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WASHINGTON, Feb. 02, 2023 (GLOBE NEWSWIRE) — Vantage Market Research analyses that the Artificial Intelligence (Al) in Agriculture Market is expected to reach $ 4.2 Billion by 2028, which is $ 1.1 Billion in 2022, at a CAGR of 25.1% during the forecast period.
Vantage Market Research has recently published comprehensive business research on Artificial Intelligence in Agriculture Market including historic data, present market trends, future product environment, marketing strategies, technological innovation, upcoming technologies, emerging trends or opportunities, and the technical progress in the related industry. Al in Agriculture Market research report gives critical information about the market and business landscape. It suggests how the company is perceived by the target customers and clients that are desired to reach. The report helps us understand how to connect with customers, how to stack up against the competition, and how to plan the next steps. It plays an important role in the process of developing products and services, bringing them to the marketplace, and marketing them to consumers. For many businesses, Artificial Intelligence in Agriculture Market report acts as a key component in developing marketing strategy by providing a fact-based foundation for estimating sales and profitability.
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Al in Agriculture Market Overview
According to Vantage Market Research, some of the key factors anticipated acceleratingthe Al in agriculturemarket growth over the forecast period.The rise in the market for agriculture-related artificial intelligence can be attributed to the expanding use of information management systems and cutting-edge technologies for increasing agricultural yield using deep learning techniques. To meet the growing demand for food on a global scale, increased agricultural output is also necessary.
We forecast that the machine learning category in Al in agriculturemarketsales will account for more than 30% of total sales by 2028. To increase farm productivity and gain a competitive edge in business operations, agricultural organizations and farmers worldwide are embracing machine learning-enabled solutions in significant numbers. The use of machine learning in various agricultural practices is anticipated to grow rapidly in the upcoming years.
North America dominates Al in the agriculture market, and this trend of dominance will continue throughout the projection period. The market is anticipated to expand further due to the region’s booming artificial intelligence market and top-tier industrial automation industry. North America is characterized by its expanding purchasing power, ongoing automation, significant IoT investments, and growing government focus on developing domestic A.I. equipment.
Top Players in the Global Al in Agriculture Market
- I.B.M. Corporation (U.S.)
- Microsoft Corporation (U.S.)
- Bayer AG (Germany)
- Google L.L.C. (U.S.)
- John Deere & Company (U.S.)
- A.A.A Taranis Visual Ltd. (Israel)
- AgEagle Aerial Systems Ltd. (U.S.)
- Gamaya SA (Switzerland)
- AGCO Corporation (US)
- A.G. Leader Technology (U.S.)
- Trimble Inc. (U.S.)
- Granular Inc. (U.S.)
- Raven Industries Inc. (U.S.)
For Additional Information on Al in Agriculture Market Players and Detail List, Download a Report PDF Brochure
Increased Use of Smart Sensors in Agriculture:
The rising usage of smart sensors in agriculture is a key trend in the A.I. in the agriculture market. Thanks to sensor-based technology, farmers can precisely map their fields, track crop treatment items, and administer them where needed. Farmers gain from the development of various operations explicit sensors, including soil moisture sensors, position sensors, airflow sensors, and weather sensors, which help them monitor and maximize their yields while also allowing them to adjust to changing environmental factors.
Shortage of Labour:
For several reasons, there has been a dramatic decrease in the workforce worldwide. Automated agricultural operations are emerging due to this decline, linked to a lack of skilled workers, elderly farmers, and young people’s disinterest in farming as a profession. As a result, governmental and private institutions are being driven by the trend of a declining workforce in agriculture to focus on automating operations by using artificial intelligence technologies in the industry.
Increased Adoption of Agricultural Drones:
Drones with hyperspectral, multispectral, or thermal sensors can spot locations that need their irrigation schedules changed. Once crops have begun to grow, these sensors may use the heat signature of the crop to generate the vegetation index, an AI-based indication of health. Although chemical spraying is unpopular, it is a necessary component of industrial agriculture. Fortunately, intelligent farming drones are minimizing their negative environmental effects. Sprayers and other specialized UAV (Unmanned Aerial Vehicle) technology, including lasers and ultrasonic echoing devices, can measure distance with extreme precision. As a result, there is a significant decrease in the overall amount of spray and chemicals that enter the groundwater.
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- May 2022: AGCO acquired JCA Industries to increase engineering and software development capabilities and to accelerate the development of highly automated and autonomous machines.
- April 2022: Deere & Company and GUSS Automation formed a joint venture with an LLC in Kingsburg, Calif. Global Unmanned Spray System (GUSS) is a pioneer in semi-autonomous sprayers for orchards and vineyards.
