Global Artificial Intelligence (AI) in Agriculture Market Size, Status and Forecast 2019-2025

SKU ID : QYR-13916582 | Publishing Date : 04-Mar-2019 | No. of pages : 102

Artificial Intelligence (AI) in Agriculture Market size is being driven by the growing adoption of the robots in agriculture. Increasing consumption and rising requirement of better yield of crops are estimated to be one of the major factors that is fueling the demand of robots in agriculture. Increasing consumption motivates farmers to scale up farming operations and give rise to the requirement of automating farming operations. As the farmers are shifting more towards automation, drones and robots have become integral part of agriculture farms and are enhancing yield and improving the product quality. Since AI is the backbone of robotics, increasing adoption of robots in agriculture is estimated to drive the AI in agriculture market growth.
United States is the largest consumption countries of Artificial Intelligence (AI) in Agriculture in the world in the past few years and it will keep leader position in the next few years. United States market took up about 42.96% the global market in 2017, while Europe was about 22.67%.
USA is now the key developers of Artificial Intelligence (AI) in Agriculture; most companies are in USA. Others are in Europe, China and India.
In 2018, the global Artificial Intelligence (AI) in Agriculture market size was 240 million US$ and it is expected to reach 1100 million US$ by the end of 2025, with a CAGR of 20.8% during 2019-2025.

This report focuses on the global Artificial Intelligence (AI) in Agriculture status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Artificial Intelligence (AI) in Agriculture development in United States, Europe and China.

The key players covered in this study
IBM
Intel
Microsoft
SAP
Agribotix
The Climate Corporation
Mavrx
aWhere
Precision Hawk
Granular
Prospera Technologies
Spensa Technologies
Resson
Vision Robotics
Harvest Croo Robotics
CropX
John Deere
Gamaya
Cainthus

Market segment by Type, the product can be split into
Machine Learning
Computer Vision
Predictive Analytics

Market segment by Application, split into
Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others

Market segment by Regions/Countries, this report covers
United States
Europe
China
Japan
Southeast Asia
India
Central & South America

The study objectives of this report are:
To analyze global Artificial Intelligence (AI) in Agriculture status, future forecast, growth opportunity, key market and key players.
To present the Artificial Intelligence (AI) in Agriculture development in United States, Europe and China.
To strategically profile the key players and comprehensively analyze their development plan and strategies.
To define, describe and forecast the market by product type, market and key regions.

In this study, the years considered to estimate the market size of Artificial Intelligence (AI) in Agriculture are as follows:
History Year: 2014-2018
Base Year: 2018
Estimated Year: 2019
Forecast Year 2019 to 2025
For the data information by region, company, type and application, 2018 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.

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.
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