Artificial Intelligence in Agriculture Market Size, Share and Growth

Artificial Intelligence in Agriculture Market Size, Share & Industry Growth Analysis Report by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, AI-as-a-Service), Application (Drone Analytics, Precision Farming) and Region - Global Forecast to 2028

Report Code: SE 5832 Feb, 2023, by marketsandmarkets.com

Updated on : October 22, 2024

Artificial Intelligence in Agriculture Market Size & Growth

The AI in Agriculture Market size is projected to grow from USD 1.7 billion in 2023 to USD 4.7 billion by 2028; growing at a Compound Annual Growth Rate (CAGR) of 23.1% from 2023 to 2028.

AI in agriculture offers several advantages to the farmers such as real-time insights from their fields, monitor soil quality, plant health, temperature, automate irrigation, pesticide process- all of which are helping to improve the overall harvest quality and accuracy. AI in agriculture has various applications aimed at optimizing the efficiency of crop production such as precision farming, livestock monitoring, drone analytics, agriculture robots, labor management.  Increasing crop productivity through deep learning technology driving the growth of the market.

The objective of the report is to define, describe, and forecast the AI in agriculture market share based on technology, offering, application and region.

Artificial Intelligence in Agriculture Market

Artificial Intelligence in Agriculture Market Forecast to 2028

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Artificial Intelligence in Agriculture Market Trends:

Rising need for real-time data by growers and farmers to take preventive measures

Increasing agricultural activities and the growing need for real-time data largely drive the market for AI in agriculture. Real-time data from agricultural farms help make prompt decisions regarding preventive measures. Farmers from North America, South America, and Europe use sensors, drones, guidance technologies, and soil sampling techniques to gather data on soil moisture and nutrient levels across their fields. Farmers and growers from the US, Canada, Brazil, and most Western European countries are turning to high-tech tools for data collection and data analysis. Drone-enabled scouting is one of the most convenient ways of collecting farm data.

Government schemes encouraging adoption of AI solutions to manage small farms

There are over 570 million farms worldwide, and 95% of all these farms are less than 5 hectares in size. AI solutions are predominantly implemented in farms with over 100 hectares of land. This can be attributed to the high initial investment required for implementing AI solutions. Farmers owning lands over 100 hectares generally have the capability to invest in AI-based solutions for farm management and other applications. However, with governments around the world supporting the use of AI for agricultural applications and providing aid to farmers with small farms, there is an opportunity for solution providers to focus on farms with less than 5 hectares of land. For instance, in the US, the Department of Agriculture provides small and mid-size producers with programs that avail farmers with easy loans and improve their technological know-how to use the best technology for farming.

High cost of AI-driven precision farming equipment

The major restraining factor for the AI in agricultural market is the high cost of AI-enabled farming products and solutions, including sensors, software, and robots. Many factors are responsible for the high cost of gathering precise field data. For instance, companies develop AI-powered solutions or platforms according to customer requirements. They offer AI-powered prebuilt and custom-built solutions such as analytics systems, virtual assistants, and chatbots. Similarly, AI features and AI management are also important factors that incur additional costs.

Availability of limited workforce with technological expertise

Artificial intelligence (AI) is a complex system, and for developing, managing, and successfully implementing AI systems, farmers require certain skill sets. For instance, people dealing with AI systems should know about technologies such as cognitive computing, machine learning, deep learning, and image recognition. In addition, the integration of AI solutions in existing systems is a difficult task that requires extensive data processing to replicate the behavior of a human brain. Even a minor error can result in system failure or adversely affect the desired result.

Artificial Intelligence in Agriculture Market Segmentation

Machine learning enabled AI in agriculture contributes largest market share through the forecast period.”

Machine learning-enabled solutions are being significantly adopted by agricultural organizations and farmers worldwide to enhance farm productivity and to gain a competitive edge in business operations. Technological advancement and proliferation in farm data generation are some of the major driving factors for the AI in agriculture market. With the use of machine learning farmers able to capture the factor of soil, seeds quality fertilizer application, environmental variables and irrigation.

AI in agriculture market for software segment is to hold the largest market share through the forecast period.

AI in agriculture market share has been segmented based on offerings into hardware, software, AI-as-a-service, and service. Software segment is to hold the largest market share through the forecast period. The software integrated into a computer system is responsible for carrying out complex operations. It synthesizes the data received from the hardware and processes it in the AI system to generate an intelligent response. Furthermore software segment is segmented into AI platform and AI solution. Where in AI platform data is combined with a decision-making algorithm to enable developers to create a business solution.

Precision farming application of AI in agriculture to hold significant share during the forecast period”

The market for precision farming applications was valued at USD 542 million in 2022 and is projected to reach USD 1,432 million by 2028; it is expected to grow at a CAGR of 20.5% during the forecast period. This segment is likely to continue to hold the second-largest market share in the coming years due to the high adoption rate of AI technologies for precision farming applications. Precision farming and automatization in food production are priorities for food growers in the current situation, and AI fuels the gains.

Market for computer vision technology based AI products is expected to grow at highest CAGR during forecasted period.

The AI in agriculture market has been segmented based on technology into machine learning, computer vision, and predictive analytics. Market for computer vision technology based AI products is expected to grow at highest CAGR during forecasted period. This high growth rate is attributed to the rising need for continuous monitoring and analysis of crop health and increasing use of computer vision technology in agricultural applications such as sorting the produce according to weight, color, size, and ripeness and identifying defects in agricultural produce.

