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Global Artificial Intelligence in Agriculture Market (2023-2028) Competitive Analysis, Impact of Covid-19 with Ansoff Analysis

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    Report

  • 183 Pages
  • February 2024
  • Region: Global
  • Infogence Global Research
  • ID: 5585680
The Global Artificial Intelligence in Agriculture Market is estimated to be USD 2.4 Bn in 2023 and is expected to reach USD 6.27 Bn by 2028 growing at a CAGR of 21.19%.

Market Dynamics

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence in Agriculture Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Market Segmentations

  • The Global Artificial Intelligence in Agriculture Market is segmented based on Offerings, Technology, Applications, and Geography.
  • By Offerings, the market is classified into Hardware, Software, AI, As-A-Service, and Services.
  • By Technology, the market is classified into Machine Learning, Computer Vision, and Predictive Analytics.
  • By Applications, the market is classified into Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Labor Management, and Others.
  • By Geography, the market is classified into Americas, Europe, Middle-East & Africa and Asia-Pacific.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario. Some of the companies covered in this report are A.A.A Taranis Visual Ltd, Ag Eagle Aerial Systems Inc, Autonomous Tractor Corp, aWhere Inc, Cainthus Corp, etc.

Countries Studied

  • America (Argentina, Brazil, Canada, Chile, Colombia, Mexico, Peru, United States, Rest of Americas)
  • Europe (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Poland, Russia, Spain, Sweden, Switzerland, United Kingdom, Rest of Europe)
  • Middle-East and Africa (Egypt, Israel, Qatar, Saudi Arabia, South Africa, United Arab Emirates, Rest of MEA)
  • Asia-Pacific (Australia, Bangladesh, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Sri Lanka, Thailand, Taiwan, Rest of Asia-Pacific)

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

  • The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence in Agriculture Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.
  • The publisher analyses the Global Artificial Intelligence in Agriculture Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.
  • Based on the SWOT analysis conducted on the industry and industry players, the publisher has devised suitable strategies for market growth.

Why buy this report?

  • The report offers a comprehensive evaluation of the Global Artificial Intelligence in Agriculture Market. The report includes in-depth qualitative analysis, verifiable data from authentic sources, and projections about market size. The projections are calculated using proven research methodologies.
  • The report has been compiled through extensive primary and secondary research. The primary research is done through interviews, surveys, and observation of renowned personnel in the industry.
  • The report includes an in-depth market analysis using Porter's 5 forces model and the Ansoff Matrix. In addition, the impact of Covid-19 on the market is also featured in the report.
  • The report also includes the regulatory scenario in the industry, which will help you make a well-informed decision. The report discusses major regulatory bodies and major rules and regulations imposed on this sector across various geographies.
  • The report also contains the competitive analysis using Positioning Quadrants, the Proprietary competitive positioning tool.

Report Highlights:

  • A complete analysis of the market, including parent industry
  • Important market dynamics and trends
  • Market segmentation
  • Historical, current, and projected size of the market based on value and volume
  • Market shares and strategies of key players
  • Recommendations to companies for strengthening their foothold in the market

