Artificial Intelligence in Agriculture Market Forecast, 2020-2026

Market Research Report

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1.1   Industry Outlook
1.1.1   Market Definition
1.1.2   Ecosystem/Ongoing Programs
1.1.2.1   Consortiums and Associations
1.1.2.2   Government Initiatives Landscape
1.1.2.2.1   North America
1.1.2.2.2   Europe
1.1.2.2.3   Asia-Pacific
1.1.2.2.4   Rest-of-the-World
1.2   Business Dynamics
1.2.1   Business Drivers
1.2.1.1   Need for Increased Agricultural Production
1.2.1.2   Complexities in Data-Driven Farming
1.2.1.3   Increased Demand for Automation in Agriculture
1.2.2   Business Challenges
1.2.2.1   Data Privacy Concerns Among Farmers
1.2.2.2   Lack of Required Infrastructure in Developing Countries
1.2.3   Business Strategies
1.2.3.1   Product Development
1.2.3.2   Market Developments
1.2.3.3   Other Strategies
1.2.4   Corporate Strategies
1.2.4.1   Mergers and Acquisitions
1.2.4.2   Partnerships, Collaborations, and Joint Ventures
1.2.5   Business Opportunities
1.2.5.1   Increased Government Initiatives Supporting AI in Agriculture
1.2.5.2   Increased Implementation of Robots and Drones in Agriculture
1.2.5.3   Rise in Adoption of SaaS Business Model in Agriculture

2.1   Global Artificial Intelligence in Agriculture Market (by Application)
2.1.1   Global Artificial Intelligence in Agriculture Market (by Farming Type)
2.1.1.1   Field Farming
2.1.1.2   Indoor Farming
2.1.1.3   Livestock Farming
2.1.1.4   Others
2.1.2   Global Artificial Intelligence in Agriculture Market (by End Use)
2.1.2.1   Crops, Fruits, Vegetables, and Other Plants
2.1.2.1.1   Crop Protection
2.1.2.1.2   Weather Forecasting
2.1.2.1.3   Precision Farming
2.1.2.1.4   Farm Machinery Automation
2.1.2.1.5   Crop Growth Assessment
2.1.2.1.6   Others
2.1.2.2   Livestock and Aquaculture
2.1.2.2.1   Animal Growth Monitoring
2.1.2.2.2   Animal Health Monitoring
2.1.2.2.3   Others
2.2   Demand Analysis of Global Artificial Intelligence in Agriculture Market (by Application)
2.2.1   Demand Analysis of Global Artificial Intelligence in Agriculture Market (by Farming Type)
2.2.2   Demand Analysis of Global Artificial Intelligence in Agriculture Market (by End Use)

3.1   Global Artificial Intelligence in Agriculture Market (by Product)
3.1.1   Software
3.1.2   Hardware
3.1.3   Artificial Intelligence-as-a-Service (AIaaS)
3.1.4   Support Services
3.2   Demand Analysis of Global Artificial Intelligence in Agriculture Market (by Product)
3.3   Patent Analysis
3.3.1   Patent Analysis (by Patent Office)
3.3.2   Patent Analysis (by Organization)
3.4   Value Chain Analysis

