The North America Artificial Intelligence in Agriculture Market should witness market growth of 22.7% CAGR during the forecast period (2022-2028).
To develop crop metrics across thousands of acres, remote sensing techniques, hyperspectral photography, and 3D laser scanning are essential. It can potentially bring about a fundamental shift in how farmers view agriculture from a time and effort perspective. Additionally, this technology will be used to track crops throughout their existence, producing reports in the event of anomalies. Irrigation is a farming operation requiring a lot of human labor. Automation of irrigation can increase total yield when machines are taught about past weather patterns, the quality of the soil, and the kind of crops that will be planted.
Both in terms of agricultural goods and field farming practices, AI and machine learning (ML) are being quickly incorporated into agriculture. Since it can comprehend, pick up on, and react to various situations with increased effectiveness, intellectual computing, in particular, is poised to become the most disruptive technology in the farm service sector. All farmers will benefit from having access to some of these solutions, such as a chatbot or other conversational platform, if it enables them to keep up with technological advancements and implement them into their daily agricultural practices.
The region has witnessed a rise in government incentives for the use of cutting-edge agricultural technologies, as well as an improvement in infrastructure. The National Institute of Food and Agriculture (NIFA), a division of the United States Department of Agriculture, implements geospatial, sensor, and precision technology projects in an effort to educate farmers. In addition, NIFA collaborates with Land-Grand universities to aid farmers in developing robust sensors, software, and tools for modelling, monitoring, and assessing a vast array of complex biological materials and processes. These elements are projected to stimulate the regional market for artificial intelligence in agriculture.
The US market dominated the North America Artificial Intelligence in Agriculture Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $1,287.9 million by 2028. The Canada market is poised to grow at a CAGR of 25.5% during (2022-2028). Additionally, The Mexico market should witness a CAGR of 24.4% during (2022-2028).
Based on Technology, the market is segmented into Machine Learning, Computer Vision and Predictive Analytics. Based on Application, the market is segmented into Drone Analytics, Precision Farming, Agricultural Robots, Labor Management, Livestock Monitoring and Others. Based on Offering, the market is segmented into Software, Hardware, AI-as-a-Service and Service. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Deere & Company, IBM Corporation, Microsoft Corporation, Climate LLC (Bayer AG), Farmers Edge Inc, AgEagle Aerial Systems, Inc., Prospera Technologies, Inc. (Valmont Industries, Inc.), A.A.A Taranis Visual Ltd., CropIn Technology Solutions Private Limited, and Corteva, Inc. (Dow AgroSciences LLC).
To develop crop metrics across thousands of acres, remote sensing techniques, hyperspectral photography, and 3D laser scanning are essential. It can potentially bring about a fundamental shift in how farmers view agriculture from a time and effort perspective. Additionally, this technology will be used to track crops throughout their existence, producing reports in the event of anomalies. Irrigation is a farming operation requiring a lot of human labor. Automation of irrigation can increase total yield when machines are taught about past weather patterns, the quality of the soil, and the kind of crops that will be planted.
Both in terms of agricultural goods and field farming practices, AI and machine learning (ML) are being quickly incorporated into agriculture. Since it can comprehend, pick up on, and react to various situations with increased effectiveness, intellectual computing, in particular, is poised to become the most disruptive technology in the farm service sector. All farmers will benefit from having access to some of these solutions, such as a chatbot or other conversational platform, if it enables them to keep up with technological advancements and implement them into their daily agricultural practices.
The region has witnessed a rise in government incentives for the use of cutting-edge agricultural technologies, as well as an improvement in infrastructure. The National Institute of Food and Agriculture (NIFA), a division of the United States Department of Agriculture, implements geospatial, sensor, and precision technology projects in an effort to educate farmers. In addition, NIFA collaborates with Land-Grand universities to aid farmers in developing robust sensors, software, and tools for modelling, monitoring, and assessing a vast array of complex biological materials and processes. These elements are projected to stimulate the regional market for artificial intelligence in agriculture.
The US market dominated the North America Artificial Intelligence in Agriculture Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $1,287.9 million by 2028. The Canada market is poised to grow at a CAGR of 25.5% during (2022-2028). Additionally, The Mexico market should witness a CAGR of 24.4% during (2022-2028).
Based on Technology, the market is segmented into Machine Learning, Computer Vision and Predictive Analytics. Based on Application, the market is segmented into Drone Analytics, Precision Farming, Agricultural Robots, Labor Management, Livestock Monitoring and Others. Based on Offering, the market is segmented into Software, Hardware, AI-as-a-Service and Service. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Deere & Company, IBM Corporation, Microsoft Corporation, Climate LLC (Bayer AG), Farmers Edge Inc, AgEagle Aerial Systems, Inc., Prospera Technologies, Inc. (Valmont Industries, Inc.), A.A.A Taranis Visual Ltd., CropIn Technology Solutions Private Limited, and Corteva, Inc. (Dow AgroSciences LLC).
Scope of the Study
By Technology
- Machine Learning
- Computer Vision
- Predictive Analytics
By Application
- Drone Analytics
- Precision Farming
- Agricultural Robots
- Labor Management
- Livestock Monitoring
- Others
By Offering
- Software
- Hardware
- AI-as-a-Service
- Service
By Country
- US
- Canada
- Mexico
- Rest of North America
Key Market Players
List of Companies Profiled in the Report:
- Deere & Company
- IBM Corporation
- Microsoft Corporation
- Climate LLC (Bayer AG)
- Farmers Edge Inc
- AgEagle Aerial Systems, Inc.
- Prospera Technologies, Inc. (Valmont Industries, Inc.)
- A.A.A Taranis Visual Ltd.
- CropIn Technology Solutions Private Limited
- Corteva, Inc. (Dow AgroSciences LLC)
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Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. Competition Analysis - Global
Chapter 4. North America Artificial Intelligence in Agriculture Market by Technology
Chapter 5. North America Artificial Intelligence in Agriculture Market by Application
Chapter 6. North America Artificial Intelligence in Agriculture Market by Offering
Chapter 7. North America Artificial Intelligence in Agriculture Market by Country
Chapter 8. Company Profiles
Companies Mentioned
- Deere & Company
- IBM Corporation
- Microsoft Corporation
- Climate LLC (Bayer AG)
- Farmers Edge Inc
- AgEagle Aerial Systems, Inc.
- Prospera Technologies, Inc. (Valmont Industries, Inc.)
- A.A.A Taranis Visual Ltd.
- CropIn Technology Solutions Private Limited
- Corteva, Inc. (Dow AgroSciences LLC)
Methodology
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About the Market
The Agriculture AI market is a rapidly growing sector of the agriculture industry, focused on the use of artificial intelligence (AI) to improve the efficiency and productivity of agricultural operations. AI-based solutions are used to automate processes, optimize crop yields, and reduce costs. AI-based solutions can also be used to monitor and analyze crop health, soil conditions, and weather patterns, allowing farmers to make informed decisions about their crops. Additionally, AI-based solutions Read more
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