HTF MI offers deep assessment of the Global and Regional AI in Agriculture Market. The Research report presents a complete assessment of the market and contains Future trend, Current Growth Factors, attentive opinions, historical data, facts and statistically supported and industry certified market data. It delivers regional exploration of the Global and Regional AI in Agriculture market to expose key prospects presented in different parts of the world. The study is segmented by products type, application/end-users. The competitive scenery is generally appraised along with company profiling of leading players operating in the Global and Regional AI in Agriculture market. Some of the Most Important Key Players Involved in the Study are IBM , Deere & Company , Microsoft , Agribotix , The Climate Corporation (Subsidiary of Monsanto) , Granular , Descartes Labs , Prospera , Mavrx , Awhere , Gamaya, Ec2ce, Precision Hawk, Skysquirrel Technologies, Cainthus, Tule Technologies, Resson, Farmbot, Connecterra, Vision Robotics, By Technology, Machine Learning , Computer Vision , Predictive Analytics, By Offering, Hardware , Software , AI-As-A-Service & Service .
If you are involved in the AI in Agriculture industry or intend to be, then this study will provide you comprehensive outlook. It’s vital you keep your market knowledge up to date segmented by Applications Precision Farming , Livestock Monitoring , Drone Analytics , Agriculture Robots , Other Applications & By, Product Types such as and some major players in the industry. If you have a different set of players/manufacturers according to geography or needs regional or country segmented reports we can provide customization according to your requirement.
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The AI in Agriculture market size will grow from USD 522.6 Million in 2017 to USD 1765.98 Million by 2023, at an estimated CAGR of 22.5%. The base year considered for the study is 2017, and the market size is projected from 2018 to 2023. The major factors driving the growth of the AI in agriculture market include the growing demand for agricultural production owing to the increasing population, rising adoption of information management systems and new, advanced technologies for improving crop productivity, increasing crop productivity by implementing deep learning techniques, and growing initiatives by worldwide governments supporting the adoption of modern agricultural techniques. The combination of the Internet of Things and artificial intelligence technologies, such as machine learning, computer vision, and predictive analytics, further allow farmers to analyze real-time data of weather conditions, temperature, soil moisture, plant health, and crop prices in the market.
The Global and Regional AI in Agriculture market report gives an exceptional, first-time present and attentive analysis of the size, patterns, division and lookout in the production and supply of AI in Agriculture on the world. It also talks almost the market size of different sections and their progress features along with growth trends, various stakeholders like investors, traders, suppliers, CEOs, Research & media, Global Director, Manager, President, SWOT analysis i.e. Strength, Weakness, Opportunities, and Threat to the business and others.
MARKET SPLIT BY PRODUCT TYPE AND APPLICATIONS:
The report segments the Global and Regional AI in Agriculture Market on the basis of Types as follows:
On the basis of Application/End-Users, the Global and Regional AI in Agriculture market is segmented into:
Precision Farming , Livestock Monitoring , Drone Analytics , Agriculture Robots , Other Applications & By
Players Profiled: IBM , Deere & Company , Microsoft , Agribotix , The Climate Corporation (Subsidiary of Monsanto) , Granular , Descartes Labs , Prospera , Mavrx , Awhere , Gamaya, Ec2ce, Precision Hawk, Skysquirrel Technologies, Cainthus, Tule Technologies, Resson, Farmbot, Connecterra, Vision Robotics, By Technology, Machine Learning , Computer Vision , Predictive Analytics, By Offering, Hardware , Software , AI-As-A-Service & Service
Region Analysis
• Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific)
• North America (U.S., Canada, Mexico)
• Europe (U.K., France, Germany, Spain, Italy and Rest of Europe)
• Middle East and Africa (Turkey, GCC, UAE and South Africa Rest of Middle East)
• Latin America (Brazil, Argentina, Colombia and Rest of L.A.)
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Stay up-to-date with AI in Agriculture market research offered by HTF MI. Check how key trends and emerging drivers are shaping this industry growth as the study avails you with market characteristics, size and growth, segmentation, regional breakdowns, competitive landscape, shares, trend and strategies for this market. In the AI in Agriculture Market Analysis & Forecast 2018-2023, the revenue is valued at USD XX million in 2017 and is expected to reach USD XX million by the end of 2023, growing at a CAGR of XX% between 2018 and 2023. The production is estimated at XX million in 2017 and is forecasted to reach XX million by the end of 2023, growing at a CAGR of XX% between 2018 and 2023.
In this study, the years considered to estimate the market size of the AI in Agriculture are as follows:
History Year: 2013-2018 | Base Year: 2018 | Estimated Year: 2019 | Forecast Year 2019 to 2024
Research Objectives:
Focuses on the key Global and Regional AI in Agriculture manufacturers, to define, pronounce and examine the value, sales volume, market share, market competition landscape, SWOT analysis, and development plans in the next few years.
To share comprehensive information about the key factors influencing the growth of the market (opportunities, drivers, growth potential, industry-specific challenges and risks).
To analyze the AI in Agriculture with respect to individual future prospects, growth trends and their involvement to the total market.
To analyze reasonable developments such as agreements, expansions new product launches, and acquisitions in the market.
To deliberately profile the key players and systematically examine their growth strategies.
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Key Points sheathed in the AI in Agriculture Market Report Coverage:
– Market share study of the top manufacturing players
– Market share debts for the regional and country level segments
– Premeditated references for the new competitors
– Competitive landscaping planning the key common trends
– Tactical endorsements in key business segments based on the market estimations
– Market Trends (Constraints, Drivers, Opportunities, Threats, Challenges, recommendations and Investment Opportunities)
– Company profiling with detailed strategies, financial and latest developments
– Supply chain trends mapping the latest technological advancements
There are 15 Chapters to display the AI in Agriculture Market
Chapter 1, to describe Definition, Specifications and Classification of AI in Agriculture, Applications of Global and Regional AI in Agriculture, Market Segment by Regions;
Chapter 2, Market Trend Analysis, Regional Market Trend, Market Trend by Product Type [,], Market Trend by Application [Precision Farming , Livestock Monitoring , Drone Analytics , Agriculture Robots , Other Applications & By];
Chapter 3, to analyze the Manufacturing Cost Structure, Raw Material and Suppliers, Manufacturing Process, Industry Chain Structure;
Chapter 4, to show the Overall Market Analysis, Capacity Analysis (Company Segment), Sales Analysis (Company Segment), Sales Price Analysis (Company Segment);
Chapter 5, to display the Technical Data and Manufacturing Plants Analysis of , Capacity and Commercial Production Date, Manufacturing Plants Distribution, Export & Import, R&D Status and Technology Source, Raw Materials Sources Analysis;
Chapter 6 and 7, to show the Regional Market Analysis that includes North America, Europe, Asia-Pacific etc, AI in Agriculture Segment Market Analysis (by Type);
Chapter 8, to analyze the AI in Agriculture Segment Market Analysis (by Application [Precision Farming , Livestock Monitoring , Drone Analytics , Agriculture Robots , Other Applications & By]) Major Manufacturers Analysis;
Chapter 9, Regional Marketing Type Analysis, International Trade Type Analysis, Supply Chain Analysis;
Chapter 10, to analyze the Consumers Analysis of AI in Agriculture by region, type and application ;
Chapter 11, to describe AI in Agriculture Research Findings and Conclusion, Appendix, methodology and data source;
Chapter 12, 13, 14 and 15, to describe AI in Agriculture sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source.
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