Global AI in Agriculture Market Insights, Forecast to 2034
Published on: 2024-01-04 | No of Pages : 400 | Industry : Latest Trends
Publisher : MRA | Format : PDF
Global AI in Agriculture Market Insights, Forecast to 2034
Artificial intelligence (AI) is a program that can adapt itself to execute tasks in real-time situations using cognitive processing as the human mind. As the program can analyze and adapt itself to real-time situations, it does not require constant supervision. In the agriculture industry, on the basis of application, AI technology has been segmented into robotics, crop and soil management, and animal husbandry.
Market Analysis and InsightsGlobal AI in Agriculture Market
The global AI in Agriculture market is projected to grow from US$ 779.7 million in 2023 to US$ 1606 million by 2033, at a Compound Annual Growth Rate (CAGR) of 12.8% during the forecast period.
Based on technology, the AI in agriculture market has been classified into machine learning, computer vision, and predictive analytics. Machine learning held the largest market size owing to the growing adoption of this technology for various applications of agriculture such as precision farming, drone analytics, agriculture robots, and livestock monitoring.
Report Includes
This report presents an overview of global market for AI in Agriculture market size. Analyses of the global market trends, with historic market revenue data for 2018 - 2023, estimates for 2023, and projections of CAGR through 2033.
This report researches the key producers of AI in Agriculture, also provides the revenue of main regions and countries. Highlights of the upcoming market potential for AI in Agriculture, and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the AI in Agriculture revenue, market share and industry ranking of main companies, data from 2018 to 2023. Identification of the major stakeholders in the global AI in Agriculture market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by type and by application, revenue, and growth rate, from 2018 to 2033. Evaluation and forecast the market size for AI in Agriculture revenue, projected growth trends, production technology, application and end-user industry.
Descriptive company profiles of the major global players, including Ag Leader Technology, Trimble, John Deere, Iteris, AGCO, aWhere, Gamaya, Granular and Raven Industries, etc.
Ag Leader Technology
Trimble
John Deere
Iteris
AGCO
aWhere
Gamaya
Granular
Raven Industries
Prospera
Skysquirrel Technologies
Segment by Type
Machine Learning
Computer Vision
Predictive Analytics
Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East, Africa, and Latin America
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter 1Introduces the report scope of the report, executive summary of different market segments (product type, application, etc.), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2Revenue of AI in Agriculture in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world. This section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3Detailed analysis of AI in Agriculture companies’ competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 4Provides the analysis of various market segments by type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5Provides the analysis of various market segments by application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6North America by type, by application and by country, revenue for each segment.
Chapter 7Europe by type, by application and by country, revenue for each segment.
Chapter 8China by type and by application revenue for each segment.
Chapter 9Asia (excluding China) by type, by application and by region, revenue for each segment.
Chapter 10Middle East, Africa, and Latin America by type, by application and by country, revenue for each segment.
Chapter 11Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, AI in Agriculture revenue, gross margin, and recent development, etc.
Chapter 12Analyst's Viewpoints/Conclusions
Market Analysis and InsightsGlobal AI in Agriculture Market
The global AI in Agriculture market is projected to grow from US$ 779.7 million in 2023 to US$ 1606 million by 2033, at a Compound Annual Growth Rate (CAGR) of 12.8% during the forecast period.
Based on technology, the AI in agriculture market has been classified into machine learning, computer vision, and predictive analytics. Machine learning held the largest market size owing to the growing adoption of this technology for various applications of agriculture such as precision farming, drone analytics, agriculture robots, and livestock monitoring.
Report Includes
This report presents an overview of global market for AI in Agriculture market size. Analyses of the global market trends, with historic market revenue data for 2018 - 2023, estimates for 2023, and projections of CAGR through 2033.
This report researches the key producers of AI in Agriculture, also provides the revenue of main regions and countries. Highlights of the upcoming market potential for AI in Agriculture, and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the AI in Agriculture revenue, market share and industry ranking of main companies, data from 2018 to 2023. Identification of the major stakeholders in the global AI in Agriculture market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by type and by application, revenue, and growth rate, from 2018 to 2033. Evaluation and forecast the market size for AI in Agriculture revenue, projected growth trends, production technology, application and end-user industry.
Descriptive company profiles of the major global players, including Ag Leader Technology, Trimble, John Deere, Iteris, AGCO, aWhere, Gamaya, Granular and Raven Industries, etc.
By Company
Ag Leader Technology
Trimble
John Deere
Iteris
AGCO
aWhere
Gamaya
Granular
Raven Industries
Prospera
Skysquirrel Technologies
Segment by Type
Machine Learning
Computer Vision
Predictive Analytics
Segment by Application
Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East, Africa, and Latin America
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1Introduces the report scope of the report, executive summary of different market segments (product type, application, etc.), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2Revenue of AI in Agriculture in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world. This section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3Detailed analysis of AI in Agriculture companies’ competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 4Provides the analysis of various market segments by type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5Provides the analysis of various market segments by application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6North America by type, by application and by country, revenue for each segment.
Chapter 7Europe by type, by application and by country, revenue for each segment.
Chapter 8China by type and by application revenue for each segment.
Chapter 9Asia (excluding China) by type, by application and by region, revenue for each segment.
Chapter 10Middle East, Africa, and Latin America by type, by application and by country, revenue for each segment.
Chapter 11Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, AI in Agriculture revenue, gross margin, and recent development, etc.
Chapter 12Analyst's Viewpoints/Conclusions