Artificial Intelligence in Agriculture Industry Regional Analysis

North America is to contribute the largest in the market during the forecast period

The North America held the largest market share during the forecast period. The AI in agriculture industry in this region has been segmented into US, Canada and Mexico. North America has large scale agriculture players in the region are already using AI technology to significantly improve the speed and accuracy of their planting and crop management techniques. The demand for advanced agricultural solutions is expected to drive the growth of the AI in agriculture market in this region.

Artificial Intelligence in Agriculture Market by Region

Artificial Intelligence in Agriculture Market by Region

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In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews have been conducted with key industry experts in the AI in agriculture market space. The break-up of primary participants for the report has been shown below:

  • By Company Type: Tier 1 – 45%, Tier 2 – 35%, and Tier 3 – 20%
  • By Designation: C-level Executives – 35%, Directors – 43%, and Others – 22%
  • By Region: North America –33%, Asia Pacific– 30%, Europe – 24%, and RoW – 13%

Top Artificial Intelligence in Agriculture Companies - Key Market Players

  • Deere & Company (US),
  • IBM (US),
  • Microsoft (US),
  • The Climate Corporation (US),
  • Farmers Edge Inc. (Canada),
  • Granular Inc. (Canada), 
  • AgEagle Aerial Syatems Inc. (US),
  • Descartes Labs, Inc. (US).

Artificial Intelligence in Agriculture Market Report Scope

Report Metric

Details

Estimated Market Size

USD 1.7 billion in 2023

Expected Market Size

USD 4.7 billion by 2028

Growth Rate

CAGR of 23.1%

Market size available for years

2019—2028

Base year

2022

Forecast period

2023—2028

Units

Value (USD Billion)

Segments covered

Technology, offering, application, and geography.

Geographic regions covered

North America, Europe, Asia Pacific, and RoW

Companies covered

Deere & Company (US), IBM (US), Microsoft (US), The Climate Corporation (US), Farmers Edge Inc. (Canada), Granular Inc. (Canada), AgEagle Aerial Systems Inc. (US), Descartes Labs, Inc. (US) are the major players in the market.
A total of 25 players are profiled in the report.

Artificial Intelligence in Agriculture Market Highlights

This report categorizes the AI in agriculture market share based on technology, offering, application, geography.

Segment

Subsegment

AI in Agriculture Market, by Technology:

  • Machine Learning
  • Computer Vision
  • Predictive Analytics

AI in Agriculture, by Offering:

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

AI in Agriculture Market, by Application:

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

AI in Agriculture Market, by Region:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Europe
  • APAC
    • China
    • Japan
    • South Korea
    • India
    • Australia
    • Rest of APAC
  • RoW
    • Middle East & Africa
    • South America

Recent Developments in Artificial Intelligence in Agriculture Industry

  • In May 2022, Alliance for a Green Revolution in Africa (AGRA) and Microsoft announced the expansion of their partnership to advance digital agriculture transformation in Africa to improve food security. The partnership of AGRA with Microsoft will support governments, farmers, and small and medium-sized enterprises (SMEs) to build food systems in the region by using digital tools provided by Microsoft.
  • In February 2022, Farmers Edge and Deere & Company (US), a manufacturer of agriculture machinery and heavy equipment, entered into an agreement allowing users of FarmCommand to integrate their data with the John Deer Operations Center account. This will give users the insights to make decisions that drive yields and profits.
  • In October 2021, IBM launched the IBM Environment Intelligence Suite, an AI-driven software for environment intelligence that helps companies anticipate the climate risks, such as floods and wildfires, and understand agricultural production and market intelligence by providing weather data, climate risk analytics, and carbon accounting.
  • In March 2021, Climate LLC, a Bayer Crop Science Digital arm subsidiary, launched the industry-leading digital farming platform, climate FieldView, in South Africa. Launching the product in the African region helps the farmers manage risk and increase productivity while simplifying their operations actively.
  • In January 2020, Descartes Labs launched a cloud-based geospatial data refinery and modeling platform called the Descartes Labs Platform. This platform has improved forecasting abilities in agriculture.

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 28)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
    1.3 STUDY SCOPE 
           1.3.1 MARKETS COVERED
                    FIGURE 1 SEGMENTATION OF AI IN AGRICULTURE MARKET
           1.3.2 REGIONAL SCOPE
           1.3.3 YEARS CONSIDERED
    1.4 CURRENCY CONSIDERED 
    1.5 LIMITATIONS 
    1.6 STAKEHOLDERS 
    1.7 SUMMARY OF CHANGES 
 
2 RESEARCH METHODOLOGY (Page No. - 33)
    2.1 RESEARCH DATA 
           FIGURE 2 AI IN AGRICULTURE MARKET: RESEARCH DESIGN
           2.1.1 SECONDARY AND PRIMARY RESEARCH
                    2.1.1.1 Key industry insights
           2.1.2 SECONDARY DATA
                    2.1.2.1 List of major secondary sources
                    2.1.2.2 Secondary sources
           2.1.3 PRIMARY DATA
                    2.1.3.1 Primary interviews with experts
                    2.1.3.2 Breakdown of primaries
                    2.1.3.3 Key data from primary sources
    2.2 MARKET SIZE ESTIMATION 
           FIGURE 3 MARKET SIZE ESTIMATION METHODOLOGY: SUPPLY-SIDE APPROACH
           2.2.1 BOTTOM-UP APPROACH
                    2.2.1.1 Approach to estimate market size using bottom-up analysis (demand side)
                               FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH
           2.2.2 TOP-DOWN APPROACH
                    2.2.2.1 Approach to estimate market size using top-down analysis (supply side)
                               FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH
    2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 
           FIGURE 6 DATA TRIANGULATION
    2.4 RESEARCH ASSUMPTIONS 
           FIGURE 7 RESEARCH STUDY ASSUMPTIONS
           TABLE 1 PARAMETERS CONSIDERED TO ANALYZE IMPACT OF RECESSION ON AI IN AGRICULTURE MARKET
 
