Artificial Intelligence in Agriculture Market

Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, Hardware, AI-as-a-Service, and Services), Application, and Geography - Global Forecast to 2026

Report Code: SE 5832 Apr, 2020, by marketsandmarkets.com

The overall AI in agriculture market is projected to grow from an estimated USD 1.0 billion in 2020 to USD 4.0 billion by 2026, at a CAGR of 25.5% between 2020 and 2026. The market growth is propelled by the increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep-learning technology, and government support for the adoption of modern agricultural techniques.

AI in Agriculture Market

By technology, machine learning segment to lead AI in agriculture market during forecast period

Machine learning-enabled solutions are being significantly adopted by agricultural organizations and farmers worldwide to enhance their farm productivity and gain a competitive edge in business operations. In the coming years, the application of machine learning in various agricultural practices is expected to rise exponentially.

By offering, software segment to hold largest share of AI in agriculture market during forecast period

The market for the software segment is mainly driven by the integration of mobile technologies with farming techniques, the growing use of AI software to improve farm efficiency, and the rising demand for real-time data management systems.

AI in Agriculture Market

Americas accounted for largest share of AI in agriculture market in 2019

In the Americas, large scale agriculture players are already using AI technology to significantly improve the speed and accuracy of their planting and crop management techniques. Raizen, Brazil’s leading sugar and ethanol producer, recently announced a partnership with Space Time Analytics (Brazil) to use AI to forecast the size of sugarcane harvests.

Key Market Players

International Business Machines Corp. (IBM) (US), Deere & Company (John Deere) (US), Microsoft Corporation (Microsoft) (US), Farmers Edge Inc. (Farmers Edge) (Canada), The Climate Corporation (Climate Corp.) (US), ec2ce (ec2ce) (Spain), Descartes Labs, Inc. (Descartes Labs) (US), AgEagle Aerial Systems (AgEagle) (US), and aWhere Inc. (aWhere) (US) are the key players in the AI in agriculture market.

Deere & Company is one of the key players providing efficient AI solutions for agriculture. It has a strong brand name and a well-established distribution network. The company has adopted acquisition as a key business strategy for its growth. For example, in September 2017, it acquired an artificial intelligence startup Blue River Technology, which develops cutting-edge machine vision tools to help farmers scan fields and assess crops. The company also regularly engages in product enhancements, new product launches, and collaborations with leading industry players. Product enhancements and collaborations are expected to help the company offer innovative and improved technology and performance solutions in precision farming applications, leading to its growth in the AI in agriculture market.

Report Scope

Report Metric

Details

Market size availability years

2017–2026

Base year

2019

Forecast period

2020–2026

Forecast units

Value (USD million/thousand)

Covered segments

Technology, offering, application, and geography

Covered regions

Americas, Europe, APAC, and RoW

Covered companies

International Business Machines Corp. (IBM) (US), Deere & Company (John Deere) (US), Microsoft Corporation (Microsoft) (US), Farmers Edge Inc. (Farmers Edge) (Canada), The Climate Corporation (Climate Corp.) (US), ec2ce (ec2ce) (Spain), Descartes Labs, Inc. (Descartes Labs) (US), AgEagle Aerial Systems (AgEagle) (US), aWhere Inc. (aWhere) (US), Gamaya Inc. (Gamaya) (Switzerland), Precision Hawk Inc. (Precision Hawk) (US), Granular, Inc. (Granular) (US), Prospera Technologies (Prospera) (Israel), Cainthus Corporation (Cainthus) (Ireland), Taranis (Taranis) (Israel), Resson Inc. (Resson) (Canada), FarmBot Inc. (FarmBot) (US), Connecterra B.V. (Connecterra) (Netherlands), Vision Robotics Corporation (Vision Robotics) (US), Harvest Croo, LLC (Harvest Croo) (US), Autonomous Tractor Corporation (ATC) (US), Trace Genomics, Inc. (Trace Genomics) (US), VineView (VineView) (Canada), CropX Inc. (CropX) (Israel), Tule Technologies Inc. (Tule Technologies) (US), and PEAT GmbH (PEAT) (Germany).

