[225+ Pages Updated Research Report] According to the recent research report; the global AI in Agriculture Market in 2020 was approximately USD 1,002.02 Million. The market is expected to surge at a CAGR of 25.2% and is anticipated to surpass USD 3,984.5 Million by 2026. Top market players in the market are AgEagle Aerial Systems Inc., GAMAYA, Deere & Company, Descartes Labs, Inc., ec2ce, Microsoft, IBM Corporation, Granular, Inc. and others.
New York, NY, April 27, 2021 (GLOBE NEWSWIRE) -- Facts and Factors have published a new research report titled “AI in Agriculture Market By Component (Hardware, and Software) By Technology (Predictive Analytics, Machine Learning & Deep Learning, and Computer Vision), By Application (Drone Analytics, Livestock Monitoring, Precision Farming, Agriculture Robots, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2021 – 2026”.
“According to the research report, the global AI in Agriculture Market was estimated at USD 1,002.02 Million in 2020 and is expected to reach USD 3,984.5 Million by 2026. The global AI in Agriculture Market is expected to grow at a compound annual growth rate (CAGR) of 25.2% from 2019 to 2026”.
AI in Agriculture Market: Key Market Insights Overview
Farming techniques that use artificial intelligence can help increase growth and quality. As a result, agribusiness companies are embracing artificial intelligence in the form of predictive analytics-based solutions. In the entire food supply chain, AI-based applications and technologies help manage pests, produce healthier crops, track the soil, and enhance agriculture-related tasks. Since it aids in the analysis of farm data, artificial intelligence is increasingly being used in the agriculture industry to increase harvest quality and accuracy. The need for AI in agriculture is being driven by the world's rapidly rising population. The need for a green revolution powered by artificial intelligence, the Internet of Things (IoT), and data analytics is driven by limited arable land supply and the need for increasing agricultural productivity for food security. Predictive and recommendation analytics, recognizing plant diseases, detecting insect infestations, and soil monitoring are all areas where AI-enabled applications can help in the agriculture industry.
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Our Free Sample Report Includes:
2020 Updated Report Introduction, Overview, and In-depth industry analysis
COVID-19 Pandemic Outbreak Impact Analysis Included
225+ Pages Research Report (Inclusion of Updated Research)
Provide Chapter-wise guidance on Request
2020 Updated Regional Analysis with Graphical Representation of Size, Share & Trends
Includes Updated List of table & figures
Updated Report Includes Top Market Players with their Business Strategy, Sales Volume, and Revenue Analysis
Facts and Factors research methodology
(Note: The sample of this report is updated with COVID-19 impact analysis before delivery)
Key Questions Answered in this Report
1) What were the pre and post-business impacts of COVID-19 on the AI in Agriculture Market?
2) What is the market size, share of AI in Agriculture Market?
3) Who are the top market players in AI in Agriculture Market?
4) What will be the future market of AI in Agriculture Market?
5) How AI is used in agriculture?
6) How much is the AI industry worth?
Market Size & Forecast by Revenue | 2020−2026
Market Dynamics – Leading trends, growth drivers, restraints, and investment opportunities
Market Segmentation – A detailed analysis by product, by types, end-user, applications, segments, and geography
Competitive Landscape – Top key vendors and other prominent vendors
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AI in Agriculture Market: Industry Major Market Players
AgEagle Aerial Systems Inc.
Deere & Company
Descartes Labs Inc.
Tule Technologies Inc.
The Climate Corporation
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Artificial Intelligence in agriculture has a wide range of applications, including agricultural automatons, face recognition, computerized water system systems, and autonomous vehicle tractors. These applications are carried out in conjunction with a variety of AI-based sensors, GPS systems, radars, and other cutting-edge devices.
The factors propelling the global of the AI in agriculture market include increased implementation of innovative technological advancements and IMS, increased demand for agricultural production, and government initiatives to adopt modern agricultural techniques. Drone use on farms is becoming more common, which presents an opportunity. The high cost of collecting precise field data is limiting AI's use in agriculture. One of the problems facing the AI in agriculture sector is a lack of standardization.