3 EXECUTIVE SUMMARY (Page No. - 42)
           FIGURE 8 MACHINE LEARNING TECHNOLOGY TO ACCOUNT FOR LARGEST SHARE OF AI IN AGRICULTURE MARKET IN 2028
           FIGURE 9 SOFTWARE OFFERINGS TO HOLD LARGEST MARKET SHARE THROUGHOUT FORECAST PERIOD
           FIGURE 10 DRONE ANALYTICS APPLICATION TO EXHIBIT HIGHEST CAGR DURING FORECAST PERIOD
           FIGURE 11 NORTH AMERICA ACCOUNTED FOR LARGEST SHARE OF AI IN AGRICULTURE MARKET IN 2022
    3.1 ANALYSIS OF RECESSION IMPACT ON AI IN AGRICULTURE MARKET 
           FIGURE 12 GDP GROWTH PROJECTION TILL 2023 FOR MAJOR ECONOMIES (PERCENTAGE CHANGE)
           FIGURE 13 AI IN AGRICULTURE MARKET: PRE- AND POST-RECESSION SCENARIOS
 
4 PREMIUM INSIGHTS (Page No. - 47)
    4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN AGRICULTURE MARKET 
           FIGURE 14 RISING USE OF DRONES TO INCREASE FARM PRODUCTIVITY AND PROFITABILITY TO PROVIDE OPPORTUNITIES FOR PLAYERS OFFERING AI-POWERED SOLUTIONS
    4.2 AI IN AGRICULTURE MARKET, BY TECHNOLOGY 
           FIGURE 15 COMPUTER VISION TECHNOLOGY TO REGISTER HIGHEST CAGR IN AI IN AGRICULTURE MARKET BETWEEN 2023 AND 2028
    4.3 AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY AND APPLICATION 
           FIGURE 16 US AND DRONE ANALYTICS TO ACCOUNT FOR LARGEST SHARE OF AI IN AGRICULTURE MARKET IN NORTH AMERICA IN 2028
    4.4 REGION-WISE AI IN AGRICULTURE MARKET GROWTH RATE 
           FIGURE 17 ASIA PACIFIC TO RECORD HIGHEST CAGR IN AI IN AGRICULTURE MARKET DURING FORECAST PERIOD
 
5 MARKET OVERVIEW (Page No. - 49)
    5.1 INTRODUCTION 
    5.2 MARKET DYNAMICS 
           FIGURE 18 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
           5.2.1 DRIVERS
                    5.2.1.1 Adoption of newer technologies in arable land to balance food supply and population increase
                    5.2.1.2 Rising need for real-time data by growers and farmers to take preventive measures
                               FIGURE 19 VOLUME OF DATA GENERATED PER DAY BY IOT-CONNECTED FARMS GLOBALLY
                    5.2.1.3 Increasing crop productivity through deep learning technology
                    5.2.1.4 Government support to adopt modern agricultural techniques
                    5.2.1.5 Increasing use of AI-enabled robots and automation in agriculture due to labor shortage
           5.2.2 RESTRAINTS
                    5.2.2.1 High cost of AI-driven precision farming equipment
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Potential growth opportunities in developing countries
                    5.2.3.2 Government schemes encouraging adoption of AI solutions to manage small farms
                    5.2.3.3 Rising use of drones to increase farm productivity and profitability
           5.2.4 CHALLENGES
                    5.2.4.1 Interoperability issues due to lack of standardization of communication protocols
                    5.2.4.2 Availability of limited workforce with technological expertise
                    5.2.4.3 Insufficient historical data to build predictive models
    5.3 VALUE CHAIN ANALYSIS 
           FIGURE 20 VALUE CHAIN ANALYSIS FOR AI IN AGRICULTURE MARKET
    5.4 ECOSYSTEM ANALYSIS 
           FIGURE 21 AI IN AGRICULTURE MARKET: ECOSYSTEM ANALYSIS
           TABLE 2 ECOSYSTEM MAPPING
    5.5 PRICING ANALYSIS 
           TABLE 3 INDICATIVE PRICING ANALYSIS OF AI PRODUCTS OFFERED BY KEY COMPANIES
           FIGURE 22 AVERAGE SELLING PRICE OF PROCESSOR COMPONENTS
           5.5.1 AVERAGE SELLING PRICE ANALYSIS OF PROCESSOR COMPONENTS OFFERED BY TOP 3 PLAYERS
                    FIGURE 23 AVERAGE SELLING PRICE OF PROCESSORS OFFERED BY TOP 3 COMPANIES
                    TABLE 4 ASP RANGE OF PROCESSOR COMPONENTS, 2019–2028
                    TABLE 5 ASP RANGE OF PROCESSOR, BY REGION, 2019–2028 (USD)
    5.6 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 
           FIGURE 24 REVENUE SHIFT AND NEW REVENUE POCKETS FOR PLAYERS IN AI IN AGRICULTURE MARKET
    5.7 TECHNOLOGY ANALYSIS 
           5.7.1 INTERNET OF THINGS (IOT)
           5.7.2 ROBOTICS
           5.7.3 BLOCKCHAIN TECHNOLOGY
           5.7.4 AI-DRIVEN DRONES
    5.8 PORTER’S FIVE FORCES ANALYSIS 
           TABLE 6 AI IN AGRICULTURE MARKET: PORTER’S FIVE FORCES ANALYSIS, 2022
           FIGURE 25 PORTER’S FIVE FORCES ANALYSIS: AI IN AGRICULTURE MARKET
           5.8.1 THREAT OF NEW ENTRANTS
           5.8.2 THREAT OF SUBSTITUTES
           5.8.3 BARGAINING POWER OF SUPPLIERS
           5.8.4 BARGAINING POWER OF BUYERS
           5.8.5 INTENSITY OF COMPETITIVE RIVALRY
    5.9 KEY STAKEHOLDERS AND BUYING CRITERIA 
           5.9.1 KEY STAKEHOLDERS IN BUYING PROCESS
                    FIGURE 26 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP 3 APPLICATIONS
                    TABLE 7 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP 3 APPLICATIONS (%)
    5.10 CASE STUDIES 
           TABLE 8 E&J GALLO (US) ADOPTED IBM CLOUD TO INCREASE YIELDS AND REDUCE WATER USAGE
           TABLE 9 BUNGE (US) IMPLEMENTED IBM PAIRS TO GAIN DATA AND COMPUTING POWER TO BUILD ADVANCED STATISTICAL MODELS
           TABLE 10 AGROPECUÁRIA CANOA MIRIM S/A (BRAZIL) DEPLOYED VARIABLE RATE TECHNOLOGY OFFERED BY FARMERS EDGE TO ENSURE ACCURATE QUANTITY OF FERTILIZERS
    5.11 TRADE ANALYSIS 
           FIGURE 27 EXPORT DATA FOR PRODUCTS COVERED UNDER HS CODE 8432, 2017–2021 (USD MILLION)
           FIGURE 28 IMPORT DATA FOR PRODUCTS COVERED UNDER HS CODE 8432, 2017–2021 (USD MILLION)
    5.12 PATENT ANALYSIS 
           FIGURE 29 NUMBER OF PATENTS GRANTED FROM 2013 TO 2022
           FIGURE 30 TOP 10 PATENT APPLICANT COMPANIES IN LAST 10 YEARS
           TABLE 11 TOP 12 PATENT OWNERS IN LAST 10 YEARS
           TABLE 12 IMPORTANT PATENTS RELATED TO AI IN AGRICULTURE MARKET
    5.13 KEY CONFERENCES AND EVENTS, 2023–2024 
           TABLE 13 ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET: CONFERENCES AND EVENTS, 2023–2024
    5.14 REGULATIONS AND STANDARDS 
           5.14.1 STANDARDS
                    TABLE 14 STANDARDS FOR AI IN AGRICULTURE MARKET
           5.14.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 15 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 16 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 17 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
 
