Global Artificial Intelligence (AI) in Agriculture Market 2018 by Manufacturers, Countries, Type and Application, Forecast to 2023

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Artificial Intelligence (AI) in Agriculture Market size is being driven by the growing adoption of the robots in agriculture. Increasing consumption and rising requirement of better yield of crops are estimated to be one of the major factors that is fueling the demand of robots in agriculture. Increasing consumption motivates farmers to scale up farming operations and give rise to the requirement of automating farming operations. As the farmers are shifting more towards automation, drones and robots have become integral part of agriculture farms and are enhancing yield and improving the product quality. Since AI is the backbone of robotics, increasing adoption of robots in agriculture is estimated to drive the AI in agriculture market growth.

Scope of the Report:

This report studies the Artificial Intelligence (AI) in Agriculture market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Artificial Intelligence (AI) in Agriculture market by product type and applications/end industries.

United States is the largest consumption countries of Artificial Intelligence (AI) in Agriculture in the world in the past few years and it will keep leader position in the next few years. United States market took up about 42.96% the global market in 2017, while Europe was about 22.67%.

USA is now the key developers of Artificial Intelligence (AI) in Agriculture; most companies are in USA. Others are in Europe, China and India.

The global Artificial Intelligence (AI) in Agriculture market is valued at 240 million USD in 2017 and is expected to reach 790 million USD by the end of 2023, growing at a CAGR of 21.8% between 2017 and 2023.

The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.

North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Artificial Intelligence (AI) in Agriculture.

Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.

Market Segment by Companies, this report covers

IBM

Intel

Microsoft

SAP

Agribotix

The Climate Corporation

Mavrx

aWhere

Precision Hawk

Granular

Prospera Technologies

Spensa Technologies

Resson

Vision Robotics

Harvest Croo Robotics

CropX

John Deere

Gamaya

Cainthus

Market Segment by Regions, regional analysis covers

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

South America (Brazil, Argentina, Colombia)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Market Segment by Type, covers

Machine Learning

Computer Vision

Predictive Analytics

Market Segment by Applications, can be divided into

Precision Farming

Livestock Monitoring

Drone Analytics

Agriculture Robots

Others

Table of Contents

1 Artificial Intelligence (AI) in Agriculture Market Overview

1.1 Product Overview and Scope of Artificial Intelligence (AI) in Agriculture

1.2 Classification of Artificial Intelligence (AI) in Agriculture by Types

1.2.1 Global Artificial Intelligence (AI) in Agriculture Revenue Comparison by Types (2017-2023)

1.2.2 Global Artificial Intelligence (AI) in Agriculture Revenue Market Share by Types in 2017

1.2.3 Machine Learning

1.2.4 Computer Vision

1.2.5 Predictive Analytics

1.3 Global Artificial Intelligence (AI) in Agriculture Market by Application

1.3.1 Global Artificial Intelligence (AI) in Agriculture Market Size and Market Share Comparison by Applications (2013-2023)

1.3.2 Precision Farming

1.3.3 Livestock Monitoring

1.3.4 Drone Analytics

1.3.5 Agriculture Robots

1.3.6 Others

1.4 Global Artificial Intelligence (AI) in Agriculture Market by Regions

1.4.1 Global Artificial Intelligence (AI) in Agriculture Market Size (Million USD) Comparison by Regions (2013-2023)

1.4.1 North America (USA, Canada and Mexico) Artificial Intelligence (AI) in Agriculture Status and Prospect (2013-2023)

1.4.2 Europe (Germany, France, UK, Russia and Italy) Artificial Intelligence (AI) in Agriculture Status and Prospect (2013-2023)

1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) Artificial Intelligence (AI) in Agriculture Status and Prospect (2013-2023)

1.4.4 South America (Brazil, Argentina, Colombia) Artificial Intelligence (AI) in Agriculture Status and Prospect (2013-2023)

1.4.5 Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Artificial Intelligence (AI) in Agriculture Status and Prospect (2013-2023)

1.5 Global Market Size of Artificial Intelligence (AI) in Agriculture (2013-2023)

2 Manufacturers Profiles

2.1 IBM

2.1.1 Business Overview

2.1.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.1.2.1 Product A

2.1.2.2 Product B

2.1.3 IBM Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.2 Intel

2.2.1 Business Overview

2.2.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.2.2.1 Product A

2.2.2.2 Product B

2.2.3 Intel Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.3 Microsoft

2.3.1 Business Overview

2.3.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.3.2.1 Product A

2.3.2.2 Product B

2.3.3 Microsoft Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.4 SAP

2.4.1 Business Overview

2.4.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.4.2.1 Product A

2.4.2.2 Product B

2.4.3 SAP Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.5 Agribotix

2.5.1 Business Overview

2.5.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.5.2.1 Product A

2.5.2.2 Product B

2.5.3 Agribotix Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.6 The Climate Corporation

2.6.1 Business Overview

2.6.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.6.2.1 Product A

2.6.2.2 Product B

2.6.3 The Climate Corporation Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.7 Mavrx

2.7.1 Business Overview

2.7.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.7.2.1 Product A

2.7.2.2 Product B

2.7.3 Mavrx Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.8 aWhere

2.8.1 Business Overview

2.8.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.8.2.1 Product A

2.8.2.2 Product B

2.8.3 aWhere Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.9 Precision Hawk

