The global Artificial Intelligence in Agriculture Market research report provides complete insights on industry scope, trends, regional estimates, key application, competitive landscape and financial performance of prominent players. It also offers ready data-driven answers to several industry-level questions. This study enables numerous opportunities for the market players to invest in research and development.
The global artificial intelligence in agriculture market size is estimated to reach USD 2.9 billion, by 2025 and is projected to grow at a CAGR of 25.4% over the forecast period 2019 to 2025, according to a new report by Million Insights. Artificial intelligence solutions are used in different forms for agricultural farming which include crop & soil monitoring, predictive analytics and agricultural robots.
- IBM Corporation
- Deere & Company
- AgEagle Aerial Systems Inc.
- The Climate Corporation
- Descartes Labs
- Prospera Technologies
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Agribusinesses use AI-enabled sensors to monitor soil and crop productivity. AI solutions process analytical data for better farming, which is expected to increase the demand for these solutions in the next few years.
Rising population across the globe is also contributing to the growth of artificial intelligence technologies in the agricultural industry. It is projected that the world’s population would reach around 9.8 billion by the end of 2050. Artificial intelligence improves farming efficiency and crop productivity. For example, Microsoft has developed a Sowing App, which gives the best advice to farmers for better crop sowing. Moreover, it helps farmers to keep track of weather conditions as well and harvest crops according to the situation.
- Machine Learning & Deep Learning
- Predictive Analytics
- Computer Vision
- Precision Farming
- Drone Analytics
- Agriculture Robots
- Livestock Monitoring
Asia Pacific is projected to expand at a significant rate from 2019 to 2025. This growth is contributed to the growing trend of AI-enabled devices in agribusiness in the region. In the developing countries such as China and India, computer vision and machine learning applications have been growing from the past few years, which in turn, are expected to boost the crop yield capacity in the agriculture sector. Moreover, supportive government regulations are encouraging farmers to seek for these new technologies. For example, in 2019 the Indian government has started using artificial intelligence solutions for estimating crop yield and increasing farming productivity.
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