Applied AI In Agriculture Market Landscape 2025: Forecast Data and Growth Strategy Insights

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What Is the Expected CAGR for the Applied AI In Agriculture Market Through 2025?
The market size of applied artificial intelligence in agriculture has experienced rapid growth in the last few years. Forecasts predict an increase from $2.89 billion in 2024 to $3.75 billion in 2025, indicating a compound annual growth rate (CAGR) of 29.7%. The significant increase observed in the past can be attributed to several factors including, availability and gathering of data, advancements in technology, inadequacy of labor, the impact of climate change and sustainability, as well as environmental issues.

What's the Projected Size of the Global Applied AI In Agriculture Market by 2029?
In the forthcoming years, the market size of applied AI in agriculture is projected to surge remarkably. An increase to $10.5 billion by 2029, with a Compound Annual Growth Rate (CAGR) of 29.4% is expected. The anticipated growth during this period is due to factors such as the rising need for precision farming, various government schemes and subsidies, a growing demand for food security, investments put into agritech startups, and decision-making based on data. Some leading trends during this forecast period consist of the expansion of precision agriculture, predictive analytics powered by AI, automation and robotics, intelligent irrigation systems, and crop breeding enhanced by AI.

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Top Growth Drivers in the Applied AI In Agriculture Industry: What's Accelerating the Market?
An uptick in crop productivity is predicted to fuel the growth of the applied AI in agriculture market. When we talk about crop productivity, we refer to the measurement of crop output, usually denoted through yield by per unit land area. It is increasing due to the evolution of agricultural technology and methods. These include advanced crop types, better irrigation techniques, and precision farming. Applied AI is used in agriculture to boost crop productivity by refining farming processes through valuable data insights, predictive analytics, and automation. For example, the United States Department of Agriculture, a federal executive department responsible for the formulation and execution of federal laws in the US, noted in January 2024 that the average yield of rice in the US was assessed to be 7,649 pounds per acre in 2023. This is an increase of 264 pounds from the 2022 average yield of 7,385 pounds per acre. Hence, the enhancement of crop productivity is leading to the expansion of the applied AI in agriculture market.

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What Trends Will Shape the Applied AI In Agriculture Market Through 2029 and Beyond?
Key businesses within the applied AI in the agriculture market are prioritizing the creation of innovative solutions like AI-based tools to maintain their dominance in this sector. AI-based tools include software and technologies that employ artificial intelligence to upgrade diverse areas of farming and agricultural procedures. An example of this was in July 2024, when Google LLC, an American technology company, introduced Agricultural Landscape Understanding (ALU), an advanced AI tool, to improve agricultural methods in India, specifically in the areas of drought readiness and irrigation management. Using detailed satellite images and machine learning, this tool generates personalized insights for each farm field, catering to the unique requirements of India's varied agricultural environment. The ALU tool can delineate precise field boundaries and analyze various factors like crop variety, field dimensions, and closeness to water bodies, which are essential for effective irrigation and drought control strategies. The aim of this project is to empower farmers by enhancing crop outputs, making capital more accessible, and improving market entry for agricultural goods.

What Are the Main Segments in the Applied AI In Agriculture Market?
The applied ai in agriculturemarket covered in this report is segmented -

1) By Component: Hardware, Software, Service
2) By Technology: Machine Learning And Deep Learning, Predictive Analytics, Computer Vision
3) By Application: Precision Farming, Drone Analytics, Agriculture Robots, Livestock Monitoring, Other Applications

Subsegments:
1) By Hardware: Sensors (Soil, Climate, Crop Monitoring), Drones For Crop Surveillance, Automated Tractors And Harvesters, GPS & GIS Systems For Precision Farming, Imaging Systems, IoT Devices For Agricultural Monitoring, Robotics For Seeding, Planting, And Weeding
2) By Software: Farm Management Software, AI-Based Crop Prediction Software, Precision Agriculture Software, Irrigation Management Software, Pest And Disease Detection Software, Data Analytics And Visualization Tools, Supply Chain Optimization Software, Machine Learning Algorithms For Yield Prediction
3) By Service: AI Integration And Implementation Services, Data Analytics Services For Crop And Soil Analysis, Cloud-Based Agricultural Services, AI Model Training And Customization Services, Maintenance And Support Services, Consultation And Advisory Services For AI Adoption In Agriculture

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Which Top Companies are Driving Growth in the Applied AI In Agriculture Market?
Major companies operating in the applied AI in agriculture market are Microsoft Corporation, BASF SE, International Business Machines Corporation, Bayer AG, Deere & Company, SAP SE, CNH Industrial N.V., Kubota Corporation, Corteva Inc., AGCO Corporation, Trimble Inc., Raven Industries Inc., The Climate Corporation, AG Leader Technology, The BAE Systems Taranis, Farmers Edge Inc., PrecisionHawk, AgEagle Aerial Systems, Descartes Labs Inc., Prospera Technologies Ltd., Agribotix, Gamaya

Which Regions Will Dominate the Applied AI In Agriculture Market Through 2029?
North America was the largest region in the applied AI in agriculture market in 2024. The regions covered in the applied AI in agriculture market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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