New York, April 06, 2023 (GLOBE NEWSWIRE) -- The global Artificial Intelligence (Ai) In Agriculture market size is expected to be worth around USD 10.2 billion by 2032 from USD 1.2 billion in 2022, growing at a CAGR of 24.5% during the forecast period from 2022 to 2032. Artificial intelligence techniques in agriculture can boost yield and productivity. Agribusiness companies employ artificial intelligence technologies that use predictive analytics. These AI-based applications and techniques can be utilized for controlling pests, increasing yields, monitoring soil conditions, and streamlining agricultural-related tasks throughout the food supply chain. As it analyzes farm data, artificial intelligence is increasingly being employed in agriculture to enhance harvest quality and accuracy.
In the agricultural industry, artificial intelligence solutions like drones, robots, and ground-based wireless sensors are becoming more widely utilized. In November 2017, Microsoft joined forces with the International Crop Research Institute of the Semi-Arid Tropics to launch an AI Sowing App. NatureFresh Farms is another U.S. tech company using artificial intelligence technology to analyze plant data at scale and produce accurate yield and harvest forecasts; their algorithm even predicts when blossoms will ripen.
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Key Takeaway:
- By Technology, in 2022, the artificial intelligence (AI) in the agriculture market was dominated by the machine learning and deep learning segment, with a revenue share of 39.6%
- By Application, the precision farming segment administrated the demand with a revenue portion over the forecast period.
- By Component, software represented the greatest revenue piece of over 45.2% in 2022.
- In 2022, North America dominated the market with the highest revenue share of over 39%.
- Over the forecast period, Asia Pacific is expected to witness the highest compound annual growth rate due to the increasing use of artificial intelligence technology in agriculture.
Factors affecting the growth of the artificial intelligence (AI) in agriculture industry?
Several factors can have an impact on the growth of artificial intelligence (AI) in agriculture industry. Some of these factors include:
- Each day, vast amounts of data are created in both structured and unstructured forms.
- This includes historical weather patterns and soil reports, as well as new research and drone images taken at specific spots. IOT solutions can sense all this to increase yield and provide strong perceptions.
- Remote Sensing, which detects proximity to a location, and Remote Sensing Underground Soil at that specific spot are two commonly used technologies for intelligent data fusion.
- Rowbot is one such hardware solution that combines data-gathering software with robotics to produce the ideal fertilizer for corn.
- High-altitude agriculture is one of the hottest topics in agriculture today. Drone-based images provide invaluable field analysis, crop observation, scanning, and more; farmers can even combine IOT and drone data to make quick decisions.
- Aerialtronics installed the IBM Watson IoT Platform and Visual Recognition APIs on its commercial drones for real-time image analysis.
- Computer vision technology is being increasingly employed to detect crop readiness, detect disease and manage fields - helping farmers stay ahead.
- Hyperspectral imaging, remote sensing, and 3d laser scanning are all potential methods for creating crop metrics over thousands of acres.
- This technology could revolutionize how farmers view farmlands. Monitoring can be conducted throughout a crop's lifecycle to detect anomalies and generate reports.
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Market Restraints
Because of the shortage of skilled workers, aging farmers, and declining interest among young people in farming as a career path, there has been an alarming decrease in global workforce numbers. As governments and private institutions strive to automate agriculture operations using artificial intelligence technology, this trend towards decreasing labor has caused alarmingly rapid increases.
Market Trends
The demand for robots has grown as agriculture stakeholders prioritize increasing productivity and reducing carbon footprints. Robotic companies offer products that can be applied in both structured and unstructured agricultural settings. Robots were originally developed with industrial production in mind, but technological advancements have allowed them to expand into other sectors like transport or healthcare. Furthermore, robotic systems are playing an increasingly important role in alleviating food scarcity; milking farms now use them too!
Regional Analysis
North America accounted for more than 39% of the global market in 2022 due to its dominant industrial automation industry and increasing adoption of artificial intelligence solutions. North America boasts a higher purchasing power, continued investments in automation, significant investments in IoT technology, and government initiatives toward in-house AI equipment manufacturing. Furthermore, many agricultural technology providers such as Deere & Company, Microsoft, Granular Inc., and The Climate Corporation are present on this front.
Over the forecast period, Asia Pacific is expected to witness the highest compound annual growth rate due to the increasing use of artificial intelligence technology in agriculture. China and India are two emerging economies that have already adopted artificial intelligence solutions such as remote monitoring technology or predictive analysis for food industry needs. Agribusiness companies are being encouraged to utilize AI-enabled services and solutions due to the growing demand for smart cities.
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Scope of the Report
| Report Attribute | Details |
| Market Value (2022) | USD 1.2 Billion |
| Market Size (2032) | USD 10.2 Billion |
| CAGR (from 2022 to 2032) | 24.5% |
| North America Revenue Share | 39% |
| Historic Period | 2016 to 2022 |
| Base Year | 2022 |
| Forecast Year | 2023 to 2032 |
Market Drivers
Every day, vast amounts of data are produced in both structured and unstructured formats. This includes historical weather patterns, soil reports, and new research. IoT solutions can detect all this information to create strong perceptions that increase yield. Remote Sensing uses intelligence data to combine it with soil analysis using subsurface soil in an area. Rowbot, combining data collection software with robotics technology, has already proven to be the best fertilizer for growing corn.