6 AI IN AGRICULTURE MARKET, BY TECHNOLOGY (Page No. - 73)
    6.1 INTRODUCTION 
           FIGURE 31 COMPUTER VISION TECHNOLOGY TO REGISTER HIGHEST CAGR IN AI IN AGRICULTURE MARKET BETWEEN 2023 AND 2028
           TABLE 18 AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION)
           TABLE 19 AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION)
    6.2 MACHINE LEARNING 
           6.2.1 NEED TO MINIMIZE RISKS AND COSTS ASSOCIATED WITH AGRICULTURAL OPERATIONS TO DRIVE DEMAND FOR MACHINE LEARNING TECHNOLOGY
    6.3 COMPUTER VISION 
           6.3.1 USE OF COMPUTER VISION TECHNOLOGY TO MONITOR CROP HEALTH AND PREDICT NUTRIENT DEFICIENCY TO PROVIDE OPPORTUNITIES FOR MARKET PLAYERS
    6.4 PREDICTIVE ANALYTICS 
           6.4.1 ADOPTION OF PREDICTIVE ANALYTICS TECHNOLOGY TO MAKE AGRONOMIC DECISIONS TO DRIVE MARKET
 
7 AI IN AGRICULTURE MARKET, BY OFFERING (Page No. - 77)
    7.1 INTRODUCTION 
           FIGURE 32 AI-AS-A-SERVICE SEGMENT TO EXHIBIT HIGHEST CAGR BETWEEN 2023 AND 2028
           TABLE 20 AI IN AGRICULTURE MARKET, BY OFFERING, 2019–2022 (USD MILLION)
           TABLE 21 AI IN AGRICULTURE MARKET, BY OFFERING, 2023–2028 (USD MILLION)
    7.2 HARDWARE 
           7.2.1 AVAILABILITY OF HIGH-TECH TOOLKITS FOR AGRICULTURAL APPLICATIONS TO BOOST MARKET
                    TABLE 22 HARDWARE: AI IN AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 23 HARDWARE: AI IN AGRICULTURE MARKET, BY TYPE, 2023–2028 (USD MILLION)
           7.2.2 PROCESSOR
                    7.2.2.1 Need for highly advanced processors to run complex algorithms and translate them into useful information
           7.2.3 STORAGE DEVICE
                    7.2.3.1 Requirement for high-capacity storage devices to store critical data generated through sensors and drones
           7.2.4 NETWORK
                    7.2.4.1 Network systems include RAMs, memory boards, Ethernet adaptors, and interconnects
    7.3 SOFTWARE 
           7.3.1 INSTALLATION OF SOFTWARE TO SYNTHESIZE DATA HELPFUL IN MAKING PROMPT DECISIONS TO DRIVE DEMAND
                    TABLE 24 SOFTWARE: AI IN AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 25 SOFTWARE: AI IN AGRICULTURE MARKET, BY TYPE, 2023–2028 (USD MILLION)
           7.3.2 AI PLATFORM
                    7.3.2.1 Adoption of AI platforms to fetch and store data from different sources to create consolidated data environment
           7.3.3 AI SOLUTION
                    7.3.3.1 Commercialization of robust AI solutions by Alphabet, Siemens, Data RPM, and other players to contribute to segmental growth
    7.4 AI-AS-A-SERVICE 
           7.4.1 INCLINATION TOWARD IMPLEMENTING EFFICIENT FARMING METHODS TO REDUCE WASTAGE AND INCREASE CROP YIELD TO DRIVE DEMAND FOR AIAAS
    7.5 SERVICES 
           7.5.1 INCREASING REQUIREMENT FOR ONLINE AND OFFLINE SUPPORT SERVICES TO BOOST SEGMENTAL GROWTH
                    TABLE 26 SERVICES: AI IN AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 27 SERVICES: AI IN AGRICULTURE MARKET, BY TYPE, 2023–2028 (USD MILLION)
           7.5.2 DEPLOYMENT & INTEGRATION
                    7.5.2.1 Rising adoption of software-integrated on-premises and cloud-based platforms by modern farmers to accelerate demand for deployment & integration services
           7.5.3 SUPPORT & MAINTENANCE
                    7.5.3.1 Post-installation requirement to address operations-related issues to drive demand for support & maintenance services
 