4.1   North America
4.1.1   Market
4.1.1.1   Key Providers in North America
4.1.1.2   Business Drivers
4.1.1.3   Business Challenges
4.1.2   North America (by Country)
4.1.2.1   U.S.
4.1.2.1.1   Market
4.1.2.1.1.1   Buyer Attributes
4.1.2.1.1.2   Key Providers Operating in the U.S.
4.1.2.1.1.3   Business Challenges
4.1.2.1.1.4   Business Drivers
4.1.2.2   Canada
4.1.2.2.1   Market
4.1.2.2.1.1   Buyer Attributes
4.1.2.2.1.2   Key Providers Operating in Canada
4.1.2.2.1.3   Business Challenges
4.1.2.2.1.4   Business Drivers
4.1.2.3   Mexico
4.1.2.3.1   Market
4.1.2.3.1.1   Buyer Attributes
4.1.2.3.1.2   Key Providers Operating in Mexico
4.1.2.3.1.3   Business Challenges
4.1.2.3.1.4   Business Drivers
4.2   Europe
4.2.1   Market
4.2.1.1   Key Providers in Europe
4.2.1.2   Business Drivers
4.2.1.3   Business Challenges
4.2.2   Europe (by Country)
4.2.2.1   Germany
4.2.2.1.1   Market
4.2.2.1.1.1   Buyer Attributes
4.2.2.1.1.2   Key Providers Operating in Germany
4.2.2.1.1.3   Business Challenges
4.2.2.1.1.4   Business Drivers
4.2.2.2   France
4.2.2.2.1   Market
4.2.2.2.1.1   Buyer Attributes
4.2.2.2.1.2   Key Providers Operating in France
4.2.2.2.1.3   Business Challenges
4.2.2.2.1.4   Business Drivers
4.2.2.3   Italy
4.2.2.3.1   Market
4.2.2.3.1.1   Buyer Attributes
4.2.2.3.1.2   Key Providers Operating in Italy
4.2.2.3.1.3   Business Challenges
4.2.2.3.1.4   Business Drivers
4.2.2.4   Netherlands
4.2.2.4.1   Market
4.2.2.4.1.1   Buyer Attributes
4.2.2.4.1.2   Key Providers Operating in the Netherlands
4.2.2.4.1.3   Business Challenges
4.2.2.4.1.4   Business Drivers
4.2.2.5   Spain
4.2.2.5.1   Market
4.2.2.5.1.1   Buyer Attributes
4.2.2.5.1.2   Key Providers Operating in Spain
4.2.2.5.1.3   Business Challenges
4.2.2.5.1.4   Business Drivers
4.2.2.6   Rest-of-Europe
4.2.2.6.1   Market
4.2.2.6.1.1   Buyer Attributes
4.2.2.6.1.2   Key Providers Operating in the Rest-of-Europe
4.2.2.6.1.3   Business Challenges
4.2.2.6.1.4   Business Drivers
4.3   U.K.
4.3.1   Markets
4.3.1.1   Buyer Attributes
4.3.1.2   Key Providers in the U.K.
4.3.1.3   Business Challenges
4.3.1.4   Business Drivers
4.4   China
4.4.1   Markets
4.4.1.1   Buyer Attributes
4.4.1.2   Key Providers in China
4.4.1.3   Business Challenges
4.4.1.4   Business Drivers
4.5   Asia-Pacific
4.5.1   Market
4.5.1.1   Key Providers in Asia-Pacific
4.5.1.2   Business Drivers
4.5.1.3   Business Challenges
4.5.2   Asia-Pacific (by Country)
4.5.2.1   Japan
4.5.2.1.1   Market
4.5.2.1.1.1   Buyer Attributes
4.5.2.1.1.2   Key Providers in Japan
4.5.2.1.1.3   Business Challenges
4.5.2.1.1.4   Business Drivers
4.5.2.2   India
4.5.2.2.1   Market
4.5.2.2.1.1   Buyer Attributes
4.5.2.2.1.2   Key Providers in India
4.5.2.2.1.3   Business Challenges
4.5.2.2.1.4   Business Drivers
4.5.2.3   Australia
4.5.2.3.1   Market
4.5.2.3.1.1   Buyer Attributes
4.5.2.3.1.2   Key Providers Operating in Australia
4.5.2.3.1.3   Business Challenges
4.5.2.3.1.4   Business Drivers
4.5.2.4   Rest-of-Asia-Pacific
4.5.2.4.1   Market
4.5.2.4.1.1   Buyer Attributes
4.5.2.4.1.2   Key Providers Operating in Rest-of-Asia Pacific
4.5.2.4.1.3   Business Challenges
4.5.2.4.1.4   Business Drivers
4.6   Rest-of-the-World
4.6.1   Market
4.6.1.1   Key Providers in Rest-of-the-World
4.6.1.2   Business Drivers
4.6.1.3   Business Challenges
4.6.2   Rest-of-the-World (by Country)
4.6.2.1   Brazil
4.6.2.1.1   Market
4.6.2.1.1.1   Buyer Attributes
4.6.2.1.1.2   Key Providers Operating in Brazil
4.6.2.1.1.3   Business Challenges
4.6.2.1.1.4   Business Drivers
4.6.2.2   Argentina
4.6.2.2.1   Market
4.6.2.2.1.1   Buyer Attributes
4.6.2.2.1.2   Key Providers Operating in Argentina
4.6.2.2.1.3   Business Challenges
4.6.2.2.1.4   Business Drivers
4.6.2.3   South Africa
4.6.2.3.1   Market
4.6.2.3.1.1   Buyer Attributes
4.6.2.3.1.2   Key Providers Operating in South Africa
4.6.2.3.1.3   Business Challenges
4.6.2.3.1.4   Business Drivers
4.6.2.4   Israel
4.6.2.4.1   Market
4.6.2.4.1.1   Buyer Attributes
4.6.2.4.1.2   Key Providers Operating in Israel
4.6.2.4.1.3   Business Challenges
4.6.2.4.1.4   Business Drivers