AI in agriculture market segmentation:

 In this report, the AI in agriculture market has been segmented into the following categories:

Based on technology:

  • Machine Learning
  • Computer Vision
  • Predictive Analytics

Based on offering:

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

Based on application:

  • Precision Farming
  • Agriculture Robots
  • Livestock Monitoring
  • Drone Analytics
  • Labor Management
  • Others

Based on region:

  • Americas
  • Europe
  • Asia Pacific (APAC)
  • Rest of the World (RoW)

Recent Developments

  • In March 2020, Farmers Edge and Nufarm Brasil, a leading crop protection company, announced an exclusive, three-year partnership to digitize at least three million acres of farmland in Brazil by 2023. Leveraging the strengths of both companies, Farmers Edge and Nufarm will provide improved crop protection, and the modern tools growers need for making better-informed agronomic decisions to maximize profitability.
  • In January 2020, IBM and Yara International (Norway), a global leader in crop nutrition and digital farming solutions, invited farmer associations, industry players, academia, and NGOs from the food and agriculture industry to join a movement to develop an open data exchange that facilitates collaboration around farm and field data, with the aim of improving the efficiency, transparency, and sustainability of global food production.
  • In January 2020, Deere & Company announced the list for its startup collaborator program. The startup companies included are DataFarm (Brazil), FaunaPhotonics (Denmark), Fieldin (Israel), and EarthSense (US). This program will help the company leverage technologies offered by the startups and provide value to customers.

Critical Questions Answered by the Report:

  • How will these developments impact the AI in agriculture market in the mid- and long-term?
  • What are the prevalent trends in the AI in agriculture market?
  • What are the key strategies adopted by leading companies in the AI in agriculture market?

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

TABLE OF CONTENTS

1 INTRODUCTION (Page No. - 18)
    1.1 STUDY OBJECTIVES
    1.2 DEFINITION
    1.3 STUDY SCOPE
           1.3.1 MARKETS COVERED
           1.3.2 GEOGRAPHIC SCOPE
    1.4 YEARS CONSIDERED FOR STUDY
    1.5 CURRENCY
    1.6 LIMITATIONS
    1.7 STAKEHOLDERS

2 RESEARCH METHODOLOGY (Page No. - 22)
    2.1 RESEARCH DATA
           2.1.1 SECONDARY DATA
                    2.1.1.1 Major secondary sources
                    2.1.1.2 Key data from secondary sources
           2.1.2 PRIMARY DATA
                    2.1.2.1 Primary interviews with experts
                    2.1.2.2 Breakdown of primaries
                    2.1.2.3 Key data from primary sources
                    2.1.2.4 Key industry insights
           2.1.3 SECONDARY AND PRIMARY RESEARCH
    2.2 MARKET SIZE ESTIMATION
           2.2.1 BOTTOM-UP APPROACH
                    2.2.1.1 Approach for capturing market share by bottom-up analysis (demand side)
           2.2.2 TOP-DOWN APPROACH
                    2.2.2.1 Approach for capturing market share by top-down analysis (supply side)
    2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
    2.4 RESEARCH ASSUMPTIONS

3 EXECUTIVE SUMMARY (Page No. - 31)

4 PREMIUM INSIGHTS (Page No. - 36)
    4.1 ATTRACTIVE OPPORTUNITIES FOR THE AI IN AGRICULTURE MARKET
    4.2 AI IN AGRICULTURE MARKET, BY OFFERING
    4.3 MARKET, BY TECHNOLOGY
    4.4 MARKET FOR APAC, BY APPLICATION & COUNTRY
    4.5 MARKET, BY GEOGRAPHY

5 MARKET OVERVIEW (Page No. - 39)
    5.1 INTRODUCTION
    5.2 MARKET DYNAMICS
           5.2.1 DRIVERS
                    5.2.1.1 Increasing strain on global food supply owing to rising population
                    5.2.1.2 Increasing implementation of data generation through sensors and aerial images for crops
                    5.2.1.3 Increasing crop productivity through deep learning technology
                    5.2.1.4 Government support to adopt modern agricultural techniques
           5.2.2 RESTRAINTS
                    5.2.2.1 High cost of gathering precise field data
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Developing countries to offer significant growth opportunities
                    5.2.3.2 Use of AI solutions to manage small farms (less than 5 hectares)
           5.2.4 CHALLENGES
                    5.2.4.1 Lack of standardization
                    5.2.4.2 Lack of awareness about AI among farmers
                    5.2.4.3 Limited availability of historical data
    5.3 VALUE CHAIN ANALYSIS
    5.4 IMPACT OF COVID-19 ON AI IN AGRICULTURE MARKET