- March 2022: As demand for industry-leading Ag Tech accelerates, Raven’s facilities expansions in Arizona and South Dakota are likely to enhance the development in AI, autonomy, Machine Learning, and core technology.
Top Trends in Global Al in agriculture Market
- One trend that Vantage Market Research (V.M.R.) expects to see in the Al in the agriculture industryis yield production. A further area in which A.I. can benefit farmers is yield prediction. Artificial intelligence algorithms can forecast future yields for farmers by examining previous data and the current environment. Farmers who plan their production with the aid of this knowledge can make sure they have the right resources available when they’re needed.
- Another trend that V.M.R. predicts will continue in the Al agriculture industryis rising precision farming. Precision farming is a method of farming that uses cutting-edge technology to maximize harvests. This entails using sensors and data analysis to understand better and manage crops, soil, water, and other resources. Precision farming is greatly aided by artificial intelligence (A.I.), which may provide farmers access to real-time data about their crops and fields.
Top Report Findings
- Based on type, most of the Al in the agricultureMarket’s revenue is controlled by the product category.A significant portion is anticipated to be allocated for agricultural input/output software (AISO) providers in the products, which is dominated by machine learning for crop scouting and yield prediction.
- Based on technology, the machine learning category dominated Al in the agriculture market, and this trend is anticipated to continue. Agricultural organizations and farmers widely use machine learning-enabled solutions worldwide to increase farm production and gain a competitive edge in market operations.
- Based on application, the precision farmingcategory dominated Al in the agriculture market, and this trend is anticipated to continue. Due to the growing demand for optimum yield from the limited resources available and for lowering crop production costs, the precision farming technique is becoming more and more well-known among farmers.
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Machine LearningCategory inAl in Agriculture Market to Generate Over 30% Revenue
Al in agriculture is an expensive investment. Vantage Market Research has analyzed the market for Al in agriculture to understand its current state and potential future growth factors. For better understanding, based on technologyAl in agriculturemarketis divided into:machine learning, predictive&analytics and computer vision.
During the forecast period, the market for Al in agriculture is anticipated to experience the highest CAGR for the machine learningcategory. Machine learning is pervasive throughout the entire growing and harvesting cycle. A seed is planted in the ground, the soil is prepared, seeds are bred, water feed is measured, and the harvest is picked up by robots that use computer vision to assess ripeness.
On the other hand, the predictive& analyticscategory is anticipated to grow significantly over the forecast period.Predictive analytics is one of the most intriguing technologies being utilised, modified, and developed right now. Predictive &analytics comprise numerous statistical methods, including modeling, machine learning, and data mining.
Browse market data Tables and Figures spread through 145 Pages and in-depth TOC on Al in Agriculture Market Forecast Report (2022-2028).
Global Al in Agriculture Market Segmentation
- Machine Learning
- Predictive Analytics
- Computer Vision
- Precision Farming
- Agricultural Robots
- Livestock Monitoring
- Drone Analytics
- North America
- Asia Pacific
- Latin America
- Middle East & Africa
Scope of the Report:
|Market Size in 2021||USD 1.1 Billion|
|Revenue Forecast by 2028||USD 4.2 Billion|
|CAGR||25.1% from 2022 to 2028|
|Forecast Year||2022 to 2028|
|Key Players||IBM Corporation, Microsoft Corporation, Bayer AG, Google LLC, John Deere & Company, A.A.A Taranis Visual Ltd., AgEagle Aerial Systems Ltd., Gamaya SA, AGCO Corporation, AG Leader Technology, Trimble Inc., Granular Inc., Raven Industries Inc.|
|Customization Options||Customized purchase options are available to meet any research needs. Explore customized purchase options|
- Europe is estimated to account for the largest market growth due to their farmers manage almost half of the land area for agriculture and it makes dominant industry in Europe. Trend in observing and reporting utensils for indoor and outdoor farms, and delivering a visualization of the farmer’s intact production using computer vision and AI are increasing the AI market in agriculture. The European Soil Data Centre (ESDAC) is the thematic center for soil associated data in Europe, where its goal is to be the single reference point for and to host all appropriate soil data and statistics at European level. AI firms are handling ‘Internet of the Soil’, which is a software and hardware solution for observing soil conditions like humidity, temperature, electrical conductivity, and more in European countries.
- North America region dominates the artificial intelligence (AI) in agriculture market and will continue to flourish its trend of dominance during the forecast period. This is because of the increasing expenditure for research and development proficiencies in this region and strong dominance in artificial intelligence in this region. Asia-Pacific region is projected to undergo substantial during the forecast period and will score the highest CAGR owing to the surging adoption of connected devices technology by the agricultural industry.
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