5.1   Competitive Benchmarking
5.2   Market Share Analysis
5.3   Company Profiles
5.3.1   Deere & Company
5.3.1.1   Company Overview
5.3.1.2   Role of Deere & Company in Artificial Intelligence in Agriculture Market
5.3.1.3   Service Portfolio
5.3.1.4   Business Strategies
5.3.1.4.1   Market Developments
5.3.1.4.2   Product Developments
5.3.1.5   Corporate Strategies
5.3.1.5.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.1.5.2   Mergers & Acquisitions
5.3.1.6   Strengths and Weaknesses of Deere & Company
5.3.2   Microsoft Corporation
5.3.2.1   Company Overview
5.3.2.2   Role of Microsoft Corporation in Artificial Intelligence in Agriculture Market
5.3.2.3   Service Portfolio
5.3.2.4   Business Strategies
5.3.2.4.1   Market Developments
5.3.2.4.2   Product Launch
5.3.2.5   Corporate Strategies
5.3.2.5.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.2.6   Strengths and Weaknesses of Microsoft Corporation
5.3.3   CNH Industrial N.V.
5.3.3.1   Company Overview
5.3.3.2   Role of CNH Industrial N.V. in Artificial Intelligence in Agriculture Market
5.3.3.3   Service Portfolio
5.3.3.4   Corporate Strategies
5.3.3.4.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.3.4.2   Merger and Acquisition
5.3.3.5   Strengths and Weaknesses of CNH Industrial N.V.
5.3.4   Robert Bosch GmbH
5.3.4.1   Company Overview
5.3.4.2   Role of Robert Bosch GmbH in Artificial Intelligence in Agriculture Market
5.3.4.3   Service Portfolio
5.3.4.4   Business Strategies
5.3.4.4.1   Product Launch
5.3.4.5   Corporate Strategies
5.3.4.5.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.4.6   Strengths and Weaknesses of Robert Bosch GmbH
5.3.5   Granular Inc.
5.3.5.1   Company Overview
5.3.5.2   Role of Granular Inc. in Artificial Intelligence in Agriculture Market
5.3.5.3   Service Portfolio
5.3.5.4   Corporate Strategies
5.3.5.4.1   Partnerships, Collaborations, Joint Ventures, and Alliances
5.3.5.5   Strengths and Weaknesses of Granular Inc.
5.3.6   Harvest Crop Robotics, LLC
5.3.6.1   Company Overview
5.3.6.2   Role of Harvest Crop Robotics, LLC in Artificial Intelligence in Agriculture Market
5.3.6.3   Service Portfolio
5.3.6.4   Strengths and Weaknesses of Harvest Crop Robotics, LLC.
5.3.7   Agrivi
5.3.7.1   Company Overview
5.3.7.2   Role of Agrivi in Artificial Intelligence in Agriculture Market
5.3.7.3   Service Portfolio
5.3.7.4   Business Strategies
5.3.7.4.1   Product Launch
5.3.7.5   Corporate Strategies
5.3.7.5.1   Partnership, Collaborations, Joint Ventures, and Alliances
5.3.7.5.2   Mergers & Acquisitions
5.3.7.6   Strengths and Weaknesses of Agrivi
5.3.8   CropIn Technology Solutions Pvt Ltd.
5.3.8.1   Company Overview