6 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET, BY TECHNOLOGY (Page No. - 47)
    6.1 INTRODUCTION
    6.2 MACHINE LEARNING
           6.2.1 MACHINE LEARNING TECHNOLOGY TO HOLD THE LARGEST SHARE OF MARKET
    6.3 COMPUTER VISION
           6.3.1 COMPUTER VISION TECHNOLOGY IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
    6.4 PREDICTIVE ANALYTICS
           6.4.1 INCREASING PREDICTIVE ANALYTICS APPLICATIONS IS EXPECTED TO DRIVE THE GROWTH OF MARKET

7 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET, BY OFFERING (Page No. - 52)
    7.1 INTRODUCTION
    7.2 HARDWARE
           7.2.1 TECHNOLOGICAL ADVANCEMENTS IN THE HARDWARE SEGMENT IS LEADING TO THE WIDESPREAD ADOPTION OF AI IN AGRICULTURE
           7.2.2 PROCESSOR
           7.2.3 STORAGE DEVICE
           7.2.4 NETWORK
    7.3 SOFTWARE
           7.3.1 MARKET FOR SOFTWARE SEGMENT IS PROJECTED TO HOLD THE LARGEST MARKET SHARE DURING THE FORECAST PERIOD
           7.3.2 AI PLATFORM
           7.3.3 AI SOLUTION
    7.4 AI-AS-A-SERVICE
           7.4.1 AI-AS-A-SERVICE SEGMENT IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
    7.5 SERVICES
           7.5.1 INCREASING REQUIREMENT OF ONLINE AND OFFLINE SUPPORT SERVICES IS LEADING TO THE GROWTH OF THIS SEGMENT
           7.5.2 DEPLOYMENT & INTEGRATION
           7.5.3 SUPPORT & MAINTENANCE

8 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET, BY APPLICATION (Page No. - 62)
    8.1 INTRODUCTION
    8.2 PRECISION FARMING
           8.2.1 PRECISION FARMING IS EXPECTED TO HOLD THE LARGEST MARKET SHARE DURING THE FORECAST PERIOD
           8.2.2 YIELD MONITORING
           8.2.3 FIELD MAPPING
           8.2.4 CROP SCOUTING
           8.2.5 WEATHER TRACKING & FORECASTING
           8.2.6 IRRIGATION MANAGEMENT
    8.3 LIVESTOCK MONITORING
           8.3.1 INCREASING LIVESTOCK MONITORING APPLICATIONS IS DRIVING THE GROWTH OF THIS SEGMENT
    8.4 DRONE ANALYTICS
           8.4.1 DRONE ANALYTICS APPLICATION EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
    8.5 AGRICULTURE ROBOTS
           8.5.1 INCREASED DEEP LEARNING CAPABILITIES OF AGRICULTURE ROBOTS IS DRIVING THE GROWTH OF THIS SEGMENT
    8.6 LABOR MANAGEMENT
           8.6.1 MAJOR BENEFITS SUCH AS REDUCED PRODUCTION COSTS DUE TO LABOR MANAGEMENT APPLICATION IS LEADING TO THE GROWTH OF THIS SEGMENT
    8.7 OTHERS
           8.7.1 SMART GREENHOUSE MANAGEMENT
           8.7.2 SOIL MANAGEMENT
                    8.7.2.1 Moisture monitoring
                    8.7.2.2 Nutrient monitoring
           8.7.3 FISH FARMING MANAGEMENT