2.9.1 Business Overview

2.9.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.9.2.1 Product A

2.9.2.2 Product B

2.9.3 Precision Hawk Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.10 Granular

2.10.1 Business Overview

2.10.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.10.2.1 Product A

2.10.2.2 Product B

2.10.3 Granular Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.11 Prospera Technologies

2.11.1 Business Overview

2.11.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.11.2.1 Product A

2.11.2.2 Product B

2.11.3 Prospera Technologies Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.12 Spensa Technologies

2.12.1 Business Overview

2.12.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.12.2.1 Product A

2.12.2.2 Product B

2.12.3 Spensa Technologies Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.13 Resson

2.13.1 Business Overview

2.13.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.13.2.1 Product A

2.13.2.2 Product B

2.13.3 Resson Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.14 Vision Robotics

2.14.1 Business Overview

2.14.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.14.2.1 Product A

2.14.2.2 Product B

2.14.3 Vision Robotics Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.15 Harvest Croo Robotics

2.15.1 Business Overview

2.15.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.15.2.1 Product A

2.15.2.2 Product B

2.15.3 Harvest Croo Robotics Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.16 CropX

2.16.1 Business Overview

2.16.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.16.2.1 Product A

2.16.2.2 Product B

2.16.3 CropX Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.17 John Deere

2.17.1 Business Overview

2.17.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.17.2.1 Product A

2.17.2.2 Product B

2.17.3 John Deere Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.18 Gamaya

2.18.1 Business Overview

2.18.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.18.2.1 Product A

2.18.2.2 Product B

2.18.3 Gamaya Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

2.19 Cainthus

2.19.1 Business Overview

2.19.2 Artificial Intelligence (AI) in Agriculture Type and Applications

2.19.2.1 Product A

2.19.2.2 Product B

2.19.3 Cainthus Artificial Intelligence (AI) in Agriculture Revenue, Gross Margin and Market Share (2016-2017)

3 Global Artificial Intelligence (AI) in Agriculture Market Competition, by Players

3.1 Global Artificial Intelligence (AI) in Agriculture Revenue and Share by Players (2013-2018)

3.2 Market Concentration Rate

3.2.1 Top 5 Artificial Intelligence (AI) in Agriculture Players Market Share

3.2.2 Top 10 Artificial Intelligence (AI) in Agriculture Players Market Share

3.3 Market Competition Trend

4 Global Artificial Intelligence (AI) in Agriculture Market Size by Regions

4.1 Global Artificial Intelligence (AI) in Agriculture Revenue and Market Share by Regions

4.2 North America Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

4.3 Europe Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

4.4 Asia-Pacific Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

4.5 South America Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

4.6 Middle East and Africa Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

5 North America Artificial Intelligence (AI) in Agriculture Revenue by Countries

5.1 North America Artificial Intelligence (AI) in Agriculture Revenue by Countries (2013-2018)

5.2 USA Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

5.3 Canada Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

5.4 Mexico Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

6 Europe Artificial Intelligence (AI) in Agriculture Revenue by Countries

6.1 Europe Artificial Intelligence (AI) in Agriculture Revenue by Countries (2013-2018)

6.2 Germany Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

6.3 UK Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

6.4 France Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

6.5 Russia Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

6.6 Italy Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

7 Asia-Pacific Artificial Intelligence (AI) in Agriculture Revenue by Countries

7.1 Asia-Pacific Artificial Intelligence (AI) in Agriculture Revenue by Countries (2013-2018)

7.2 China Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

7.3 Japan Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

7.4 Korea Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

7.5 India Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

7.6 Southeast Asia Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

8 South America Artificial Intelligence (AI) in Agriculture Revenue by Countries

8.1 South America Artificial Intelligence (AI) in Agriculture Revenue by Countries (2013-2018)

8.2 Brazil Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

8.3 Argentina Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