5.3.8.2   Role of CropIn Technology Solutions Pvt Ltd. in Artificial Intelligence in Agriculture Market
5.3.8.3   Service Portfolio
5.3.8.4   Business Strategies
5.3.8.4.1   Product Developments
5.3.8.5   Corporate Strategies
5.3.8.5.1   Partnerships, Collaborations, Joint Ventures, and Alliances
5.3.8.6   Strengths and Weaknesses of CropIn Technology Solutions Pvt Ltd.
5.3.9   Alibaba Group Holding Limited
5.3.9.1   Company Overview
5.3.9.2   Role of Alibaba Group Holding Limited in Artificial Intelligence in Agriculture Market
5.3.9.3   Service Portfolio
5.3.9.4   Corporate Strategies
5.3.9.5   Strengths and Weaknesses of Alibaba Group Holding Limited
5.3.10   The Climate Corporation
5.3.10.1   Company Overview
5.3.10.2   Role of The Climate Corporation in Artificial Intelligence in Agriculture Market
5.3.10.3   Service Portfolio
5.3.10.4   Corporate Strategies
5.3.10.4.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.10.5   Strengths and Weaknesses of The Climate Corporation
5.3.11   Descartes Labs, Inc.
5.3.11.1   Company Overview
5.3.11.2   Role of Descartes Labs, Inc. in Artificial Intelligence in Agriculture Market
5.3.11.3   Service Portfolio
5.3.11.4   Corporate Strategies
5.3.11.4.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.11.5   Strengths and Weaknesses of Descartes Labs, Inc.
5.3.12   PrecisionHawk, Inc.
5.3.12.1   Company Overview
5.3.12.2   Role of Precisionhawk, Inc. in Artificial Intelligence in Agriculture Market
5.3.12.3   Service Portfolio
5.3.12.4   Corporate Strategies
5.3.12.4.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.12.4.2   Mergers and Acquisitions
5.3.12.5   Strengths and Weaknesses of PrecisionHawk, Inc.
5.3.13   Ceres Imaging
5.3.13.1   Company Overview
5.3.13.2   Role of Ceres Imaging in Artificial Intelligence in Agriculture Market
5.3.13.3   Service Portfolio
5.3.13.4   Business Strategies
5.3.13.4.1   Product Developments
5.3.13.5   Corporate Strategies
5.3.13.5.1   Partnerships, Collaborations, Joint Ventures, and Alliances
5.3.13.6   Strengths and Weaknesses of Ceres Imaging
5.3.14   IBM Corporation
5.3.14.1   Company Overview
5.3.14.2   Role of IBM Corporation in Artificial Intelligence in Agriculture Market
5.3.14.3   Service Portfolio
5.3.14.4   Business Strategies
5.3.14.4.1   Product Developments
5.3.14.5   Corporate Strategies
5.3.14.5.1   Partnerships, Joint Ventures, Collaborations, and Alliances
5.3.14.6   Strengths and Weaknesses of IBM Corporation
5.3.15   Prospera Technologies
5.3.15.1   Company Overview
5.3.15.2   Role of Prospera Technologies in Artificial Intelligence in Agriculture Market
5.3.15.3   Service Portfolio
5.3.15.4   Corporate Strategies
5.3.15.5   Strengths and Weaknesses of Prospera Technologies
5.3.16   Other Key Players