9 GEOGRAPHIC ANALYSIS (Page No. - 87)
    9.1 INTRODUCTION
    9.2 AMERICAS
           9.2.1 NORTH AMERICA
                    9.2.1.1 US
                               9.2.1.1.1 US projected to account for the largest size of the market in North America
                    9.2.1.2 Canada
                               9.2.1.2.1 Increasing AI technology adoption is leading to the growth of Canadian market
                    9.2.1.3 Mexico
                               9.2.1.3.1 market in Mexico is projected to grow at the highest CAGR during the forecast period
           9.2.2 SOUTH AMERICA
                    9.2.2.1 Brazil
                               9.2.2.1.1 Brazil expected to hold the largest share in the South American market
                    9.2.2.2 Argentina
                               9.2.2.2.1 Expanding industrial production in Argentina is driving the market
                    9.2.2.3 Rest of South America
    9.3 EUROPE
           9.3.1 UK
                    9.3.1.1 Increasing adoption of AI-based solutions for agriculture is driving the UK market
           9.3.2 GERMANY
                    9.3.2.1 Germany held the largest share of European market in 2019
           9.3.3 FRANCE
                    9.3.3.1 Increasing number of start-ups developing AI solutions for agriculture is driving the market in Europe
           9.3.4 ITALY
                    9.3.4.1 market in Italy is growing steadily to overcome drastic climate conditions
           9.3.5 SPAIN
                    9.3.5.1 Favorable government policies are driving the market in Spain
           9.3.6 REST OF EUROPE
    9.4 ASIA PACIFIC
           9.4.1 AUSTRALIA
                    9.4.1.1 Australia expected to hold the largest share of the market in APAC
           9.4.2 CHINA
                    9.4.2.1 Increasing precision farming applications in China is expected to drive the market for APAC
           9.4.3 JAPAN
                    9.4.3.1 In 2019, Japan held the second-largest share of market in APAC
           9.4.4 SOUTH KOREA
                    9.4.4.1 Government funding and initiatives are driving the growth of market in South Korea
           9.4.5 INDIA
                    9.4.5.1 India is expected to be the fastest-growing market in APAC
           9.4.6 REST OF APAC
    9.5 REST OF THE WORLD
           9.5.1 INCREASING AWARENESS AMONG FARMERS REGARDING THE BENEFITS OF AI ASSISTED AGRICULTURAL OPERATIONS IS DRIVING THE MARKET IN ROW

10 COMPETITIVE LANDSCAPE (Page No. - 106)
     10.1 OVERVIEW
     10.2 RANKING ANALYSIS
     10.3 COMPETITIVE SCENARIO
             10.3.1 PRODUCT LAUNCHES AND DEVELOPMENTS
             10.3.2 PARTNERSHIPS, AGREEMENTS, AND COLLABORATIONS
             10.3.3 MERGERS AND ACQUISITIONS
     10.4 COMPETITIVE LEADERSHIP MAPPING
             10.4.1 VISIONARY LEADERS
             10.4.2 DYNAMIC DIFFERENTIATORS
             10.4.3 INNOVATORS
             10.4.4 EMERGING COMPANIES

11 COMPANY PROFILES (Page No. - 113)
     11.1 KEY PLAYERS
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, MnM View)*
             11.1.1 IBM
             11.1.2 DEERE & COMPANY
             11.1.3 MICROSOFT
             11.1.4 THE CLIMATE CORPORATION
             11.1.5 FARMERS EDGE
             11.1.6 GRANULAR
             11.1.7 AGEAGLE
             11.1.8 DESCARTES LABS
             11.1.9 PROSPERA
             11.1.10 TARANIS
             11.1.11 AWHERE
     11.2 RIGHT-TO-WIN
     11.3 OTHER KEY COMPANIES
             11.3.1 GAMAYA
             11.3.2 EC2CE
             11.3.3 PRECISION HAWK
             11.3.4 VINEVIEW
             11.3.5 CAINTHUS
             11.3.6 TULE TECHNOLOGIES
             11.3.7 RESSON
             11.3.8 CONNECTERRA
             11.3.9 VISION ROBOTICS
             11.3.10 FARMBOT
             11.3.11 HARVEST CROO
             11.3.12 PEAT
             11.3.13 AUTONOMOUS TRACTOR CORPORATION
             11.3.14 TRACE GENOMICS
             11.3.15 CROPX TECHNOLOGIES

*Business Overview, Products Offered, Recent Developments, SWOT Analysis, MnM View might not be captured in case of unlisted companies.


12 APPENDIX (Page No. - 145)
     12.1 INSIGHTS OF INDUSTRY EXPERTS
     12.2 DISCUSSION GUIDE
     12.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
     12.4 AVAILABLE CUSTOMIZATIONS
     12.5 RELATED REPORTS
     12.6 AUTHOR DETAILS

List of Tables (81 Tables)

