Press release
Applied AI In Agriculture Market Set to Reach $10.5 Billion by 2029 with 29.4% Yearly Growth
Applied AI In Agriculture Market Size
The market size for applied AI in agriculture has expanded significantly in the recent past. It's projected to rise from $2.89 billion in 2024 to $3.75 billion in 2025, registering a compound annual growth rate (CAGR) of 29.7%. Factors contributing to this growth during the historic period include the accessibility and accumulation of data, advances in technology, labor deficits, concerns related to climate change and sustainability, and issues concerning the environment.
The market size of applied AI in agriculture is anticipated to witness drastic expansion in the upcoming years, with expectation to reach $10.5 billion by 2029, showcasing a Compound Annual Growth Rate (CAGR) of 29.4%. This projected increase during the forecast period can be credited to the surge in requirement for precision farming, governmental policies and subventions, growing demand for food security, investments towards agritech startups, and data-centric decision-making processes. The forecast period is predicted to see major trends such as the progression of precision agriculture, predictive analysis fueled by AI, automation and robot technology, advanced irrigation systems, and enhanced crop breeding through AI.
What Are the Forces Behind the Rapid Growth of the Applied AI In Agriculture Market?
The growth of the applied AI in agriculture market is anticipated to be driven by heightened crop productivity. Crop productivity, which measures crop output per unit area, is on the rise thanks to advancements in agricultural technology and practices. Notable improvements include enhanced crop strains, more efficient irrigation, and the application of precision farming methods. By providing data-driven insights, predictive analytics, and automation, applied AI in agriculture helps optimize these practices, thereby boosting crop productivity. For example, the United States Department of Agriculture, a US-based agency responsible for enforcing federal laws, reported in January 2024 that the average yield across all US rice had risen to an estimated 7,649 pounds per acre in 2023. This represented an increase of 264 pounds from the 2022 average of 7,385 pounds per acre. Hence, the rise in crop productivity is fueling the expansion of the applied AI in agriculture market.
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Who Are the Dominant Companies Influencing Applied AI In Agriculture Market Trends?
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
How Is the Applied AI In Agriculture Market Evolving?
Leading businesses working in the applied AI agricultural domain are dialing up their commitment to devise innovative solutions, such as tools driven by AI, in a bid to maintain their market foothold. AI-based tools allude to software and technologies that leverage artificial intelligence to augment several facets of farming and agricultural operations. For example, Google LLC, a tech firm from the US, unveiled a groundbreaking AI-powered tool, named Agricultural Landscape Understanding (ALU), in July 2024 to revolutionize farming practices in India, concentrating particularly on drought readiness and irrigation management. This tool leverages high-definition satellite images and machine learning to offer bespoke insights for individual agricultural fields, catering to the diverse requirements of India's farming landscape. With the definition of precise field perimeters, the ALU tool can assess diverse variables such as crop variant, field dimensions, and proximity to water bodies, which are vital for effective irrigation and drought management strategies. The primary ambition of this venture is to empower agriculturists by augmenting crop yields, facilitating access to funds, and enhancing the market accessibility of agricultural products.
What Are the Different Segmentations 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 Region Is at the Forefront of the Applied AI In Agriculture Market?
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.
What Is Covered In The Applied AI In Agriculture Global Market Report?
- Market Size Analysis: Analyze the Applied AI In Agriculture Market size by key regions, countries, product types, and applications.
- Market Segmentation Analysis: Identify various subsegments within the Applied AI In Agriculture Market for effective categorization.
- Key Player Focus: Focus on key players to define their market value, share, and competitive landscape.
- Growth Trends Analysis: Examine individual growth trends and prospects in the Market.
- Market Contribution: Evaluate contributions of different segments to the overall Applied AI In Agriculture Market growth.
- Growth Drivers: Detail key factors influencing market growth, including opportunities and drivers.
- Industry Challenges: Analyze challenges and risks affecting the Applied AI In Agriculture Market.
- Competitive Developments: Analyze competitive developments, such as expansions, agreements, and new product launches in the market.
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