6.1   Data Sources
6.1.1   Primary Data Sources
6.1.2   Secondary Data Sources
6.1.3   Data Triangulation
6.2   Market estimation and Forecast
6.2.1   Factors for Data Prediction and Modelling

Table 1:   Key Consortiums and Associations in Global Artificial Intelligence in Agriculture Market
Table 2:   AI Products by Key Companies for Field Farming in Global Artificial Intelligence in Agriculture Market
Table 3:   AI Products by Key Companies for Indoor Farming in Global Artificial Intelligence in Agriculture Market
Table 4:   AI Products by Key Companies for Livestock Farming in Global Artificial Intelligence in Agriculture Market
Table 5:   AI Products by Key Companies for Other Farming Types in Global Artificial Intelligence in Agriculture Market
Table 6:   Key Crop Protection Products in Global Artificial Intelligence in Agriculture Market
Table 7:   Key Weather Forecasting Products in Global Artificial Intelligence in Agriculture Market
Table 8:   Key Precision Farming Products in Global Artificial Intelligence in Agriculture Market
Table 9:   Key Farm Machinery Automation Products in Global Artificial Intelligence in Agriculture Market
Table 10:   Key Crop Growth Assessment Products in Global Artificial Intelligence in Agriculture Market
Table 11:   Other Products in Global Artificial Intelligence in Agriculture Market
Table 12:   Key Animal Growth Monitoring Products in Global Artificial Intelligence in Agriculture Market
Table 13:   Key Animal Health Monitoring Products in Global Artificial Intelligence in Agriculture Market
Table 14:   Other Livestock and Aquaculture Products in Global Artificial Intelligence in Agriculture Market
Table 15:   Global Artificial Intelligence in Agriculture Market (by Farming Type), $Million, 2020-2026
Table 16:   Global Artificial Intelligence in Agriculture Market (by End Use), $Million, 2020-2026
Table 17:   Global Artificial Intelligence in Agriculture Market (by Crops, Fruits, Vegetables, and Other Plants), $Million, 2020-2026
Table 18:   Global Artificial Intelligence in Agriculture Market (by Livestock and Aquaculture), $Million, 2020-2026
Table 19:   Key Players with Artificial Intelligence-Based Software
Table 20:   Key Players with Artificial Intelligence Based Hardware
Table 21:   Key Players with Artificial Intelligence-as-a-Service Products
Table 22:   Key Players with Artificial Intelligence-Based Support Services
Table 23:   Global Artificial Intelligence in Agriculture Market (by Product), $Million, 2020-2026
Table 24:   Global Artificial Intelligence in Agriculture Market (by Region), $Million, 2020-2026
Table 25:   North America Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 26:   Europe Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 27:   U.K. Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 28:   China Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 29:   Asia-Pacific Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 30:   Rest-of-the-World Artificial Intelligence in Agriculture Market (by Country), $Million, 2020-2026
Table 31:   Deere & Company: Service Portfolio
Table 32:   Deere & Company: Market Developments
Table 33:   Deere & Company: Product Developments
Table 34:   Deere & Company: Partnerships, Joint Ventures, Collaborations, and Alliances
Table 35:   Deere & Company: Mergers & Acquisitions
Table 36:   Microsoft Corporation: Service Portfolio
Table 37:   Microsoft Corporation: Market Developments
Table 38:   Microsoft Corporation: Product Launch
Table 39:   Microsoft Corporation: Partnerships, Joint Ventures, Collaborations and Alliances
Table 40:   CNH Industrial N.V.: Service Portfolio
Table 41:   CNH Industrial N.V.: Partnerships, Joint Ventures, Collaborations and Alliances
Table 42:   CNH Industrial N.V.: Mergers and Acquisitions
Table 43:   Robert Bosch GmbH: Service Portfolio
Table 44:   Robert Bosch GmbH: Product Launch
Table 45:   Robert Bosch GmbH: Partnerships, Joint Ventures, Collaborations and Alliances
Table 46:   Granular Inc.: Service Portfolio
Table 47:   Granular Inc.: Partnerships, Collaborations, Joint Ventures, and Alliances
Table 48:   Harvest Crop Robotics, LLC: Service Portfolio
Table 49:   Agrivi: Service Portfolio
Table 50:   Agrivi: Product Launch
Table 51:   Agrivi: Partnership, Collaboration, Joint Ventures, and Alliances
Table 52:   Agrivi: Mergers & Acquisitions
Table 53:   CropIn Technology Solutions Pvt Ltd.: Service Portfolio
Table 54:   CropIn Technology Solutions Pvt Ltd.: Product Developments
Table 55:   CropIn Technology Solutions Pvt Ltd.: Partnerships, Collaborations, Joint Ventures, and Alliances
Table 56:   Alibaba Group Holding Limited: Service Portfolio
Table 57:   Partnerships, Joint Ventures, Collaborations, and Alliances
Table 58:   The Climate Corporation: Service Portfolio
Table 59:   The Climate Corporation: Partnerships, Joint Ventures, Collaborations, and Alliances
Table 60:   Descartes Labs, Inc.: Service Portfolio
Table 61:   Descartes Labs, Inc.: Partnerships, Joint Ventures, Collaborations, and Alliances
Table 62:   PrecisionHawk, Inc.: Service Portfolio
Table 63:   PrecisionHawk, Inc.: Partnerships, Joint Ventures, Collaborations, and Alliances
Table 64:   PrecisionHawk, Inc.: Mergers and Acquisitions
Table 65:   Ceres Imaging: Service Portfolio
Table 66:   Ceres Imaging: Product Developments
Table 67:   Ceres Imaging: Partnerships, Collaborations, Joint Ventures and Alliances
Table 68:   IBM Corporation: Service Portfolio
Table 69:   IBM Corporation: Product Developments
Table 70:   IBM Corporation: Partnerships, Joint Ventures, Collaborations and Alliances
Table 71:   Prospera Technologies: Service Portfolio
Table 72:   Partnerships, Joint Ventures, Collaborations, and Alliances
Table 73:   Other Key Players Operating in Global Artificial Intelligence in Agriculture Market