TABLE 1 AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2017–2026 (USD MILLION)
TABLE 2 MARKET FOR MACHINE LEARNING TECHNOLOGY, BY REGION, 2017–2026 (USD MILLION)
TABLE 3 MARKET FOR COMPUTER VISION TECHNOLOGY, BY REGION, 2017–2026 (USD MILLION)
TABLE 4 MARKET FOR PREDICTIVE ANALYTICS TECHNOLOGY, BY REGION, 2017–2026 (USD MILLION)
TABLE 5 MARKET, BY OFFERING, 2017–2026 (USD MILLION)
TABLE 6 MARKET FOR HARDWARE, BY TYPE, 2017–2026 (USD MILLION)
TABLE 7 MARKET FOR HARDWARE, BY REGION, 2017–2026 (USD MILLION)
TABLE 8 MARKET FOR PROCESSOR, BY TYPE, 2017–2026 (USD MILLION)
TABLE 9 MARKET FOR SOFTWARE, BY TYPE, 2017–2026 (USD MILLION)
TABLE 10 MARKET FOR SOFTWARE, BY REGION, 2017–2026 (USD MILLION)
TABLE 11 MARKET, BY PLATFORM TYPE, 2017–2026 (USD MILLION)
TABLE 12 AI SOLUTION MARKET, BY DEPLOYMENT TYPE, 2017–2026 (USD MILLION)
TABLE 13 MARKET FOR SERVICES, BY TYPE, 2017–2026 (USD MILLION)
TABLE 14 MARKET FOR SERVICES, BY REGION, 2017–2026 (USD MILLION)
TABLE 15 MARKET, BY APPLICATION, 2017–2026 (USD MILLION)
TABLE 16 PRECISION FARMING: AI IN AGRICULTURE MARKET, BY REGION 2017–2026 (USD MILLION)
TABLE 17 PRECISION FARMING: MARKET, BY TYPE, 2017–2026 (USD MILLION)
TABLE 18 PRECISION FARMING: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 19 PRECISION FARMING: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 20 PRECISION FARMING: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 21 PRECISION FARMING: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 22 PRECISION FARMING: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 23 PRECISION FARMING: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 24 LIVESTOCK MONITORING: MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 25 LIVESTOCK MONITORING: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 26 LIVESTOCK MONITORING: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026, (USD MILLION)
TABLE 27 LIVESTOCK MONITORING: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 28 LIVESTOCK MONITORING: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 29 LIVESTOCK MONITORING: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 30 LIVESTOCK MONITORING: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 31 DRONE ANALYTICS: AI IN AGRICULTURE MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 32 DRONE ANALYTICS: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 33 DRONE ANALYTICS: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 34 DRONE ANALYTICS: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 35 DRONE ANALYTICS: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 36 DRONE ANALYTICS: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 37 DRONE ANALYTICS: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 38 AGRICULTURE ROBOTS: MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 39 AGRICULTURE ROBOTS: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 40 AGRICULTURE ROBOTS: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 41 AGRICULTURE ROBOTS: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 42 AGRICULTURE ROBOTS: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 43 AGRICULTURE ROBOTS: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 44 AGRICULTURE ROBOTS: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 45 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 46 LABOR MANAGEMENT: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 47 LABOR MANAGEMENT: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 48 LABOR MANAGEMENT: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 49 LABOR MANAGEMENT: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 50 LABOR MANAGEMENT: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 51 LABOR MANAGEMENT: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 52 OTHER APPLICATIONS: MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 53 OTHER APPLICATIONS: MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 54 OTHER APPLICATIONS: MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 55 OTHER APPLICATIONS: MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 56 OTHER APPLICATIONS: MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 57 OTHER APPLICATIONS: MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 58 OTHER APPLICATIONS: MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 59 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET, BY REGION, 2017–2026 (USD MILLION)
TABLE 60 MARKET IN AMERICAS, BY APPLICATION, 2017–2026 (USD MILLION)
TABLE 61 MARKET IN AMERICAS, BY TECHNOLOGY, 2017–2026 (USD MILLION)
TABLE 62 MARKET IN AMERICAS, BY OFFERING, 2017–2026 (USD MILLION)
TABLE 63 MARKET IN AMERICAS, BY REGION, 2017–2026 (USD MILLION)
TABLE 64 MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 65 MARKET IN SOUTH AMERICA, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 66 MARKET IN EUROPE, BY APPLICATION, 2017–2026 (USD MILLION)
TABLE 67 MARKET IN EUROPE, BY TECHNOLOGY, 2017–2026 (USD MILLION)
TABLE 68 MARKET IN EUROPE, BY OFFERING, 2017–2026 (USD MILLION)
TABLE 69 MARKET IN EUROPE, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 70 MARKET IN ASIA PACIFIC, BY APPLICATION, 2017–2026 (USD MILLION)
TABLE 71 MARKET IN ASIA PACIFIC, BY TECHNOLOGY, 2017–2026 (USD MILLION)
TABLE 72 MARKET IN ASIA PACIFIC, BY OFFERING, 2017–2026 (USD MILLION)
TABLE 73 MARKET IN ASIA PACIFIC, BY COUNTRY, 2017–2026 (USD MILLION)
TABLE 74 MARKET IN ROW, BY APPLICATION, 2017–2026 (USD MILLION)
TABLE 75 MARKET IN ROW, BY TECHNOLOGY, 2017–2026 (USD MILLION)
TABLE 76 MARKET IN ROW, BY OFFERING, 2017–2026 (USD MILLION)
TABLE 77 MARKET IN ROW, BY REGION, 2017–2026 (USD MILLION)
TABLE 78 RANKING ANALYSIS OF TOP 5 PLAYERS IN MARKET
TABLE 79 PRODUCT LAUNCHES AND DEVELOPMENTS, AUGUST 2018– DECEMBER 2019
TABLE 80 PARTNERSHIPS, AGREEMENTS, AND COLLABORATIONS, NOVEMBER 2019–MARCH 2020
TABLE 81 ACQUISITIONS, SEPTEMBER 2017–SEPTEMBER 2018