Market Challenges
AI in agriculture has many applications, yet there is a lack of awareness regarding high-tech machine-learning solutions in farms around the world. Adjusting farming to external factors such as weather patterns, soil conditions, and pest presence requires significant financial investment, while AI systems likewise need vast amounts of data in order to train machines and make accurate predictions.
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Report Segmentation of artificial intelligence (AI) in Agriculture Market
Technology Insight
The market can be segmented on technology into machine learning and deep learning, predictive analytics, and computer vision. Many agribusiness companies utilize predictive analytics to deploy artificial Intelligence; AgEagle Aerial Systems Inc., Microsoft, and Granular have all developed AI-enabled platforms and solutions for agriculture and farming that utilize this predictive analytics technology.
Application Insight
The market can be divided into four categories based on application: precision farming, drone analytics, and agriculture robots. Precision farming is expected to hold a dominant share during the forecast period due to its AI-enabled capabilities, which help farmers reduce costs and maximize resources.
AI is used in precision farming to collect, interpret and analyze digital data. GPS-equipped combines harvesters employ artificial intelligence to track harvest yields for field variability analysis - including differences in soil makeup and water. This analysis and prediction allow farmers to adjust fertilizers or pesticides accordingly. An AI system can control agriculture robots through artificial intelligence combined with field sensors and data analytics. They're effective for many applications, such as harvesting crops efficiently or wedding with ease. The segment of agriculture robots is being driven forward by the growing adoption of artificial intelligence technology along with advances in robotics technology.
Component Insight
The software industry is witnessing an uptick in the use of predictive analytics-based tools. Popular programs include the Watson Decision Platform from AI Sowing App for Microsoft, IBM Corporation, and See and Spray pesticide and insecticide distribution systems from Deere and Company. These artificial intelligence programs assist farmers with selecting when to plant crops; spotting crop diseases; tracking yield; as well as calculating land, fertilizers, and water requirements. AI technology has many potential uses, such as precision farming or drone analysis - further fuelling demand for software within this segment of the agricultural software market.
For more insights on the historical and Forecast Artificial Intelligence (Ai) In Agriculture Market data from 2016 to 2032 - download a sample report at https://market.us/report/artificial-intelligence-ai-in-agriculture-market/request-sample/
Market Segmentation
By Technology
- Machine Learning & Deep Learning
- Predictive Analytics
- Computer Vision
By Application
- Precision Farming
- Drone Analytics
- Agriculture Robots
- Livestock Monitoring
- Labor Management
- Agriculture Robots
- Other Applications
By Component
- Hardware
- Software
- Service
- AI-as-a-Service
By Geography
- North America
-
- The US
- Canada
- Mexico
- Western Europe
-
- Germany
- France
- The UK
- Spain
- Italy
- Portugal
- Ireland
- Austria
- Switzerland
- Benelux
- Nordic
- Rest of Western Europe
- Eastern Europe
-
- Russia
- Poland
- The Czech Republic
- Greece
- Rest of Eastern Europe
- APAC
-
- China
- Japan
- South Korea
- India
- Australia & New Zealand
- Indonesia
- Malaysia
- Philippines
- Singapore
- Thailand
- Vietnam
- Rest of APAC
- Latin America
-
- Brazil
- Colombia
- Chile
- Argentina
- Costa Rica
- Rest of Latin America
- Middle East & Africa
-
- Algeria
- Egypt
- Israel
- Kuwait
- Nigeria
- Saudi Arabia
- South Africa
- Turkey
- United Arab Emirates
- Rest of MEA
Competitive Landscape
Vendors offering artificial intelligence solutions to agriculture focus on growing their customer base to gain a competitive edge in the market. To do this, they often implement strategic initiatives like mergers and acquisitions as well as partnerships. Deere & Company recently joined Cultivating New Frontiers in Agriculture (CNFA) on May 26th to implement mechanization within their agriculture industry. Climate Corporation followed suit in October 2018 by joining forces with three agriculture tech firms: SoilOptix and AgCon Aerial Corp.; this collaboration allows farmers new capabilities while expanding Climate FieldView's digital platform further.
Some of the major players include:
- Raven Industries Inc.
- Farmers Edge Inc.
- Deere & Company
- A.A Taranis Visual Ltd.
- Gamaya SA
- AGCO Corporation
- Bayer AG
- IBM Corporation
- Ag Leader Technology
- Trimble Inc.
Recent Development of artificial intelligence (AI) in agriculture Market
- In May 2022, AGCO was acquired by JCA Industries to enhance its engineering and software development abilities, as well as expedite the production and deployment of autonomous and highly automated machines.
- In April 2022, Deere & Company created a joint venture in Kingsburg, Calif. with GUSS Automation to develop Global Unmanned Spray System--an industry leader for semi-autonomous sprayers used for vineyards and orchards alike.
- In March 2022, Raven's expansions of facilities in Arizona and South Dakota will likely drive up demand for Ag Tech, which is industry-leading.
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