Figure 1:   Microeconomic Indicators Impacting AI in Agriculture Market
Figure 2:   Market Dynamics of the Global AI in Agriculture Market, Drivers, and Challenges
Figure 3:   Global AI in Agriculture Market, $Billion, 2020-2026
Figure 4:   Global AI in Agriculture Market (by Farming Type), $Million, 2020 and 2026
Figure 5:   Global AI in Agriculture (by Solution), $Million, 2020-2026
Figure 6:   Global AI in Agriculture (by Application), $Million, 2020-2026
Figure 7:   Global AI in Agriculture Market (by Region), $Million, 2020
Figure 8:   Global AI in Agriculture Market Coverage
Figure 9:   Classification of Artificial Intelligence
Figure 10:   AI in Smart Farming Architecture
Figure 11:   Global Artificial Intelligence in Agriculture Market Ecosystem
Figure 12:   Government Initiatives Landscape in North America
Figure 13:   Government Initiatives Landscape in Europe
Figure 14:   Government Initiatives Landscape in Asia-Pacific
Figure 15:   Government Initiatives Landscape in Rest-of-the-World
Figure 16:   Average Data Points Generated from Agricultural IoT Devices Daily, 2014 and 2050
Figure 17:   Employment in Agriculture, by Region
Figure 18:   Share of Key Market Strategies and Developments, 2017-2021
Figure 19:   Product Development and Innovation (by Company), 2018-2021
Figure 20:   Market Developments (by Company), 2017-2021
Figure 21:   Mergers and Acquisitions (by Company), 2017-2021
Figure 22:   Partnerships, Collaborations, and Joint Ventures (by Company), 2017-2021
Figure 23:   Global Artificial Intelligence in Agriculture Market (by Farming Type)
Figure 24:   Global Artificial Intelligence in Agriculture Market (by End Use)
Figure 25:   Global Agriculture Technology-as-a-Service Market (by Service Type)
Figure 26:   Patents Filed or Granted for the Global Smart Farming Market, January 2018-October 2021
Figure 27:   Patent Analysis (by Patent Office), January 2017-October 2021
Figure 28:   Patent Analysis (by Organization), January 2017-October 2021
Figure 29:   Smart Farming Technologies in Agricultural Value Chain
Figure 30:   Competitive Market High and Low Matrix
Figure 31:   Market Share Analysis of AI in Agriculture Equipment Manufacturers, 2020
Figure 32:   Data Triangulation
Figure 33:   Top-Down and Bottom-Up Approach
Figure 34:   Assumptions and Limitations

