Global Artificial Intelligence in Agriculture Market – Industry Analysis and Forecast (2020-2027) – by Technology, Offering, Application, and Geography.

Global Artificial Intelligence in Agriculture Market – Industry Analysis and Forecast (2020-2027) – by Technology, Offering, Application, and Geography.

Market Scenario

Global Artificial Intelligence in Agriculture Market was valued at US$ X4X Mn in 2019 and is expected to reach US$ X1X6 Mn by 2027, at a CAGR of X5. 3X% during a forecast period. Global Artificial Intelligence in Agriculture Market According to UN Food and Agriculture Organization, the population will rise by 9.8 billion by 2050. Conversely, only 4% further land will come under farming by then. In this perspective, use of advance technological solutions to make cultivation more efficient, remains one of the greatest requirements. While, AI sees many direct use across sectors, i.e. AI-powered solutions will not only empower farmers to do better with less, it will also increase quality and assure faster go to market for crops. The report directed towards how AI can transform the agriculture landscape, the use of drone-made image processing techniques, exactitude farming landscape, the future of agriculture, challenges and overall Artificial Intelligence in Agriculture market position in forecast period. Market Scope Agriculture is seeing prompt implementation of AI and Machine Learning (ML) both in terms of agricultural products and in-field agriculture techniques. Intellectual computing in specific, is all set to become the most disruptive technology in agriculture service sector as it can understand, learn, and respond to different circumstances to rise efficacy. Providing some of these solutions as a service such as chatbot or other conversational platform to all the farmers will help them keep pace with technological innovations as well as apply the same in their day-to-day farming to obtain the benefits of this service. Now, Microsoft is working with 175 farmers in India to deliver counselling services for sowing, land and fertilizer. This initiative has previously resulted in 30% higher yield per hectare on an average compared to last year. Industry Dynamics Drivers Growth driven by IOT Large volumes of data get produced every day together with structured and unstructured format. These re-count to data on historic weather pattern, soil reports, new research, rainfall, pest invasion, images from drones and cameras. Intellectual IOT solutions can sense all this data and deliver strong perceptions to increase yield. Proximity Sensing and Remote Sensing are two technologies which are mainly used for intelligent data fusion. This supports in soil characterization based on the soil below the surface in a specific place. Hardware solutions like Rowbot are already coupling data collecting software with robotics to formulate the best fertilizer for growing corns as well to other activities to maximize output. Image-based insight generation Exactitude farming is one of the maximum discussed areas in farming today. Drone-based images can support in in-depth field analysis, crop observing and scanning of fields. Computer vision technology, IOT and drone data can be collective to assure rapid actions by farmers. Feeds from drone image data can create alerts in real time to increase the speed of precision farming. Companies such as Aerialtronics have employed IBM Watson IoT Platform and the Visual Recognition APIs in commercial drones for image analysis in real time. More or less areas where computer vision technology can be put to utilization in Disease detection, Crop readiness identification, Field management, etc. Health monitoring of crops Remote sensing techniques together with hyper spectral imaging and 3d laser scanning are crucial to create crop metrics thru thousands of acres. It has the likely to lead in a revolutionary change regarding of how farmlands are observed by farmers both from time and effort outlook. This technology will also be utilized to monitor crops along their complete lifecycle containing report generation in case of anomalies. Automation techniques in irrigation and enabling farmers With regard to human intensive processes in farming, irrigation is one of the process. Machines trained on historic weather pattern, soil quality and kind of crops to be grown, can automate irrigation and amplify overall yield. With close to 65-75% of the world’s fresh water being utilized in irrigation, automation can assist to farmers for better management of their water problems. Challenges Lack of familiarity with high tech machine learning solutions However, AI offers huge opportunities for application in agriculture, there still exists a lack of awareness with high tech machine learning solutions in farms across most of the region in a globe. Introduction of farming to