8 AI IN AGRICULTURE MARKET, BY APPLICATION (Page No. - 84)
    8.1 INTRODUCTION 
           FIGURE 33 DRONE ANALYTICS SEGMENT TO RECORD HIGHEST CAGR IN AI IN AGRICULTURE MARKET, BY APPLICATION, DURING FORECAST PERIOD
           TABLE 28 AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
           TABLE 29 AI IN AGRICULTURE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
    8.2 PRECISION FARMING 
           8.2.1 FARMERS’ FOCUS ON INCREASING CROP YIELDS USING LIMITED RESOURCES TO INCREASE DEMAND FOR AI IN PRECISION FARMING
                    TABLE 30 PRECISION FARMING: AI IN AGRICULTURE MARKET, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 31 PRECISION FARMING: AI IN AGRICULTURE MARKET, BY TYPE, 2023–2028 (USD MILLION)
                    TABLE 32 PRECISION FARMING: AI IN AGRICULTURE MARKET, BY REGION 2019–2022 (USD MILLION)
                    TABLE 33 PRECISION FARMING: AI IN AGRICULTURE MARKET, BY REGION 2023–2028 (USD MILLION)
                    TABLE 34 PRECISION FARMING: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 35 PRECISION FARMING: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 36 PRECISION FARMING: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 37 PRECISION FARMING: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 38 PRECISION FARMING: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 39 PRECISION FARMING: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 40 PRECISION FARMING: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 41 PRECISION FARMING: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
           8.2.2 YIELD MONITORING
                    8.2.2.1 Integration of advanced sensors into yield monitoring solutions to track moisture and nutrient levels in soil
           8.2.3 FIELD MAPPING
                    8.2.3.1 Adoption of AI-powered field mapping tools to record field boundaries and calculate surface area
           8.2.4 CROP SCOUTING
                    8.2.4.1 Implementation of AI-enabled crop scouting tools to examine crop conditions and gain information on pests and crop injuries
           8.2.5 WEATHER TRACKING & FORECASTING
                    8.2.5.1 Use of weather tracking and forecasting tools to gather information and predict weather conditions
           8.2.6 IRRIGATION MANAGEMENT
                    8.2.6.1 Implementation of AI-based irrigation systems to achieve optimal yield and water conservation
    8.3 LIVESTOCK MONITORING 
           8.3.1 INCORPORATION OF AI IN FEEDING AND HEAT STRESS MANAGEMENT SOLUTIONS AND MILKING ROBOTS TO FUEL MARKET GROWTH
                    TABLE 42 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 43 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 44 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022, (USD MILLION)
                    TABLE 45 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028, (USD MILLION)
                    TABLE 46 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 47 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 48 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 49 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 50 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 51 LIVESTOCK MONITORING: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
    8.4 DRONE ANALYTICS 
           8.4.1 USE OF AI-POWERED DRONES TO IDENTIFY INSECTS AND DISEASES AFFLICTING CROPS TO ACCELERATE MARKET GROWTH
                    TABLE 52 DRONE ANALYTICS: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 53 DRONE ANALYTICS: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 54 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 55 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 56 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 57 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 58 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 59 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 60 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 61 DRONE ANALYTICS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
    8.5 AGRICULTURE ROBOTS 
           8.5.1 INCREASED DEEP LEARNING CAPABILITIES OF AGRICULTURE ROBOTS TO CONTRIBUTE TO MARKET GROWTH
                    TABLE 62 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 63 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 64 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 65 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 66 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 67 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 68 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 69 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 70 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 71 AGRICULTURE ROBOTS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
    8.6 LABOR MANAGEMENT 
           8.6.1 REDUCTION IN PRODUCTION COSTS THROUGH LABOR MANAGEMENT SOFTWARE TO STIMULATE MARKET GROWTH
                    TABLE 72 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 73 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 74 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 75 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 76 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 77 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 78 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 79 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 80 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 81 LABOR MANAGEMENT: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
    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
                    TABLE 82 OTHERS: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 83 OTHERS: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 84 OTHERS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 85 OTHERS: AI IN AGRICULTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 86 OTHERS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 87 OTHERS: AI IN AGRICULTURE MARKET IN EUROPE, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 88 OTHERS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2019–2022 (USD MILLION)
                    TABLE 89 OTHERS: AI IN AGRICULTURE MARKET IN ASIA PACIFIC, BY COUNTRY, 2023–2028 (USD MILLION)
                    TABLE 90 OTHERS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 91 OTHERS: AI IN AGRICULTURE MARKET IN ROW, BY REGION, 2023–2028 (USD MILLION)
 