Market Report Coverage

Artificial Intelligence in Agriculture Market
Base Year	2020	Market Size in 2020	$1,378.0 Million
Forecast Period	2021-2026	Value Projection and Estimation by 2026	$6,655.1 Million
CAGR During Forecast Period	30.56%	Number of Tables	73
Number of Pages	180	Number of Figures	34
Market Segmentation	• Farming Type: Field Farming, Indoor Farming, Livestock Farming, Others • End Use: Crops, Fruits, Vegetables, and Other Plants; Livestock and Aquaculture • Product: Software, Hardware, Artificial Intelligence-as-a-Service (AIaaS), Support Services
Regional Segmentation	• North America: U.S., Canada, and Mexico • Europe: Germany, France, Netherlands, Italy, Spain, and Rest-of-Europe • U.K. • China • Asia-Pacific: India, Japan, Australia, and Rest-of-Asia-Pacific • Rest-of-the-World: Brazil, Argentina, South Africa, Israel
Market Growth Drivers	• Need for Increased Agricultural Production • Complexities in Data-Driven Farming • Increased Demand for Automation in Agriculture
Market Challenges	• Data Privacy Concerns Among Farmers • Lack of Required Infrastructure in Developing Countries
Market Opportunities	• Increased Government Initiatives Supporting AI in Agriculture • Increased Implementation of Robots and Drones in Agriculture • Rise in Adoption of SaaS Business Model in Agriculture
Key Companies Profiled	Deere & Company, Microsoft Corporation, CNH Industrial N.V., Robert Bosch GmbH, Granular Inc., Harvest Crop Robotics, LLC, Agrivi, CropIn Technology Solutions Pvt Ltd., Alibaba Group Holding Limited, The Climate Corporation, Descartes Labs, Inc., PrecisionHawk, Inc., Ceres Imaging, IBM Corporation, Prospera Technologies

How This Report Can Add Value

This extensive report on global artificial intelligence in agriculture market will help you with:

• The report covers product, application, and regional market estimations for the artificial intelligence in agriculture market.
• Extensive competitive benchmarking of the top 15 players (including OEMs and equipment providers) has been done to offer a holistic view of the global artificial intelligence in agriculture market landscape.

Product/Innovation Strategy: The product segment helps the reader in understanding the different types of artificial intelligence in agriculture solutions for the agriculture industry and their potential globally. Moreover, the study provides the reader a detailed understanding of the operation of different artificial intelligence in agriculture products (i.e., software, hardware, artificial intelligence-as-a-service, and support services).

Recent Developments in Artificial Intelligence in Agriculture Market

•   In May 2021, Robert Bosch unveiled its new artificial intelligence based IoT platform to keep real time track of energy consumption, electrical parameters in healthcare, agriculture, and other sectors.
•   In November 2020, Deere & Company introduced AutoPath for more accurate row guidance throughout the season.
•   In November 202, CLAAS KGaA mbH launched the cloud-based DataConnect system that enables the exchange of machinery data between CLAAS, 365FarmNet, and Deere & Company.
•   In September 2020, Agrivi launched Agrivi Farm Fleet that enables farmers to have real-time access to their fuel usage and machinery.

Key Questions Answered in the Report

•   What is the estimated global artificial intelligence in agriculture market size in terms of revenue for the forecast period 2021-2026, and what is the expected compound annual growth rate (CAGR) during the forecast period 2021-2026?
•   What are the key trends, market drivers, and opportunities in the market pertaining to artificial intelligence in agriculture?
•   What are the major restraints inhibiting the growth of global artificial intelligence in agriculture market?
•   What kinds of new strategies are being adopted by the existing market players to strengthen their market position in the industry?
•   What is the competitive strength of the key players in the artificial intelligence in agriculture market based on an analysis of their recent developments, product offerings, and regional presence?
•   How is the competitive benchmarking of the key artificial intelligence in agriculture companies in the agriculture market based on the analysis of their market coverage and market potential?
•   How much revenue is each segment expected to record during the forecast period, along with the growth percentage?
•   What is the type of players and stakeholders operating in the market ecosystem of artificial intelligence in agriculture, and what is their significance in the global market?

Report Summary

Artificial Intelligence in Agriculture

Artificial intelligence technology brings the concept of cognitive computing to agriculture, where the farm equipment intelligence is modeled on human intelligence. Artificial intelligence technologies help farmers in optimizing their planning to generate profitable crop yields using predictable analytics for agricultural input choices and farm process planning.

The capabilities enabled by this technology allow the farm equipment and solutions to interpret, acquire, and react to unpredictable farm situations with enhanced efficiency.