List of Figures (40 Figures)

FIGURE 1 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET SEGMENTATION
FIGURE 2 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET: RESEARCH DESIGN
FIGURE 3 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH
FIGURE 5 MARKET BREAKDOWN AND DATA TRIANGULATION
FIGURE 6 ASSUMPTIONS FOR RESEARCH STUDY
FIGURE 7 GLOBAL MARKET SIZE, 2017–2026 (USD MILLION)
FIGURE 8 BY OFFERING, SOFTWARE SEGMENT TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD
FIGURE 9 BY APPLICATION, DRONE ANALYTICS SEGMENT TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD
FIGURE 10 BY TECHNOLOGY, COMPUTER VISION SEGMENT TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD
FIGURE 11 MARKET IN APAC EXPECTED TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD
FIGURE 12 MARKET IS PROJECTED TO WITNESS A HIGH GROWTH RATE BETWEEN 2020 AND 2026
FIGURE 13 SOFTWARE HELD THE LARGEST MARKET SHARE IN 2019
FIGURE 14 MACHINE LEARNING TECHNOLOGY TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD
FIGURE 15 AUSTRALIA EXPECTED TO HOLD THE LARGEST MARKET SHARE IN APAC IN 2019
FIGURE 16 US HELD THE LARGEST SHARE OF THE MARKET IN 2019
FIGURE 17 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
FIGURE 18 AMOUNT OF DATA GENERATED BY IOT-CONNECTED FARMS GLOBALLY, PER DAY
FIGURE 19 VALUE CHAIN ANALYSIS: MAJOR VALUE IS ADDED DURING COMPONENT DEVELOPMENT AND DEVICE INTEGRATION PHASE
FIGURE 20 COMPUTER VISION TECHNOLOGY TO REGISTER THE HIGHEST CAGR BETWEEN 2020 AND 2026
FIGURE 21 AMERICAS TO HOLD THE LARGEST MARKET SIZE FOR COMPUTER VISION TECHNOLOGY BETWEEN 2020 AND 2026
FIGURE 22 HARDWARE SEGMENT TO GROW AT THE HIGHEST RATE BETWEEN 2020 AND 2026
FIGURE 23 BY SOFTWARE, AI PLATFORM EXPECTED TO WITNESS A HIGHER CAGR THAN AI SOLUTION DURING THE FORECAST PERIOD
FIGURE 24 AMERICAS TO HOLD THE LARGEST SIZE OF THE MARKET FOR SERVICES DURING THE FORECAST PERIOD
FIGURE 25 DRONE ANALYTICS APPLICATION PROJECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
FIGURE 26 MARKET FOR PRECISION FARMING APPLICATION IN REST OF EUROPE EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
FIGURE 27 AMERICAS TO DOMINATE THE MARKET FOR LIVESTOCK MONITORING APPLICATION BETWEEN 2020 AND 2026
FIGURE 28 ASIA PACIFIC TO EXHIBIT THE HIGHEST GROWTH IN THE MARKET FOR DRONE ANALYTICS APPLICATION DURING THE FORECAST PERIOD
FIGURE 29 AMERICAS TO HOLD THE LARGEST MARKET SIZE FOR AGRICULTURE ROBOTS APPLICATION BY 2026
FIGURE 30 LABOR MANAGEMENT APPLICATION IN MEXICO TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD
FIGURE 31 AMERICAS TO ACCOUNT FOR THE LARGEST SIZE OF THE MARKET IN OTHER APPLICATIONS BY 2026
FIGURE 32 GEOGRAPHIC SNAPSHOT: RAPIDLY GROWING ECONOMIES, SUCH AS AUSTRALIA, CHINA, AND INDIA, ARE EMERGING AS NEW HOTSPOTS FOR THE MARKET
FIGURE 33 AMERICAS: MARKET SNAPSHOT
FIGURE 34 EUROPE: MARKET SNAPSHOT
FIGURE 35 ASIA PACIFIC: AI IN AGRICULTURE MARKET SNAPSHOT
FIGURE 36 PARTNERSHIPS, AGREEMENTS, AND COLLABORATIONS WERE KEY GROWTH STRATEGIES ADOPTED BY COMPANIES FROM SEPTEMBER 2017 TO MARCH 2020
FIGURE 37 MARKET (GLOBAL) COMPETITIVE LEADERSHIP MAPPING, 2019
FIGURE 38 IBM: COMPANY SNAPSHOT
FIGURE 39 DEERE & COMPANY: COMPANY SNAPSHOT
FIGURE 40 MICROSOFT: COMPANY SNAPSHOT

