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This report contains market size and forecasts of AI in Agriculture in United States, including the following market information:
United States AI in Agriculture Market Revenue, 2016-2021, 2022-2027, ($ millions)
United States top five AI in Agriculture companies in 2020 (%)
The global AI in Agriculture market size is expected to growth from US$ 672 million in 2020 to US$ 1606 million by 2027; it is expected to grow at a CAGR of 12.8% during 2021-2027.
The United States AI in Agriculture market was valued at US$ XX million in 2020 and is projected to reach US$ XX million by 2027, at a CAGR of XX% during the forecast period.
QYResearch has surveyed the AI in Agriculture Companies and industry experts on this industry, involving the revenue, demand, product type, recent developments and plans, industry trends, drivers, challenges, obstacles, and potential risks.
Total Market by Segment:
United States AI in Agriculture Market,
United States AI in Agriculture Market Segment Percentages,
Machine Learning
Computer Vision
Predictive Analytics
United States AI in Agriculture Market,
United States AI in Agriculture Market Segment Percentages,
Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others
Competitor Analysis
The report also provides analysis of leading market participants including:
Key companies AI in Agriculture revenues in United States market, 2016-2021 (Estimated), ($ millions)
Key companies AI in Agriculture revenues share in United States market, 2020 (%)
Further, the report presents profiles of competitors in the market, key players include:
Ag Leader Technology
Trimble
John Deere
Iteris
AGCO
aWhere
Gamaya
Granular
Raven Industries
Prospera
Skysquirrel Technologies
United States AI in Agriculture Market Revenue, 2016-2021, 2022-2027, ($ millions)
United States top five AI in Agriculture companies in 2020 (%)
The global AI in Agriculture market size is expected to growth from US$ 672 million in 2020 to US$ 1606 million by 2027; it is expected to grow at a CAGR of 12.8% during 2021-2027.
The United States AI in Agriculture market was valued at US$ XX million in 2020 and is projected to reach US$ XX million by 2027, at a CAGR of XX% during the forecast period.
QYResearch has surveyed the AI in Agriculture Companies and industry experts on this industry, involving the revenue, demand, product type, recent developments and plans, industry trends, drivers, challenges, obstacles, and potential risks.
Total Market by Segment:
United States AI in Agriculture Market,
By Type
, 2016-2021, 2022-2027 ($ Millions)United States AI in Agriculture Market Segment Percentages,
By Type
, 2020 (%)Machine Learning
Computer Vision
Predictive Analytics
United States AI in Agriculture Market,
By Application
, 2016-2021, 2022-2027 ($ Millions)United States AI in Agriculture Market Segment Percentages,
By Application
, 2020 (%)Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others
Competitor Analysis
The report also provides analysis of leading market participants including:
Key companies AI in Agriculture revenues in United States market, 2016-2021 (Estimated), ($ millions)
Key companies AI in Agriculture revenues share in United States market, 2020 (%)
Further, the report presents profiles of competitors in the market, key players include:
Ag Leader Technology
Trimble
John Deere
Iteris
AGCO
aWhere
Gamaya
Granular
Raven Industries
Prospera
Skysquirrel Technologies
Frequently Asked Questions
This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.
- By product type
- By End User/Applications
- By Technology
- By Region
The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.