external factors like weather conditions, soil situations and existence of pests is relatively high. Similarly, AI systems also require a lot of data to train machines and to make accurate predictions. Market Trends Agricultural Drones to Amplify the Growth of Market As global population anticipated to reach over 9.8 billion by 2050, agricultural consumption is anticipated to rise by a massive 75%, where drones have now been mainstreamed for smart farming supporting farmers in a range of tasks from analysis and planning to the real planting of crops, and the ensuing observing of fields to determine health and growth. Also, drones prepared with hyperspectral, multispectral, or thermal sensors are capable to detect areas that need changes in irrigation. Once crops have started growing, these sensors are capable to estimate their vegetation index, and indicator of health through AI, by determining the crop’s heat signature. Geographic Overview Europe is estimated to account for the largest market growth due to their farmers manage almost half of the land area for agriculture and it makes dominant industry in Europe. Trend in observing and reporting utensils for indoor and outdoor farms, and delivering a visualization of the farmer’s intact production using computer vision and AI are increasing the AI market in agriculture. The European Soil Data Centre (ESDAC) is the thematic center for soil associated data in Europe, where its goal is to be the single reference point for and to host all appropriate soil data and statistics at European level. AI firms are handling 'Internet of the Soil', which is a software and hardware solution for observing soil conditions like humidity, temperature, electrical conductivity, and more in European countries. Their sensors connect wirelessly to a cloud-based platform where it can be retrieved by any internet connected device. Berlin-based InFarm has urbanized a vertical indoor farming system using IoT, Big Data, and cloud analytics, which can be employed in supermarkets, restaurants, local distribution warehouses, permitting businesses to grow their own fresh crop on site to deliver to customers. It is already inaugural indoor farms in 1,000 locations in Germany, and expanding in other European markets, which rises the AI in agriculture market. North America is evaluated as second largest market for AI in agriculture in the worldwide. The growth of the market is attributed to the high selection of trend setting innovations and item in agriculture part. Asia Pacific is estimated to meet high growth rate in the forecast period due to the rising demand from emerging nations, for instance, India and China. Also, rising adoption of the mechanical technology and IoT devices in agriculture is additionally evaluated to drive the Artificial Intelligence in Agriculture market. The report covers the market leaders, followers and new entrants in the industry with the market dynamics by region. It will also help to understand the position of each player in the market by region, by segment with their expansion plans, R&D expenditure and organic & in-organic growth strategies. Long term association, strategic alliances, supply chain agreement and M&A activities are covered in the report in detail from 2014 to 2019. Expected alliances and agreement in forecast period will give future course of action in the market to the readers. More than ten companies are profiled, benchmarked in the report on different parameters that will help reader to gain insight about the market in minimum time. The objective of the report is to present a comprehensive analysis of the Global Artificial Intelligence in Agriculture Market including all the stakeholders of the industry. The past and current status of the industry with forecasted market size and trends are presented in the report with the analysis of complicated data in simple language. The report covers all the aspects of the industry with a dedicated study of key players that includes market leaders, followers and new entrants by Vehicle. PORTER, SVOR, PESTEL analysis with the potential impact of micro-economic factors by Vehicle on the market have been presented in the report. External as well as internal factors that are supposed to affect the business positively or negatively have been analyzed, which will give a clear futuristic view of the industry to the decision-makers. The report also helps in understanding Global Artificial Intelligence in Agriculture Market dynamics, structure by analyzing the market segments and project the Global Artificial Intelligence in Agriculture Market size. Clear representation of competitive analysis of key players by Application, price, financial position, Product portfolio, growth strategies, and regional presence in the Global Artificial Intelligence in Agriculture Market make the report investor’s guide.