Since 2010, the adoption of artificial intelligence in agriculture solutions has increased, especially by medium and large-scale farmers. Increased awareness regarding the benefits of these solutions has increased the adoption rate of these solutions. High technological advancement in some regions of the world is another driver toward the adoption of artificial intelligence in agriculture solutions by farmers.

Global Artificial Intelligence in Agriculture Market Overview

The global artificial intelligence in agriculture market is expected to reach $6,655.1 million by 2026, with a CAGR of 30.56% during the forecast period 2021-2026. The growth rate in the market is because of the increased awareness of artificial intelligence-based solutions in some regions of the world.

Impact of COVID-19

The supply chain for the majority of the industries across the globe got impacted due to the COVID-19 pandemic, including the artificial intelligence in agriculture industry. During the COVID-19 outbreak, the supply chain of the agriculture industry was disrupted. During the COVID-19 pandemic, agricultural production was hindered for farmers, which led to a decrease in their revenue generation. This has left the farmers in no position to invest in modern agricultural equipment.

Market Segmentation

AI in Agriculture Market by Farming Type

The farming type segment in the application for artificial intelligence in agriculture market is expected to be dominated by field farming. The majority of the farmers around the world still engage in traditional farming, which is expected to drive artificial intelligence in agriculture market in the forecast period.

AI in Agriculture Market by End Use

The end use segment in the application of artificial intelligence in agriculture market is expected to be dominated by crops, fruits, vegetables, and other plants. The primary focus of all farmers around the world is to increase agricultural production, which is expected to increase the adoption of artificial intelligence products in the agricultural industry.

AI in Agriculture Market by Product

The global artificial intelligence in agriculture market in the product segment is expected to be dominated by software products. The high market share and growth potential associated with software products in the agriculture industry is expected to drive the global artificial intelligence in agriculture market.

AI in Agriculture Market by Region

North America generated the highest revenue of $598.7 million in 2020, which is attributed to the technological advancements in the North America region. In the region, government support along with technological advancement has helped in the growth of the market. The region is expected to witness high growth of CAGR 29.88% during the forecast period 2021-2026.

Key Market Players and Competition Synopsis

Some of the key players operating in the market include Agrivi, Alibaba Group Holding Limited, Ceres Imaging, CNH Industrial N.V., Granular Inc., Harvest Crop Robotics, LLC, IBM Corporation, Microsoft Corporation, Prospera Technologies, Robert Bosch GmbH, The Climate Corporation., among others.

The companies that are profiled in the report have been selected based on the selective pool of players, primarily Tier-1 (holding 50-60% of the market), mid-segment players (comprising 30-40% share), and small and emerging companies (holding the balance 10-20% share), based on various factors such as product portfolio, annual revenues, market penetration, research, and development initiatives, along with a domestic and international presence in the artificial intelligence in agriculture industry.

Artificial Intelligence in Agriculture Market - A Global and Regional Analysis

Focus on Product, Application, and Country Analysis - Analysis and Forecast, 2020-2026

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Some Faq's

Frequently Asked Questions

The global artificial intelligence in agriculture market is expected to reach $6,655.1 million by 2026, with a CAGR of 30.56% during the forecast period 2021-2026.

The top market players are Deere & Company, Microsoft Corporation, CNH Industrial N.V., Robert Bosch GmbH, Granular Inc., Harvest Crop Robotics, LLC, Agrivi, CropIn Technology Solutions Pvt Ltd., Alibaba Group Holding Limited, The Climate Corporation, Descartes Labs, Inc., PrecisionHawk, Inc., Ceres Imaging, IBM Corporation, Prospera Technologies.

Factors driving the growth of the artificial intelligence in agriculture market are need for increased agricultural production, complexities in data-driven farming, and increased demand for automation in agriculture.

Some of the main challenges restricting the growth of the artificial intelligence in agriculture market are data privacy concerns among farmers, and lack of required infrastructure in developing countries.

The potential opportunities that are likely to boost the growth of the artificial intelligence in agriculture market are increased government initiatives supporting AI in agriculture, increased implementation of robots and drones in agriculture, and rise in adoption of SaaS business model in agriculture.

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