Artificial Intelligence (AI) Market in Agriculture Market Precise Outlook- Microsoft Corporation, IBM Corporation, Granular Inc., aWhere Inc

This report discusses many vital industry facets that influence Global Artificial Intelligence (AI) Market in Agriculture  industry acutely which includes extensive study of competitive edge, latest advancements, region-wise industry environment, contemporary market and manufacturing trends, leading market contenders, and current consumption tendency of the end user. The report also oversees market size, market share, growth rate, revenue, and CAGR reported previously along with its forecast estimation. The impact of the COVID-19, and also forecasts its recovery post-COVID-19. The report also presents forecasts for Sodium-ion Battery investments from 2021 till 2026.

The Artificial Intelligence (AI) Market in Agriculture was valued at USD 766.41 million in 2020 and is expected to reach USD 2468.02 million by 2026, at a CAGR of 21.52% over the forecast period 2021 - 2026.

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The report also presents the market competition landscape and a corresponding detailed analysis of the major vendors/manufacturers in the market. The key manufacturers covered in this report: Microsoft Corporation, IBM Corporation, Granular Inc., aWhere Inc., Prospera Technologies Ltd., Gamaya SA, ec2ce, PrecisionHawk Inc., Cainthus Corp., Tule Technologies Inc.

Regional and Country-level Analysis

The report offers an exhaustive geographical analysis of the global Artificial Intelligence (AI) Market in Agriculture market, covering important regions, viz, North America, Europe, China, and Japan. It also covers key countries (regions), viz, U.S., Canada, Germany, France, U.K., Italy, Russia, China, Japan, South Korea, India, Australia, Taiwan, Indonesia, Thailand, Malaysia, Philippines, Vietnam, Mexico, Brazil, Turkey, Saudi Arabia, U.A.E, etc.

Latest News

- June 2019 - XAG, a Chinese firm, presented its innovative solutions of combining drones with AI and IoT technology to achieve precision agriculture and induce transformational changes to the food system in 3rd AI for Good Global Summit, in Geneva. XAG is driving AI-powered intelligent devices such as drones and sensors to establish digital farming infrastructure in rural areas and enable precision agriculture which, for example, accurately target pesticides, seeds, fertilizers and water to wherever it is needed.

- April 2019 - Yara and IBM Services joined forces to innovate and commercialize digital agricultural solutions that will help increase global food production. Yara and IBM will develop digital solutions that empower professional and smallholder farmers to optimize farming practices to increase yields, crop quality, and incomes in a sustainable way. The partnership will focus on all aspects of farm optimization and apply AI, machine learning, and in-field data to unlock new insights for farmers, specifically in the area of weather data, where weather company will provide hyperlocal weather forecasts with real-time actionable recommendations tailored to the specific needs of individual fields/crops.

Market Insights:

- Maximize crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyze crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant.

- Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle.

- Increase use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is driving the market as the use of drones in the agriculture industry can be use in crop field scanning with compact multispectral imaging sensors, GPS map creation through onboard cameras, heavy payload transportation, and livestock monitoring with thermal-imaging camera-equipped drones, which increases the demand of UAVs.

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Artificial Intelligence (AI) Market in Agriculture Analysis and Strategies Carry Out as below:

The report elucidates a gist of the tried-and-tested as well as innovative strategies undertaken by potential stakeholders with regards to the marketing of the product.
The sales channels chosen (that include direct as well as indirect marketing) by the companies are briefly enumerated in the Artificial Intelligence (AI) Market in Agriculture market report.
The distributors of these products and a gist of the top-of-the-notch customers for the same are also encompassed in the study.
The report is inclusive of the pivotal driving forces influencing the commercialization landscape of the Artificial Intelligence (AI) Market in Agriculture market and their impact on the revenue scale of this business sphere.
The rising product demand from the key geographies as well as the pivotal applications and potential business arenas are also included in the Artificial Intelligence (AI) Market in Agriculture Market report.

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Note: All the reports that we list have been tracking the impact of COVID-19 on the market. Both upstream and downstream of the entire supply chain has been accounted for while doing this. Also, where possible, we will provide an additional COVID-19 update supplement/report to the report in Q3, please check for with the sales team.

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MarketInsightsReports provides syndicated market research on industry verticals including Healthcare, Information and Communication Technology (ICT), Technology and Media, Chemicals, Materials, Energy, Heavy Industry, etc. MarketInsightsReports provides global and regional market intelligence coverage, a 360-degree market view which includes statistical forecasts, competitive landscape, detailed segmentation, key trends, and strategic recommendations.

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