Scope of Global Artificial Intelligence in Agriculture Market:

Global Artificial Intelligence in Agriculture Market by Technology:

• Machine Learning • Computer Vision • Predictive Analytics

Global Artificial Intelligence in Agriculture Market by Offering:

• Hardware • Software • AI-as-a-Service • Service

Global Artificial Intelligence in Agriculture Market by Application:

• Precision Farming • Crop Monitoring • Drone Analytics • Agriculture Robots • Others

Global Artificial Intelligence in Agriculture Market by Geography:

• North America • Asia Pacific • Europe • Latin America • Middle East & Africa

Key Players Operated in Market Includes:

• IBM • John Deere • Microsoft • Agribotix • The Climate Corporation • ec2ce • Descartes Labs • Sky Squirrel Technologies • Mavrx • aWhere • Gamaya • Precision • Granular • Prospera technologies • Cainthus • Spensa Technologies • Resson • FarmBot • Connecterra • Vision Robotics • Harvest Croo • Autonomous Tractor Corporation • Trace Genomics • Vine Rangers • CropX • Intel • SAP

Table of Contents

Global Artificial Intelligence in Agriculture Market

1. Preface 1.1. Report Scope and Market Segmentation 1.2. Research Highlights 1.3. Research Objectives 2. Assumptions and Research Methodology 2.1. Report Assumptions 2.2. Abbreviations 2.3. Research Methodology 2.3.1. Secondary Research 2.3.1.1. Secondary data 2.3.1.2. Secondary Sources 2.3.2. Primary Research 2.3.2.1. Data from Primary Sources 2.3.2.2. Breakdown of Primary Sources 3. Executive Summary: Global Artificial Intelligence in Agriculture Market, by Market Value (US$ Mn) 4. Market Overview 4.1. Introduction 4.2. Market Indicator 4.2.1. Drivers 4.2.2. Restraints 4.2.3. Opportunities 4.2.4. Challenges 4.3. Porter’s Analysis 4.4. Value Chain Analysis 4.5. Market Risk Analysis 4.6. SWOT Analysis 4.7. Global Artificial Intelligence in Agriculture Market Industry Trends and Emerging Technologies 5. Supply Side and Demand Side Indicators 6. Global Artificial Intelligence in Agriculture Market Analysis and Forecast 6.1. Global Artificial Intelligence in Agriculture Market Size & Y-o-Y Growth Analysis 6.1.1. North America 6.1.2. Europe 6.1.3. Asia Pacific 6.1.4. Middle East & Africa 6.1.5. South America 7. Global Artificial Intelligence in Agriculture Market Analysis and Forecast, by Technology 7.1. Introduction and Definition 7.2. Key Findings 7.3. Global Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 7.4. Global Artificial Intelligence in Agriculture Market Size (US$ Mn) Forecast, by Technology 7.5. Global Artificial Intelligence in Agriculture Market Analysis, by Technology 7.6. Global Artificial Intelligence in Agriculture Market Attractiveness Analysis, by Technology 8. Global Artificial Intelligence in Agriculture Market Analysis and Forecast, by Offering 8.1. Introduction and Definition 8.2. Key Findings 8.3. Global Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 8.4. Global Artificial Intelligence in Agriculture Market Size (US$ Mn) Forecast, by Offering 8.5. Global Artificial Intelligence in Agriculture Market Analysis, by Offering 8.6. Global Artificial Intelligence in Agriculture Market Attractiveness Analysis, by Offering 9. Global Artificial Intelligence in Agriculture Market Analysis and Forecast, by Application 9.1. Introduction and Definition 9.2. Key Findings 9.3. Global Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 9.4. Global Artificial Intelligence in Agriculture Market Size (US$ Mn) Forecast, by Application 9.5. Global Artificial Intelligence in Agriculture Market Analysis, by Application 9.6. Global Artificial Intelligence in Agriculture Market Attractiveness Analysis, by Application 10. Global Artificial Intelligence in Agriculture Market Analysis, by Region 10.1. Global Artificial Intelligence in Agriculture Market