9 AI IN AGRICULTURE MARKET, BY REGION (Page No. - 112)
    9.1 INTRODUCTION 
           FIGURE 34 ASIA PACIFIC COUNTRIES TO BE PROSPECTIVE MARKETS FOR AI IN AGRICULTURE DURING FORECAST PERIOD
           TABLE 92 AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
           TABLE 93 AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
    9.2 NORTH AMERICA 
           FIGURE 35 NORTH AMERICA: AI IN AGRICULTURE MARKET SNAPSHOT
           TABLE 94 NORTH AMERICA: AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
           TABLE 95 NORTH AMERICA: AI IN AGRICULTURE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
           TABLE 96 NORTH AMERICA: AI IN AGRICULTURE MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
           TABLE 97 NORTH AMERICA: AI IN AGRICULTURE MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
           9.2.1 US
                    9.2.1.1 Presence of giant companies offering AI-powered solutions and services to boost market growth
           9.2.2 CANADA
                    9.2.2.1 Federal investments and favorable regulatory environment framework to propel market
           9.2.3 MEXICO
                    9.2.3.1 Limited water resources to accelerate demand for AI in agriculture sector
    9.3 EUROPE 
           FIGURE 36 EUROPE: AI IN AGRICULTURE MARKET SNAPSHOT
           TABLE 98 EUROPE: AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
           TABLE 99 EUROPE: AI IN AGRICULTURE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
           TABLE 100 EUROPE: AI IN AGRICULTURE MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
           TABLE 101 EUROPE: AI IN AGRICULTURE MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
           9.3.1 UK
                    9.3.1.1 Investments by government in high-tech farming projects to stimulate market growth
           9.3.2 GERMANY
                    9.3.2.1 High adoption of agricultural drones to monitor crops to propel market growth
           9.3.3 FRANCE
                    9.3.3.1 Focus of startup companies on development of advanced technologies for agriculture sector to support market growth
           9.3.4 ITALY
                    9.3.4.1 Limited water resources to encourage use of AI in agriculture sector
           9.3.5 SPAIN
                    9.3.5.1 Government-run pilot projects encouraging adoption of AI in agriculture to boost market growth
           9.3.6 REST OF EUROPE
    9.4 ASIA PACIFIC 
           FIGURE 37 ASIA PACIFIC: AI IN AGRICULTURE MARKET SNAPSHOT
           TABLE 102 ASIA PACIFIC: AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
           TABLE 103 ASIA PACIFIC: AI IN AGRICULTURE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
           TABLE 104 ASIA PACIFIC: AI IN AGRICULTURE MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
           TABLE 105 ASIA PACIFIC: AI IN AGRICULTURE MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
           9.4.1 AUSTRALIA
                    9.4.1.1 Government support in agricultural development to promote market growth
           9.4.2 CHINA
                    9.4.2.1 Inclination toward precision farming techniques to create opportunities for AI technology providers
           9.4.3 JAPAN
                    9.4.3.1 Rise in urban farming practices to fuel growth of AI in agriculture market
           9.4.4 SOUTH KOREA
                    9.4.4.1 Government funding and initiatives to develop smart farming technologies to support market growth
           9.4.5 INDIA
                    9.4.5.1 Digital transformation of Indian agriculture sector to provide opportunities for AI technology providers
           9.4.6 REST OF ASIA PACIFIC
    9.5 REST OF THE WORLD 
           TABLE 106 ROW: AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
           TABLE 107 ROW: AI IN AGRICULTURE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
           TABLE 108 ROW: AI IN AGRICULTURE MARKET, BY REGION, 2019–2022 (USD MILLION)
           TABLE 109 ROW: AI IN AGRICULTURE MARKET, BY REGION, 2023–2028 (USD MILLION)
           9.5.1 MIDDLE EAST & AFRICA
                    9.5.1.1 Increasing adoption of remote sensing and precision farming technologies to boost market
           9.5.2 SOUTH AMERICA
                    9.5.2.1 Growing adoption of modern farming practices to drive market
 
10 COMPETITIVE LANDSCAPE (Page No. - 131)
     10.1 OVERVIEW 
     10.2 COMPANY REVENUE ANALYSIS, 2017–2021 
             FIGURE 38 FIVE-YEAR REVENUE ANALYSIS OF KEY PLAYERS, 2017–2021
     10.3 MARKET SHARE ANALYSIS, 2022 
             FIGURE 39 SHARE OF MAJOR PLAYERS IN AI IN AGRICULTURE MARKET, 2022
             TABLE 110 DEGREE OF COMPETITION
     10.4 COMPANY EVALUATION QUADRANT 
             10.4.1 STARS
             10.4.2 PERVASIVE PLAYERS
             10.4.3 EMERGING LEADERS
             10.4.4 PARTICIPANTS
                        FIGURE 40 COMPANY EVALUATION QUADRANT, 2022
     10.5 COMPANY FOOTPRINT 
             TABLE 111 FOOTPRINTS OF COMPANIES
             TABLE 112 APPLICATION FOOTPRINT OF COMPANIES
             TABLE 113 REGION FOOTPRINT OF COMPANIES
     10.6 SMES EVALUATION QUADRANT 
             10.6.1 PROGRESSIVE COMPANIES
             10.6.2 RESPONSIVE COMPANIES
             10.6.3 DYNAMIC COMPANIES
             10.6.4 STARTING BLOCKS
                        FIGURE 41 SMES EVALUATION QUADRANT, 2022
     10.7 SMES EVALUATION MATRIX 
             TABLE 114 DETAILED LIST OF KEY SMES
             TABLE 115 COMPETITIVE BENCHMARKING OF KEY SMES
     10.8 COMPETITIVE SCENARIO 
             10.8.1 PRODUCT LAUNCHES
                        TABLE 116 PRODUCT LAUNCHES, 2020–2022
             10.8.2 DEALS
                        TABLE 117 DEALS, 2020–2022
 
