NEW YORK, Aug. 24, 2020 /PRNewswire/ -- For enhanced agricultural production, farmers are increasingly adopting tools that help them monitor their livestock. As a result, the global AI in agriculture market size is expected to register an explosive 24.8% CAGR between 2020 and 2030. At this rate, the market size would rise from $852.2 million in 2019 to $8,379.5 million in 2030. With the growing population and its surging disposable income, the demand for milk, wool, eggs, and meat is increasing.
This is helping in the advance of the AI in agriculture market, as farmers are now using numerous AI-driven livestock facial recognition, image classification, and feeding pattern tracking solutions. By monitoring the animals' facial features, hide patterns, food and water intake, as well as behavior and temperature, with the help of AI, dairy farmers are able to keep track of their livestock's health and look for diseases before severe symptoms appear.
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Due to the COVID-19 pandemic, the AI in agriculture market growth has slowed, on account of the reducing demand for produce. This is, in turn, is expected to lower the rate of technology adoption by the agrarian community, in order to check the expenditure. Moreover, the supply of agricultural goods to customers has been hit by the prevailing lockdown situation, thereby leading to a lower income for farmers. Similarly, the agrarian community hasn't been able to procure the physical systems part of AI in agricultural solutions.
Browse report overview with detailed TOC on AI in Agriculture Market Research Report: By Type (Product, Service), Technology (Machine Learning, Predictive Analytics, Computer Vision), Application (Precision Farming, Agricultural Robots, Livestock Monitoring, Drone Analytics) - Global Industry Analysis and Growth Forecast to 2030 @ https://www.psmarketresearch.com/market-analysis/artificial-intelligence-in-agriculture-market
In the coming years, the highest CAGR in the AI in agriculture market, of 26.9%, under the application segment, is projected to be witnessed in the drone analytics classification. The demand for better-quality food crops is rising, which is resulting in a rising funding for the adoption of drones in agricultural fields. The growing agricultural sector of Latin America (LATAM) and Asia-Pacific (APAC) is predicted to propel the demand for AI-driven drone analytics solutions for agriculture.
Presently, North America generates the highest revenue for the AI in agriculture market, due to the early integration of new technologies, such as computer vision and ML, for livestock management, precision farming, soil management, greenhouse management, and other agricultural purposes in the region. Additionally, the agrarian community is combining the computer vision technology with the internet of things (IoT), thereby driving the regional industry.
In the years to come, the fastest growth in the AI in agriculture market will be observed in APAC, owing to the rising adoption of agricultural robots and drone analytics and precision farming technologies, primarily in China, India, Thailand, and Indonesia. In addition, the increasing awareness of these advanced technologies and government support for their adoption would further increase the uptake of artificial intelligence solutions in the regional agricultural sector.
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Mergers and Acquisitions Driving Competition in Industry
In an effort to edge out their competitors, companies in the AI in agriculture market are engaging in mergers and acquisitions, with the intention to:
- Develop autonomous solutions for precision agriculture
- Provide better logistics solutions to agricultural retailers, custom applicators, and enterprise farms
- Enhance their service offerings with data analytics platforms
- Expand their product portfolio
- Increase the manageable area on their precision agricultural platforms
The major players in the global AI in agriculture market are Microsoft Corporation, IBM Corporation, Deere & Company, Bayer AG, AgEagle Aerial Systems Inc., A.A.A Taranis Visual Ltd., Raven Industries Inc., AGCO Corporation, Trimble Inc., Ag Leader Technology, Granular Inc., Google LLC, and Gamaya SA.
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