Value Share Analysis, by Region 10.2. Global Artificial Intelligence in Agriculture Market Size (US$ Mn) Forecast, by Region 10.3. Global Artificial Intelligence in Agriculture Market Attractiveness Analysis, by Region 11. North America Artificial Intelligence in Agriculture Market Analysis 11.1. Key Findings 11.2. North America Artificial Intelligence in Agriculture Market Overview 11.3. North America Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 11.4. North America Artificial Intelligence in Agriculture Market Forecast, by Technology 11.4.1. Machine Learning 11.4.2. Computer Vision 11.4.3. Predictive Analytics 11.5. North America Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 11.6. North America Artificial Intelligence in Agriculture Market Forecast, by Offering 11.6.1. Hardware 11.6.2. Software 11.6.3. AI-as-a-Service 11.6.4. Service 11.7. North America Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 11.8. North America Artificial Intelligence in Agriculture Market Forecast, by Application 11.8.1. Precision Farming 11.8.2. Crop Monitoring 11.8.3. Drone Analytics 11.8.4. Agriculture Robots 11.8.5. Others 11.9. North America Artificial Intelligence in Agriculture Market Value Share Analysis, by Country 11.10. North America Artificial Intelligence in Agriculture Market Forecast, by Country 11.10.1. U.S. 11.10.2. Canada 11.11. North America Artificial Intelligence in Agriculture Market Analysis, by Country 11.12. U.S. Artificial Intelligence in Agriculture Market Forecast, by Technology 11.12.1. Machine Learning 11.12.2. Computer Vision 11.12.3. Predictive Analytics 11.13. U.S. Artificial Intelligence in Agriculture Market Forecast, by Offering 11.13.1. Hardware 11.13.2. Software 11.13.3. AI-as-a-Service 11.13.4. Service 11.14. U.S. Artificial Intelligence in Agriculture Market Forecast, by Application 11.14.1. Precision Farming 11.14.2. Crop Monitoring 11.14.3. Drone Analytics 11.14.4. Agriculture Robots 11.14.5. Others 11.15. Canada Artificial Intelligence in Agriculture Market Forecast, by Technology 11.15.1. Machine Learning 11.15.2. Computer Vision 11.15.3. Predictive Analytics 11.16. Canada Artificial Intelligence in Agriculture Market Forecast, by Offering 11.16.1. Hardware 11.16.2. Software 11.16.3. AI-as-a-Service 11.16.4. Service 11.17. Canada Artificial Intelligence in Agriculture Market Forecast, by Application 11.17.1. Precision Farming 11.17.2. Crop Monitoring 11.17.3. Drone Analytics 11.17.4. Agriculture Robots 11.17.5. Others 11.18. North America Artificial Intelligence in Agriculture Market Attractiveness Analysis 11.18.1. By Technology 11.18.2. By Offering 11.18.3. By Application 11.19. PEST Analysis 11.20. Key Trends 11.21. Key Development 12. Europe Artificial Intelligence in Agriculture Market Analysis 12.1. Key Findings 12.2. Europe Artificial Intelligence in Agriculture Market Overview 12.3. Europe Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 12.4. Europe Artificial Intelligence in Agriculture Market Forecast, by Technology 12.4.1. Machine Learning 12.4.2. Computer Vision 12.4.3. Predictive Analytics 12.5. Europe Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 12.6. Europe Artificial Intelligence in Agriculture Market Forecast, by Offering 12.6.1. Hardware 12.6.2. Software 12.6.3. AI-as-a-Service 12.6.4. Service 12.7. Europe Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 12.8. Europe Artificial Intelligence in Agriculture Market Forecast, by Application 12.8.1. Precision Farming 12.8.2. Crop Monitoring 12.8.3. Drone Analytics 12.8.4. Agriculture Robots 12.8.5. Others 12.9. Europe Artificial Intelligence in Agriculture Market Value Share Analysis, by Country 12.10. Europe Artificial Intelligence in Agriculture Market Forecast, by Country 12.10.1. Germany 12.10.2. U.K. 12.10.3. France 12.10.4. Italy 