwide.

By Application, Precision Farming Dominated the Market; Agriculture Robots Segment to Register the Fastest CAGR Globally

Precision farming had the largest share in 2025, with variable rate fertilizer, seed and pesticide application technology delivering the most proven and widely adopted AI agriculture ROI calculation for North American and European commercial farming operations. Agriculture robots are predicted to see the highest CAGR between 2026 and 2035 as the severity of agricultural labour shortages, minimum wage increases and falling robotic hardware costs lead to economic crossover points where autonomous harvesting and weeding can achieve global commercial payback periods.

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Regional Insights:

North America accounted for the highest revenue share in the global AI in agriculture market in 2025, contributing to 36% revenue share due to high technological innovation, early adoption of precision farming, developed agri-tech infrastructure and government policies. John Deere, The Climate Corporation, Trimble Agriculture, AG Leader Technology, and Corteva Agriscience’s commercial operations account for about 87.4% of North American revenues in the United States.

The U.S. Artificial Intelligence in Agriculture Market size is valued at around USD 0.77 Billion in 2025 and is projected to reach around USD 6.63 Billion by 2035, at a CAGR of 24.03%. Growth is driven by the scale of commercial row crop farming, USDA precision agriculture research programmes, Farm Bill technology investment and the partnership between John Deere and NVIDIA on real-time AI analytics for autonomous tractor platforms.

The Europe Artificial Intelligence in Agriculture Market was valued at USD 1.28 Billion in 2025 and is projected to reach USD 6.08 Billion by 2035, growing at a CAGR of 16.87%. The European market is bolstered by the European Green Deal’s Farm to Fork strategy, digital farming support from the Common Agricultural Policy and strong sustainability mandates in Germany, the Netherlands, France and the United Kingdom, with commercial supply supported by BASF’s xarvio platform and Bayer’s precision agriculture operations.

Asia Pacific region is the fastest growing market, driven by food security concerns in highly populated countries, an explosion of agri-tech startups and government-sponsored digital farming initiatives in China, India, Japan, South Korea and South-east Asia. Government smart agriculture investment in China accounts for approximately 44.8% of Asia Pacific revenues. India’s Digital Agriculture Mission and fast-growing agri-tech startup ecosystem will lead to above-average emerging market growth through 2035.

Key Players:

Recent Developments:

2024: Bayer Crop Science began developing a new AWS-based data science platform with generative AI capabilities built with Amazon SageMaker Studio and Bedrock targeting innovative agricultural advisory solutions.

2024: John Deere announced a strategic partnership with NVIDIA to develop real-time AI analytics for self-driving tractor platforms combining Jetson Orin edge computing with autonomous guidance systems.

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Exclusive Sections of the Report (The USPs):

AI Platform & Precision Farming Performance Metrics – helps you understand adoption trends across software, hardware, and autonomous machinery categories along with improvements in yield accuracy, input optimisation, and farm management efficiency across deployments globally.

Machine Learning & Computer Vision Technology Metrics – helps you evaluate ML yield prediction investment, computer vision disease detection adoption, drone imagery analysis platforms, and specialist agri-tech provider competitive positioning globally.

Agriculture Robotics & Autonomous Machinery Metrics – helps you analyze robotic harvesting investment, autonomous tractor deployment, weeding and planting system adoption, and labour-cost-driven automation ROI across diverse farming verticals globally.

Generative AI & Farm Advisory Platform Metrics – helps you uncover growth in natural language farm advisory adoption, generative AI integration investment, and smallholder digital accessibility platform development across global agricultural markets.

Carbon Credit & Climate-Smart Agriculture Metrics – helps you identify growth opportunities in AI-based MRV adoption, soil carbon sequestration monitoring, and climate-smart agriculture programme investment across regulated and voluntary carbon market verticals globally.

Competitive Landscape & AI Agriculture Expansion Metrics – helps you gauge the competitive strength of key market players based on AI platform breadth, autonomous machinery capability, and geographic farm technology deployment footprint globally.

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