8.4 Colombia Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

9 Middle East and Africa Revenue Artificial Intelligence (AI) in Agriculture by Countries

9.1 Middle East and Africa Artificial Intelligence (AI) in Agriculture Revenue by Countries (2013-2018)

9.2 Saudi Arabia Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

9.3 UAE Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

9.4 Egypt Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

9.5 Nigeria Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

9.6 South Africa Artificial Intelligence (AI) in Agriculture Revenue and Growth Rate (2013-2018)

10 Global Artificial Intelligence (AI) in Agriculture Market Segment by Type

10.1 Global Artificial Intelligence (AI) in Agriculture Revenue and Market Share by Type (2013-2018)

10.2 Global Artificial Intelligence (AI) in Agriculture Market Forecast by Type (2018-2023)

10.3 Machine Learning Revenue Growth Rate (2013-2023)

10.4 Computer Vision Revenue Growth Rate (2013-2023)

10.5 Predictive Analytics Revenue Growth Rate (2013-2023)

11 Global Artificial Intelligence (AI) in Agriculture Market Segment by Application

11.1 Global Artificial Intelligence (AI) in Agriculture Revenue Market Share by Application (2013-2018)

11.2 Artificial Intelligence (AI) in Agriculture Market Forecast by Application (2018-2023)

11.3 Precision Farming Revenue Growth (2013-2018)

11.4 Livestock Monitoring Revenue Growth (2013-2018)

11.5 Drone Analytics Revenue Growth (2013-2018)

11.6 Agriculture Robots Revenue Growth (2013-2018)

11.7 Others Revenue Growth (2013-2018)

12 Global Artificial Intelligence (AI) in Agriculture Market Size Forecast (2018-2023)

12.1 Global Artificial Intelligence (AI) in Agriculture Market Size Forecast (2018-2023)

12.2 Global Artificial Intelligence (AI) in Agriculture Market Forecast by Regions (2018-2023)

12.3 North America Artificial Intelligence (AI) in Agriculture Revenue Market Forecast (2018-2023)

12.4 Europe Artificial Intelligence (AI) in Agriculture Revenue Market Forecast (2018-2023)

12.5 Asia-Pacific Artificial Intelligence (AI) in Agriculture Revenue Market Forecast (2018-2023)

12.6 South America Artificial Intelligence (AI) in Agriculture Revenue Market Forecast (2018-2023)

12.7 Middle East and Africa Artificial Intelligence (AI) in Agriculture Revenue Market Forecast (2018-2023)

13 Research Findings and Conclusion

14 Appendix

14.1 Methodology

14.2 Data Source


1

Research Methodology

Market research is a method of gathering, assessing and deducing data & information about a particular market. Market research is very crucial in these days. The techniques analyze about how a product/service can be offered to the market to its end-customers, observe the impact of that product/service based on the past customer experiences, and cater their needs and demands. Owing to the successful business ventures, accurate, relevant and thorough information is the base for all the organizations because market research report/study offers specific market related data & information about the industry growth prospects, perspective of the existing customers, and the overall market scenario prevailed in past, ongoing present and developing future. It allows the stakeholders and investors to determine the probability of a business before committing substantial resources to the venture. Market research helps in solving the marketing issues challenges that a business will most likely face.

Market research is valuable because of the following reasons:

  • Market research helps businesses strengthen a company’s position
  • Market research helps in minimizing the investment risks associated with the businesses in any industry vertical
  • Market research helps in identifying the potential threats and opportunities associated with the business industry
  • Market research aids in spotting the emerging trends and facilitates strategic planning in order to stay ahead in the competition

Our research report features both the aspects; qualitative and quantitative. Qualitative part provides insights about the market driving forces, potential opportunities, customer’s demands and requirement which in turn help the companies to come up with new strategies in order to survive in the long run competition. The quantitative segment offers the most credible information related to the industry. Based on the data gathering, we use to derive the market size and estimate their future growth prospects on the basis of global, region and country.

Our market research process involves with the four specific stages.

  • Data Collection
  • Data Synthesis
  • Market Deduction & Formulation
  • Data Screening & Validation

Data Collection: This stage of the market research process involves with the gathering and collecting of the market/industry related data from the sources. There are basically two types of research methods:

  • Primary Research: By conducting primary research, it involves with the two types of data gathering; exploratory and specific. Exploratory data is open-ended and helps us to define a particular problem involving surveys, and pilot study to the specific consumer group, knowing their needs and wants catering to the industry related product/service offering. Explanatory data gathering follows with the bit of unstructured way. Our analyst group leads the study by focusing on the key crowd, in this manner picking up bits of knowledge from them. In light of the points of view of the clients, this data is used to plan advertise techniques. In addition, showcase overviews causes us to comprehend the current scenario of the business. Specific data gathering on the hand, involves with the more structured and formal way. The primary research usually includes in telephonic conversations, E-mail collaborations and up close and personal meetings/interviews with the raw material suppliers, industrial wholesalers, and independent consultants/specialists. The interviews that we conduct offers important information on showcase size and industry development patterns. Our company likewise conducts interviews with the different business specialists so as to increase generally bits of knowledge of the business/showcase.
  • Secondary Research: The secondary research incorporates with the data gathering from the non-profit associations and organizations, for example, World bank, WHO, investor relations and their presentations, statistical databases, yearly(annual reports) reports, national government records, factual databases, websites, articles, white papers, press releases, blogs and others. From the annual report, we deduce an organization's income/revenue generation to comprehend the key product segment related to the market. We examine the organization sites and implement product mapping strategy which is significant for determining the segment revenue. In the product mapping technique, we choose and categorize the products offered by the companies catering to the industry specific market, derive the segment revenue for each of the organizations to get the market estimation. We also gather data & Information based on the supply and demand side of the value chain involved with the domain specific market. The supply side denotes the distributors, wholesalers, suppliers and the demand side denotes the end-consumers/customers of the value chain. The supply side of the market is analyzed by examining the product growth across industry in each of the region followed by its pricing analysis. The demand side is analyzed by the evaluating the penetration level and adoption rates of the product by referring to the historical/past data, examine the present usage and forecasting the future trends. 
  • Purchased Database: Our purchased data provides insights about the key market players/companies along with their financial analysis. Additionally, our data base also includes market related information. 
    • We also have the agreements with various reputed data providers, consultants and third party vendors who provide information which are not limited to:
      • Export & Import Data
      • Business Information related to trade and its statistics
      • Penetration level of a particular product/service based on geography mainly focusing on the unmet prerequisites of the customers.
  • In-house Library: Apart from these third-party sources, we have our in-house library of quantitative and qualitative data & information. Our in-house database includes market data for various industry and domains. These data are updated on regular basis as per the changing market scenario. Our library includes, internal audit reports, historic databases, archives and journal publications. Sometimes there are instances where there is no metadata or raw data available for any domain specific market. For those particular cases, we utilize our expertise to forecast and estimate the market size in order to generate comprehensive data sets. Our analyst team adopts a robust research technique in order to deduce the market size and its estimates:
  • Examining demographic along with psychographic segmentation for market evaluation
  • Analyzing the macro and micro-economic indicators for each demography
  • Evaluating the current industry trends popular in the market.

Data Synthesis: This stage includes the evaluation and assessment of all the data acquired from the primary and secondary research. It likewise includes in evaluating the information for any disparity watched while information gathering identified with the market. The data & information is gathered with consideration to the heterogeneity of sources. Scientific and statistical methods are implemented for synthesizing dissimilar information sets and provide the relevant data which is fundamental for formulating strategies. Our organization has broad involvement with information amalgamation where the information goes through different stages:

  • Information Screening: Information screening is the way toward examining information/data gathered from the sources for errors/mistakes and amending it before data integration process. The screening includes in looking at raw information, identifying and distinguishing mistakes and managing missing information. The reason for the information screening is to ensure information is effectively entered or not. Our organization utilizes objective and precise information screening grades through repetitive quality checks.
  • Data Integration: The data integration method involves with the incorporation of numerous information streams. The data streams is important so as to deliver investigate examines that give overall market scenario to the investors. These information streams originate from different research contemplates and our in house database. After the screening of the information, our analysts conduct efficient integration of the data streams, optimizing connections between integrated surveys and syndicated data sources. There are two research approaches that we follow so as to coordinate our information; top down methodology and bottom up methodology. 
    • Top-down analysis generally refers to using broad factors as a basis for decision making. The top-down approach helps in identifying the overall market scenario along with the external and internal factors effecting the market growth.
    • The bottom-up approach takes a completely different approach. Generally, the bottom-up approach focuses its analysis on micro attributes and specific characteristics of the domain specific market.

Market Formulation & Deduction: The last stage includes assigning the data & information in a suitable way in order to derive market size. Analyst reviews and domain based opinions based on holistic approach of market estimation combined with industry investigation additionally features a crucial role in this stage.

This stage includes with the finalization of the market size and numbers that we have gathered from primary and secondary research. With the data & information addition, we ensure that there is no gap in the market information. Market trend analysis is finished by our analysts by utilizing data extrapolation procedures, which give the most ideal figures to the market.

Data Validation: Validation is the most crucial step in the process. Validation & re-validation through scientifically designed technique and process that helps us finalize data-points to be used for final calculations. This stage also involves with the data triangulation process. Data triangulation generally implicates the cross validation and matching the data which has been collected from primary and secondary research methods.

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