12.10.5. Spain 12.10.6. Rest of Europe 12.11. Europe Artificial Intelligence in Agriculture Market Analysis, by Country 12.12. Germany Artificial Intelligence in Agriculture Market Forecast, by Technology 12.12.1. Machine Learning 12.12.2. Computer Vision 12.12.3. Predictive Analytics 12.13. Germany Artificial Intelligence in Agriculture Market Forecast, by Offering 12.13.1. Hardware 12.13.2. Software 12.13.3. AI-as-a-Service 12.13.4. Service 12.14. Germany Artificial Intelligence in Agriculture Market Forecast, by Application 12.14.1. Precision Farming 12.14.2. Crop Monitoring 12.14.3. Drone Analytics 12.14.4. Agriculture Robots 12.14.5. Others 12.15. U.K. Artificial Intelligence in Agriculture Market Forecast, by Technology 12.15.1. Machine Learning 12.15.2. Computer Vision 12.15.3. Predictive Analytics 12.16. U.K. Artificial Intelligence in Agriculture Market Forecast, by Offering 12.16.1. Hardware 12.16.2. Software 12.16.3. AI-as-a-Service 12.16.4. Service 12.17. U.K. Artificial Intelligence in Agriculture Market Forecast, by Application 12.17.1. Precision Farming 12.17.2. Crop Monitoring 12.17.3. Drone Analytics 12.17.4. Agriculture Robots 12.17.5. Others 12.18. France Artificial Intelligence in Agriculture Market Forecast, by Technology 12.18.1. Machine Learning 12.18.2. Computer Vision 12.18.3. Predictive Analytics 12.19. France Artificial Intelligence in Agriculture Market Forecast, by Offering 12.19.1. Hardware 12.19.2. Software 12.19.3. AI-as-a-Service 12.19.4. Service 12.20. France Artificial Intelligence in Agriculture Market Forecast, by Application 12.20.1. Precision Farming 12.20.2. Crop Monitoring 12.20.3. Drone Analytics 12.20.4. Agriculture Robots 12.20.5. Others 12.21. Italy Artificial Intelligence in Agriculture Market Forecast, by Technology 12.21.1. Machine Learning 12.21.2. Computer Vision 12.21.3. Predictive Analytics 12.22. Italy Artificial Intelligence in Agriculture Market Forecast, by Offering 12.22.1. Hardware 12.22.2. Software 12.22.3. AI-as-a-Service 12.22.4. Service 12.23. Italy Artificial Intelligence in Agriculture Market Forecast, by Application 12.23.1. Precision Farming 12.23.2. Crop Monitoring 12.23.3. Drone Analytics 12.23.4. Agriculture Robots 12.23.5. Others 12.24. Spain Artificial Intelligence in Agriculture Market Forecast, by Technology 12.24.1. Machine Learning 12.24.2. Computer Vision 12.24.3. Predictive Analytics 12.25. Spain Artificial Intelligence in Agriculture Market Forecast, by Offering 12.25.1. Hardware 12.25.2. Software 12.25.3. AI-as-a-Service 12.25.4. Service 12.26. Spain Artificial Intelligence in Agriculture Market Forecast, by Application 12.26.1. Precision Farming 12.26.2. Crop Monitoring 12.26.3. Drone Analytics 12.26.4. Agriculture Robots 12.26.5. Others 12.27. Rest of Europe Artificial Intelligence in Agriculture Market Forecast, by Technology 12.27.1. Machine Learning 12.27.2. Computer Vision 12.27.3. Predictive Analytics 12.28. Rest of Europe Artificial Intelligence in Agriculture Market Forecast, by Offering 12.28.1. Hardware 12.28.2. Software 12.28.3. AI-as-a-Service 12.28.4. Service 12.29. Rest of Europe Artificial Intelligence in Agriculture Market Forecast, by Application 12.29.1. Precision Farming 12.29.2. Crop Monitoring 12.29.3. Drone Analytics 12.29.4. Agriculture Robots 12.29.5. Others 12.30. Europe Artificial Intelligence in Agriculture Market Attractiveness Analysis 12.30.1. By Technology 12.30.2. By Offering 12.30.3. By Application 12.31. PEST Analysis 12.32. Key Trends 12.33. Key Development 13. Asia Pacific Artificial Intelligence in Agriculture Market Analysis 13.1. Key Findings 13.2. Asia Pacific Artificial Intelligence in Agriculture Market Overview 13.3. Asia Pacific Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 13.4. Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Technology 13.4.1. Machine Learning 13.4.2. Computer Vision 13.4.3. Predictive Analytics 13.5. Asia Pacific Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 13.6. Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Offering 13.6.1. Hardware 13.6.2. Software 13.6.3. AI-as-a-Service 13.6.4. Service 13.7. Asia Pacific Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 13.8. Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Application 13.8.1. Precision Farming 13.8.2. Crop Monitoring 13.8.3. Drone Analytics 13.8.4. Agriculture Robots 13.8.5. Others 13.9. Asia Pacific Artificial Intelligence in Agriculture Market Value Share Analysis, by Country 13.10. Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Country 13.10.1. China 13.10.2. India 13.10.3. Japan 13.10.4. ASEAN 13.10.5. Rest of Asia Pacific 13.11. Asia Pacific Artificial Intelligence in Agriculture Market Analysis, by Country 13.12. China Artificial Intelligence in Agriculture Market Forecast, by Technology 13.12.1. Machine Learning 13.12.2. Computer Vision 13.12.3. Predictive Analytics 13.13. China Artificial Intelligence in Agriculture Market Forecast, by Offering 13.13.1. Hardware 13.13.2. Software 13.13.3. AI-as-a-Service 13.13.4. Service 13.14. China Artificial Intelligence in Agriculture Market Forecast, by Application 13.14.1. Precision Farming 13.14.2. Crop Monitoring 13.14.3. Drone Analytics 13.14.4. Agriculture Robots 13.14.5. Others 13.15. India Artificial Intelligence in Agriculture Market Forecast, by Technology 13.15.1. Machine Learning 13.15.2. Computer Vision 13.15.3. Predictive Analytics 13.16. India Artificial Intelligence in Agriculture Market Forecast, by Offering 13.16.1. Hardware 13.16.2. Software 13.16.3. AI-as-a-Service 13.16.4. Service 13.17. India Artificial Intelligence in Agriculture Market Forecast, by Application 13.17.1. Precision Farming 13.17.2. Crop Monitoring 13.17.3. Drone Analytics 13.17.4. Agriculture Robots 13.17.5. Others 13.18. Japan Artificial Intelligence in Agriculture Market Forecast, by Technology 13.18.1. Machine Learning 13.18.2. Computer Vision 13.18.3. Predictive Analytics 13.19. Japan Artificial Intelligence in Agriculture Market Forecast, by Offering 13.19.1. Hardware 13.19.2. Software 13.19.3. AI-as-a-Service 13.19.4. Service 13.20. Japan Artificial Intelligence in Agriculture Market Forecast, by Application 13.20.1. Precision Farming 13.20.2. Crop Monitoring 13.20.3. Drone Analytics 13.20.4. Agriculture Robots 13.20.5. Others 13.21. ASEAN Artificial Intelligence in Agriculture Market Forecast, by Technology 13.21.1. Machine Learning 13.21.2. Computer Vision 13.21.3. Predictive Analytics 13.22. ASEAN Artificial Intelligence in Agriculture Market Forecast, by Offering 13.22.1. Hardware 13.22.2. Software 13.22.3. AI-as-a-Service 13.22.4. Service 13.23. ASEAN Artificial Intelligence in Agriculture Market Forecast, by Application 13.23.1. Precision Farming 13.23.2. Crop Monitoring 13.23.3. Drone Analytics 13.23.4. Agriculture Robots 13.23.5. Others 13.24. Rest of Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Technology 13.24.1. Machine Learning 13.24.2. Computer Vision 13.24.3. Predictive Analytics 13.25. Rest of Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Offering 13.25.1. Hardware 13.25.2. Software 13.25.3. AI-as-a-Service 13.25.4. Service 13.26. Rest of Asia Pacific Artificial Intelligence in Agriculture Market Forecast, by Application 13.26.1. Precision Farming 13.26.2. Crop Monitoring 13.26.3. Drone Analytics 13.26.4. Agriculture Robots 13.26.5. Others 13.27. Asia Pacific Artificial Intelligence in Agriculture Market Attractiveness Analysis 13.27.1. By Technology 13.27.2. By Offering 13.27.3. By Application 13.28. PEST Analysis 13.29. Key Trends 13.30. Key Development 14. Middle East & Africa Artificial Intelligence in Agriculture Market Analysis 14.1. Key Findings 14.2. Middle East & Africa Artificial Intelligence in Agriculture Market Overview 14.3. Middle East & Africa Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 14.4. Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Technology 14.4.1. Machine Learning 14.4.2. Computer Vision 14.4.3. Predictive Analytics 14.5. Middle East & Africa Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 14.6. Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Offering 14.6.1. Hardware 14.6.2. Software 14.6.3. AI-as-a-Service 14.6.4. Service 14.7. Middle East & Africa Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 14.8. Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Application 14.8.1. Precision Farming 14.8.2. Crop Monitoring 14.8.3. Drone Analytics 14.8.4. Agriculture Robots 14.8.5. Others 14.9. Middle East & Africa Artificial Intelligence in Agriculture Market Value Share Analysis, by Country 14.10. Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Country 14.10.1. GCC 14.10.2. South Africa 14.10.3. Rest of Middle East & Africa 14.11. Middle East & Africa Artificial Intelligence in Agriculture Market Analysis, by Country 14.12. GCC Artificial Intelligence in Agriculture Market Forecast, by Technology 14.12.1. Machine Learning 14.12.2. Computer Vision 14.12.3. Predictive Analytics 14.13. GCC Artificial Intelligence in Agriculture Market Forecast, by Offering 14.13.1. Hardware 14.13.2. Software 14.13.3. AI-as-a-Service 14.13.4. Service 14.14. GCC Artificial Intelligence in Agriculture Market Forecast, by Application 14.14.1. Precision Farming 14.14.2. Crop Monitoring 14.14.3. Drone Analytics 14.14.4. Agriculture Robots 14.14.5. Others 14.15. South Africa Artificial Intelligence in Agriculture Market Forecast, by Technology 14.15.1. Machine Learning 14.15.2. Computer Vision 14.15.3. Predictive Analytics 14.16. South Africa Artificial Intelligence in Agriculture Market Forecast, by Offering 14.16.1. Hardware 14.16.2. Software 14.16.3. AI-as-a-Service 14.16.4. Service 14.17. South Africa Artificial Intelligence in Agriculture Market Forecast, by Application 14.17.1. Precision Farming 14.17.2. Crop Monitoring 14.17.3. Drone Analytics 14.17.4. Agriculture Robots 14.17.5. Others 14.18. Rest of Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Technology 14.18.1. Machine Learning 14.18.2. Computer Vision 14.18.3. Predictive Analytics 14.19. Rest of Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Offering 14.19.1. Hardware 14.19.2. Software 14.19.3. AI-as-a-Service 14.19.4. Service 14.20. Rest of Middle East & Africa Artificial Intelligence in Agriculture Market Forecast, by Application 14.20.1. Precision Farming 14.20.2. Crop Monitoring 14.20.3. Drone Analytics 14.20.4. Agriculture Robots 14.20.5. Others 14.21. Middle East & Africa Artificial Intelligence in Agriculture Market Attractiveness Analysis 14.21.1. By Technology 14.21.2. By Offering 14.21.3. By Application 14.22. PEST Analysis 14.23. Key Trends 14.24. Key Development 15. South America Artificial Intelligence in Agriculture Market Analysis 15.1. Key Findings 15.2. South America Artificial Intelligence in Agriculture Market Overview 15.3. South America Artificial Intelligence in Agriculture Market Value Share Analysis, by Technology 15.4. South America Artificial Intelligence in Agriculture Market Forecast, by Technology 15.4.1. Machine Learning 15.4.2. Computer Vision 15.4.3. Predictive Analytics 15.5. South America Artificial Intelligence in Agriculture Market Value Share Analysis, by Offering 15.6. South America Artificial Intelligence in Agriculture Market Forecast, by Offering 15.6.1. Hardware 15.6.2. Software 15.6.3. AI-as-a-Service 15.6.4. Service 15.7. South America Artificial Intelligence in Agriculture Market Value Share Analysis, by Application 