11 COMPANY PROFILES (Page No. - 142)
     11.1 KEY PLAYERS 
(Business overview, Products offered, Recent developments, Product launches, Deals, MnM view, Key strengths/Right to win, Strategic choices, and Weaknesses/Competitive threats)*  
             11.1.1 IBM
                        TABLE 118 IBM: COMPANY OVERVIEW
                        FIGURE 42 IBM: COMPANY SNAPSHOT
                        TABLE 119 IBM: PRODUCTS OFFERED
                        TABLE 120 IBM: PRODUCT LAUNCHES
                        TABLE 121 IBM: DEALS
             11.1.2 DEERE & COMPANY
                        TABLE 122 DEERE & COMPANY: COMPANY OVERVIEW
                        FIGURE 43 DEERE & COMPANY: COMPANY SNAPSHOT
                        TABLE 123 DEERE & COMPANY: PRODUCTS OFFERED
                        TABLE 124 DEERE & COMPANY: DEALS
             11.1.3 MICROSOFT
                        TABLE 125 MICROSOFT: COMPANY OVERVIEW
                        FIGURE 44 MICROSOFT: COMPANY SNAPSHOT
                        TABLE 126 MICROSOFT: PRODUCTS OFFERED
                        TABLE 127 MICROSOFT: DEALS
             11.1.4 THE CLIMATE CORPORATION
                        TABLE 128 THE CLIMATE CORPORATION: COMPANY OVERVIEW
                        TABLE 129 THE CLIMATE CORPORATION: PRODUCTS OFFERED
                        TABLE 130 THE CLIMATE CORPORATION: PRODUCT LAUNCHES
                        TABLE 131 THE CLIMATE CORPORATION: DEALS
             11.1.5 FARMERS EDGE INC.
                        TABLE 132 FARMERS EDGE INC.: COMPANY OVERVIEW
                        FIGURE 45 FARMERS EDGE INC.: COMPANY SNAPSHOT
                        TABLE 133 FARMERS EDGE INC.: PRODUCTS OFFERED
                        TABLE 134 FARMERS EDGE INC.: DEALS
                        TABLE 135 FARMERS EDGE INC.: OTHERS
             11.1.6 GRANULAR INC.
                        TABLE 136 GRANULAR INC.: COMPANY OVERVIEW
                        TABLE 137 GRANULAR INC.: PRODUCTS OFFERED
             11.1.7 AGEAGLE AERIAL SYSTEMS INC.
                        TABLE 138 AGEAGLE AERIAL SYSTEMS INC.: COMPANY OVERVIEW
                        FIGURE 46 AGEAGLE AERIAL SYSTEMS INC.: COMPANY SNAPSHOT
                        TABLE 139 AGEAGLE AERIAL SYSTEMS INC.: PRODUCTS OFFERED
                        TABLE 140 AGEAGLE AERIAL SYSTEMS INC.: OTHERS
             11.1.8 DESCARTES LABS, INC.
                        TABLE 141 DESCARTES LABS, INC.: COMPANY OVERVIEW
                        TABLE 142 DESCARTES LABS, INC.: PRODUCTS OFFERED
                        TABLE 143 DESCARTES LABS, INC.: PRODUCT LAUNCHES
             11.1.9 PROSPERA TECHNOLOGIES, INC.
                        TABLE 144 PROSPERA TECHNOLOGIES, INC.: COMPANY OVERVIEW
                        TABLE 145 PROSPERA TECHNOLOGIES, INC.: PRODUCTS OFFERED
                        TABLE 146 PROSPERA TECHNOLOGIES, INC.: OTHERS
             11.1.10 TARANIS
                        TABLE 147 TARANIS: COMPANY OVERVIEW
                        TABLE 148 TARANIS: PRODUCTS OFFERED
                        TABLE 149 TARANIS: DEALS
                        TABLE 150 TARANIS: OTHERS
             11.1.11 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED
                        TABLE 151 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED: COMPANY OVERVIEW
                        TABLE 152 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED: PRODUCTS OFFERED
                        TABLE 153 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED: PRODUCT LAUNCHES
                        TABLE 154 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED: DEALS
                        TABLE 155 CROPIN TECHNOLOGY SOLUTIONS PRIVATE LIMITED: OTHERS
     11.2 OTHER KEY COMPANIES 
             11.2.1 GAMAYA
             11.2.2 EC2CE
             11.2.3 PRECISION HAWK
             11.2.4 VINEVIEW
             11.2.5 EVER.AG
             11.2.6 TULE TECHNOLOGIES
             11.2.7 RESSON AEROSPACE INC.
             11.2.8 CONNECTERRA B.V.
             11.2.9 VISION ROBOTICS CORPORATION
             11.2.10 FARMBOT
             11.2.11 HARVEST CROO ROBOTICS LLC
             11.2.12 PROGRESSIVE ENVIRONMENTAL & AGRICULTURAL TECHNOLOGIES (PEAT)
             11.2.13 TRACE GENOMICS
             11.2.14 CROPX INC.
*Details on Business overview, Products offered, Recent developments, Product launches, Deals, MnM view, Key strengths/Right to win, Strategic choices, and Weaknesses/Competitive threats might not be captured in case of unlisted companies.  
 