The study involved the estimation of the current size of the AI in agriculture market. Exhaustive secondary research was conducted to collect information on the market, its peer markets, and its parent market. This was followed by the validation of these findings, assumptions, and sizing with the industry experts identified across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the overall size of the market. It was followed by the market breakdown and data triangulation procedures, which were used to estimate the size of the market based on different segments and subsegments.

Secondary Research

In the secondary research process, various secondary sources were referred for the identification and collection of relevant information for this study on the AI in agriculture market. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers; journals and certified publications; and articles by recognized authors, websites, directories, and databases. Secondary research was conducted to obtain the key information regarding the supply chain and value chain of the industry, total pool of key players, market segmentation according to industry trends (to the bottom-most level), geographic markets, and key developments from the market- and technology-oriented perspectives. Secondary data was collected and analyzed to arrive at the overall size of the AI in agriculture market, which was further validated by primary research.

Primary Research

In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information relevant to this report. Several primary interviews were conducted with the market experts from both sides. The primary data was collected through questionnaires, emails, and telephonic interviews. Primary sources included industry experts, such as chief executive officers (CEOs), vice presidents (VPs), marketing directors, technology and innovation directors, and related executives from various key companies and organizations operating in the AI in agriculture market.

AI in Agriculture Market

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Top-down and bottom-up approaches were implemented to estimate and validate the total size of the AI in agriculture market. These methods were used extensively to estimate the size of the market based on various segments and subsegments. The research methodology used to estimate the market size included the following steps:

  • Key players in the industry were identified through extensive secondary research.
  • The industry’s supply chain was identified, and the market size, in terms of value, was determined through primary and secondary research processes.
  • All percentage shares, splits, and breakdowns were determined using secondary sources and verified through primary sources.

Data Triangulation

After arriving at the overall size of the AI in agriculture market—using the market size estimation processes as explained above—the market was split into several segments and subsegments. Data triangulation and market breakdown procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment. The data was triangulated by studying various factors and trends from the demand and supply sides across different applications.

Study Objectives

  • To describe and forecast the AI in agriculture market, in terms of value and volume, based on offering, technology, and application
  • To describe and forecast the market size for four major regions— Americas, Europe, Asia Pacific (APAC), and Rest of the World (RoW)
  • To provide detailed information regarding the major factors, such as drivers, restraints, opportunities, and challenges, influencing the growth of the market
  • To analyze opportunities in the AI in agriculture market for stakeholders and provide a detailed competitive landscape of the market for the leading players
  • To strategically profile the key players operating in the market and comprehensively analyze their core competencies
  • To map the competitive intelligence based on the company profiles, as well as key growth strategies adopted and game-changing developments, such as product developments, collaborations, and acquisitions, undertaken in the market
COVID-19

Get in-depth analysis of the COVID-19 impact on the Artificial Intelligence in Agriculture Market

Benchmarking the rapid strategy shifts of the Top 100 companies in the Artificial Intelligence in Agriculture Market

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Apr, 2020
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