15.8. South America Artificial Intelligence in Agriculture Market Forecast, by Application 15.8.1. Precision Farming 15.8.2. Crop Monitoring 15.8.3. Drone Analytics 15.8.4. Agriculture Robots 15.8.5. Others 15.9. South America Artificial Intelligence in Agriculture Market Value Share Analysis, by Country 15.10. South America Artificial Intelligence in Agriculture Market Forecast, by Country 15.10.1. Brazil 15.10.2. Mexico 15.10.3. Rest of South America 15.11. South America Artificial Intelligence in Agriculture Market Analysis, by Country 15.12. Brazil Artificial Intelligence in Agriculture Market Forecast, by Technology 15.12.1. Machine Learning 15.12.2. Computer Vision 15.12.3. Predictive Analytics 15.13. Brazil Artificial Intelligence in Agriculture Market Forecast, by Offering 15.13.1. Hardware 15.13.2. Software 15.13.3. AI-as-a-Service 15.13.4. Service 15.14. Brazil Artificial Intelligence in Agriculture Market Forecast, by Application 15.14.1. Precision Farming 15.14.2. Crop Monitoring 15.14.3. Drone Analytics 15.14.4. Agriculture Robots 15.14.5. Others 15.15. Mexico Artificial Intelligence in Agriculture Market Forecast, by Technology 15.15.1. Machine Learning 15.15.2. Computer Vision 15.15.3. Predictive Analytics 15.16. Mexico Artificial Intelligence in Agriculture Market Forecast, by Offering 15.16.1. Hardware 15.16.2. Software 15.16.3. AI-as-a-Service 15.16.4. Service 15.17. Mexico Artificial Intelligence in Agriculture Market Forecast, by Application 15.17.1. Precision Farming 15.17.2. Crop Monitoring 15.17.3. Drone Analytics 15.17.4. Agriculture Robots 15.17.5. Others 15.18. Rest of South America Artificial Intelligence in Agriculture Market Forecast, by Technology 15.18.1. Machine Learning 15.18.2. Computer Vision 15.18.3. Predictive Analytics 15.19. Rest of South America Artificial Intelligence in Agriculture Market Forecast, by Offering 15.19.1. Hardware 15.19.2. Software 15.19.3. AI-as-a-Service 15.19.4. Service 15.20. Rest of South America Artificial Intelligence in Agriculture Market Forecast, by Application 15.20.1. Precision Farming 15.20.2. Crop Monitoring 15.20.3. Drone Analytics 15.20.4. Agriculture Robots 15.20.5. Others 15.21. South America Artificial Intelligence in Agriculture Market Attractiveness Analysis 15.21.1. By Technology 15.21.2. By Offering 15.21.3. By Application 15.22. PEST Analysis 15.23. Key Trends 15.24. Key Development 16. Company Profiles 16.1. Market Share Analysis, by Company 16.2. Competition Matrix 16.2.1. Competitive Benchmarking of key players by price, presence, market share, Applications and R&D investment 16.2.2. New Product Launches and Product Enhancements 16.2.3. Market Consolidation 16.2.3.1. M&A by Regions, Investment and Applications 16.2.3.2. M&A Key Players, Forward Integration and Backward Integration 16.3. Company Profiles: Key Players 16.3.1. International Business Machine Corporation 16.3.1.1. Company Overview 16.3.1.2. Financial Overview 16.3.1.3. Product Portfolio 16.3.1.4. Business Strategy 16.3.1.5. Recent Developments 16.3.1.6. Company Footprint 16.3.2. John Deere 16.3.3. Microsoft 16.3.4. Agribotix 16.3.5. The Climate Corporation 16.3.6. ec2ce 16.3.7. Descartes Labs 16.3.8. Sky Squirrel Technologies 16.3.9. Mavrx 16.3.10. aWhere 16.3.11. Gamaya 16.3.12. Precision 16.3.13. Granular 16.3.14. Prospera technologies 16.3.15. Cainthus 16.3.16. Spensa Technologies 16.3.17. Resson 16.3.18. FarmBot 16.3.19. Connecterra 16.3.20. Vision Robotics 16.3.21. Harvest Croo 16.3.22. Autonomous Tractor Corporation 16.3.23. Trace Genomics 16.3.24. Vine Rangers 16.3.25. CropX 16.3.26. Intel 16.3.27. SAP 17. Primary Key Insights

About This Report

Report ID25885
Category Information Technology & Telecommunication
Published DateJAN 2020
No of Pages182
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