12 ADJACENT AND RELATED MARKETS (Page No. - 177)
     12.1 INTRODUCTION 
     12.2 STUDY LIMITATIONS 
     12.3 PRECISION FARMING MARKET, BY TECHNOLOGY 
             TABLE 156 PRECISION FARMING MARKET, BY TECHNOLOGY TYPE, 2018–2021 (USD MILLION)
             TABLE 157 PRECISION FARMING MARKET, BY TECHNOLOGY TYPE, 2022–2030 (USD MILLION)
             12.3.1 GUIDANCE TECHNOLOGY
                        12.3.1.1 GPS/GNSS-based guidance technology
                                     12.3.1.1.1 Rising preference for using advanced technologies in agriculture industry to boost demand for GPS/GNSS-based guidance technology
                        12.3.1.2 GIS-based guidance technology
                                     12.3.1.2.1 Increasing need to store data related to yields, soil survey maps, etc., to accelerate adoption of GIS-based guidance technology
             12.3.2 REMOTE SENSING TECHNOLOGY
                        12.3.2.1 Handheld or ground-based sensing
                                     12.3.2.1.1 Growing demand for and easy availability of handheld sensors to drive market growth
                        12.3.2.2 Satellite or aerial sensing
                                     12.3.2.2.1 Ability of satellite sensing to provide quantitative and near-real-time information over large areas to drive adoption
             12.3.3 VARIABLE RATE TECHNOLOGY (VRT)
                        12.3.3.1 MAP-based VRT
                                     12.3.3.1.1 MAP-based VRT segment held largest market share in 2021
                        12.3.3.2 Sensor-based VRT
                                     12.3.3.2.1 Use of sensor-based VRT to measure soil properties or crop characteristics
 
13 APPENDIX (Page No. - 184)
     13.1 DISCUSSION GUIDE 
     13.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 
     13.3 CUSTOMIZATION OPTIONS 
     13.4 RELATED REPORTS 
     13.5 AUTHOR DETAILS 
 

The study involved four major activities in estimating the size for AI in agriculture market. Exhaustive secondary research was done to collect information on the market, peer market, and parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across value chains through primary research. The bottom-up approach was employed to estimate the overall market size. After that, market breakdown and data triangulation were used to estimate the market size of segments and subsegments.

Secondary Research

In the secondary research process, various sources were referred to for identifying and collecting information important for this study. Secondary sources include corporate filings (such as annual reports, investor presentations, and financial statements); trade, business, and professional associations; white papers, AI in agriculture-related journals, and certified publications; articles by recognized authors; gold and silver standard websites; and directories.

Secondary research was mainly conducted to obtain key information about the market value chain, the industry supply chain, the total pool of key players, market classification and segmentation according to industry trends to the bottom-most level, and key developments from both market- and technology-oriented perspectives. Data from secondary research was collected and analyzed to arrive at the overall market size, which was further validated by primary research.

Primary Research

Extensive primary research has been conducted after understanding and analyzing the AI in agriculture market through secondary research. Several primary telephonic interviews have been conducted with key opinion leaders from the demand- and supply-side vendors across four major regions—North America, Europe, Asia Pacific, and the Rest of the World (RoW). Moreover, questionnaires and emails were also used to collect the data.

Artificial Intelligence in Agriculture Market Size, and Share

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

Market Size Estimation

In this report for the complete market engineering process, both top-down and bottom-up approaches were used, along with several data triangulation methods, to estimate, forecast and validate the size of the market and its segments and subsegments listed in the report. Extensive qualitative and quantitative analyses were carried out to list the key information/insights pertaining to AI in agriculture market.

Major players in the AI in agriculture market have been identified through secondary research, and their market shares in the respective regions have been determined through primary and secondary research. The entire research methodology included the study of annual and financial reports of top players and interviews with experts (such as CEOs, VPs, directors, and marketing executives) for key insights (quantitative and qualitative). All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources. This data was consolidated and enhanced with detailed inputs and analysis from MarketsandMarkets and presented in this report.

AI in Agriculture Market: Bottom-Up Approach

Artificial Intelligence in Agriculture Market Size, and Bottom-Up Approach

AI in Agriculture Market: Top-Down Approach

Artificial Intelligence in Agriculture Market Size, and Top-Down Approach

Data Triangulation

After arriving at the overall size of the AI in agriculture market from the estimation process explained above, the total market was split into several segments and subsegments. The market breakdown and data triangulation procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The data was triangulated by studying various factors and trends from both the demand and supply sides. Along with this, the market size was validated using both the top-down and bottom-up approaches.

Report Objectives

  • To define, analyze, and forecast the artificial intelligence (AI) in agriculture market, in terms of value, by technology, offering, application, and region
  • To forecast the market size for various segments with respect to four main regions: North America, Europe, Asia Pacific, and Rest of the World (RoW)
  • To provide detailed information regarding drivers, restraints, opportunities, and challenges influencing market growth
  • To strategically analyze the micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
  • To provide a detailed overview of the value chain in the artificial intelligence in agriculture market and analyze the market trends
  • To analyze opportunities in the market for various stakeholders by identifying the high-growth segments of artificial intelligence in agriculture market
  • To strategically profile the key players and comprehensively analyze their market position in terms of ranking and core competencies2, along with detailing the competitive landscape for the market leaders
  • To benchmark players within the market using competitive leadership mapping, which analyzes market players on various parameters within the broad categories of business and product strategies
  • To map the competitive intelligence based on company profiles, key player strategies, and game-changing developments, such as product launches, partnerships, and acquisitions
  • To analyze the probable impact of the recession on the market in the near future

Available Customizations

With the given market data, MarketsandMarkets offers customizations according to the specific requirements of companies. The following customization options are available for the report:

Product Analysis

  • Detailed analysis and profiling of additional market players
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Report Code
SE 5832
Published ON
Feb, 2023
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