According to technology, the predictive analytics segment in the AI in agriculture market is expected to grow at the fastest rate during the forecast period. This is due to the agrarian community's growing demand for advanced analytics solutions, which analyze actual weather conditions, moisture levels of soil, and plant health and provide deep information to improve production and crop quality.
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COVID-19 Impact Analysis
The demand for agricultural products is projected to fall in FY 2020 as a result of COVID-19. This will also mean that technical advances in the industry would be less widely implemented, resulting in slower business growth. This is primarily due to the downturn in economic development, low spending on agricultural products, and the existing global lockout condition, which has resulted in food supply chain disruptions.
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Smart Sensors Are Becoming More Popular in Agricultural Fields
A main trend in the AI in agriculture market is the increased use of smart sensors in agriculture. Farmers can now precisely map their fields and track and apply crop treatment products only to the areas that need it due to sensor-based technology. Farmers are benefiting from the production of various operations explicit sensors, such as soil moisture sensors, airflow sensors, position sensors, and weather sensors, which are assisting them in effectively tracking and maximizing their yield as well as adapting to changing environmental factors.
Drones are becoming increasingly popular in the agricultural industry.
Drones are being used more and more to track crop health and development. Drones are used to scan soil health, assist with irrigation schedules, estimate yield data, and apply fertilizers, among other things. The demand for drones in agriculture is rising year over year as a result of numerous government initiatives aimed at modernizing agricultural practices through the use of drones. For example, the state government of India partnered with the World Economic Forum in January 2019 to increase agricultural yield in the state by collecting data from agricultural farms using drones. As a result, the AI in agriculture market is being driven by the growing demand for drones in agricultural fields.
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In the AI in Agriculture market, North America produced the most revenue
During the historical period, North America held the largest the AI in agriculture industry, and it is projected to continue to lead the global market in terms of revenue during the forecast period. This is due in large part to the early implementation of innovations like machine learning and computer vision for agricultural applications such as precision farming, livestock management, cultivation management, and soil management. Furthermore, with the growing adoption of technologies such as IoT in conjunction with computer vision in agriculture, the market is expected to expand positively over the forecast period.
Over the forecast period, the Asia Pacific market is projected to grow at the fastest pace. Its rise can be due to the growing use of artificial intelligence in agriculture. In the food industry, emerging economies such as India and China are leveraging artificial intelligence technologies such as remote monitoring tech and predictive analysis. Furthermore, in these economies, the growing demand for smart cities is prompting agribusiness companies to implement AI-based solutions and services.
Furthermore, some regional players are partnering with other leading players to provide services to regional consumers. Companies like IBM Corporation and Raven Industries Inc. are constantly partnering with other players in the agriculture industry to improve their offerings. Raven Industries Inc., for example, teamed up with Farmers Edge Inc., a manufacturer of precision digital solutions, to create a new precision agriculture technology in 2020. As a result of the growing use of AI in agriculture to provide advanced analytical perspectives to farmers, the market in the area is expanding. In the coming years, APAC is expected to see the fastest growth in demand for AI-enabled agricultural solutions. The high widespread adoption of AI in the agriculture sector in significant countries like China, India, Japan, and Australia is largely responsible for the development.
Browse the full “AI in Agriculture Market By Component (Hardware, and Software) By Technology (Predictive Analytics, Machine Learning & Deep Learning, and Computer Vision), By Application (Drone Analytics, Livestock Monitoring, Precision Farming, Agriculture Robots, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2021 – 2026” report at https://www.fnfresearch.com/global-ai-in-agriculture-market-by-technology-machine-1122.
The global AI in Agriculture market is segmented as follows:
Machine Learning & Deep Learning
Smart Agriculture Market: https://www.fnfresearch.com/smart-agriculture-market-by-agriculture-type-precision-farming-213
Agriculture IoT Market: https://www.fnfresearch.com/global-agriculture-iot-market-by-offering-software-services
Agricultural Adjuvants Market: https://www.fnfresearch.com/global-agricultural-adjuvants-market-by-function-activator-adjuvants
Agriculture Sprayers Market: https://www.fnfresearch.com/global-agriculture-sprayers-market-global-agriculture-sprayers-market
Precision Farming Market: https://www.fnfresearch.com/precision-farming-market
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