Table of Contents

1 Report Description
1.1 Study Objectives
1.2 Market Definition
1.3 Currency
1.4 Years Considered
1.5 Language
1.6 Key Stakeholders
2 Research Methodology
2.1 Research Process
2.2 Data Collection and Validation
2.2.1 Secondary Research
2.2.2 Primary Research
2.2.3 Models
2.3 Market Size Estimation
2.3.1 Bottom-Up Approach
2.3.2 Top-Down Approach
2.4 Assumptions of the Study
2.5 Limitations of the Study
3 Executive Summary
3.1 Introduction
3.2 Market Size, Segmentations and Outlook
4 Market Dynamics
4.1 Drivers
4.1.1 Increasing Strain on Global Food Supply Owing to the Rising Population
4.1.2 Increasing Implementation of Data Generation through Sensors and Aerial Images for Crops
4.1.3 Increasing Crop Productivity through Deep Learning Technology
4.1.4 Government Support to Adopt Modern Agricultural Techniques
4.2 Restraints
4.2.1 High Cost of Gathering Precise Field Data
4.2.2 Lack of Awareness about AI Among Farmers
4.3 Opportunities
4.3.1 Developing Countries to Offer Significant Growth Opportunities
4.3.2 Increase in R&D Investment
4.4 Challenges
4.4.1 Lack of Standardization
4.4.2 Limited Availability of Historical Data
5 Market Analysis
5.1 Regulatory Scenario
5.2 Porter's Five Forces Analysis
5.3 Impact of COVID-19
5.4 Ansoff Matrix Analysis
6 Global Artificial Intelligence in Agriculture Market, By Offerings
6.1 Introduction
6.2 Hardware
6.2.1 rocessor
6.2.2 Storage Device
6.2.3 Network
6.3 Software
6.3.1 Platform
6.3.2 Solution
6.4 AI-As-A-Service
6.5 Services
6.5.1 Deployment & Integration
6.5.2 Support & Maintenance
7 Global Artificial Intelligence in Agriculture Market, By Technology
7.1 Introduction
7.2 Machine Learning
7.3 Computer Vision
7.4 Predictive Analytics
8 Global Artificial Intelligence in Agriculture Market, By Applications
8.1 Introduction
8.2 Precision Farming
8.3 Livestock Monitoring
8.4 Drone Analytics
8.5 Agriculture Robots
8.6 Labor Management
8.7 Others
9 Americas' Global Artificial Intelligence in Agriculture Market
9.1 Introduction
9.2 Argentina
9.3 Brazil
9.4 Canada
9.5 Chile
9.6 Colombia
9.7 Mexico
9.8 Peru
9.9 United States
9.10 Rest of Americas
10 Europe's Global Artificial Intelligence in Agriculture Market
10.1 Introduction
10.2 Austria
10.3 Belgium
10.4 Denmark
10.5 Finland
10.6 France
10.7 Germany
10.8 Italy
10.9 Netherlands
10.10 Norway
10.11 Poland
10.12 Russia
10.13 Spain
10.14 Sweden
10.15 Switzerland
10.16 United Kingdom
10.17 Rest of Europe
11 Middle East and Africa's Global Artificial Intelligence in Agriculture Market
11.1 Introduction
11.2 Egypt
11.3 Israel
11.4 Qatar
11.5 Saudi Arabia
11.6 South Africa
11.7 United Arab Emirates
11.8 Rest of MEA
12 APAC's Global Artificial Intelligence in Agriculture Market
12.1 Introduction
12.2 Australia
12.3 Bangladesh
12.4 China
12.5 India
12.6 Indonesia
12.7 Japan
12.8 Malaysia
12.9 Philippines
12.10 Singapore
12.11 South Korea
12.12 Sri Lanka
12.13 Thailand
12.14 Taiwan
12.15 Rest of Asia-Pacific
13 Competitive Landscape
13.1 Competitive Quadrant
13.2 Market Share Analysis
13.3 Strategic Initiatives
13.3.1 M&A and Investments
13.3.2 Partnerships and Collaborations
13.3.3 Product Developments and Improvements
14 Company Profiles
14.1 A.A.A Taranis Visual Ltd
14.2 Ag Eagle Aerial Systems Inc
14.3 Autonomous Tractor Corp
14.4 aWhere Inc
14.5 Cainthus Corp
14.6 Connecterra B.V.
14.7 CropX Inc
14.8 Deere & Company
14.9 Descartes Labs Inc
14.10 ec2ce
14.11 FarmBot Inc
14.12 Farmers Edge Inc
14.13 Gamaya Inc
14.14 Granular Inc
14.15 Harvest CROO Robotics LLC
14.16 IBM
14.17 Microsoft Corp
14.18 PEAT GmbH
14.19 Precision Hawk Inc
14.20 Prospera Technologies Ltd
14.21 Resson Inc
14.22 The Climate Corp
14.23 Trace Genomics Inc
14.24 Tule Technologies Inc
14.25 VineView (SkySquirrel Technologies Inc)
14.26 Vision Robotics Corp
15 Appendix
15.1 Questionnaire

Companies Mentioned

  • A.A.A Taranis Visual Ltd
  • Ag Eagle Aerial Systems Inc
  • Autonomous Tractor Corp
  • aWhere Inc
  • Cainthus Corp
  • Connecterra B.V.
  • CropX Inc
  • Deere & Company
  • Descartes Labs Inc
  • ec2ce
  • FarmBot Inc
  • Farmers Edge Inc
  • Gamaya Inc
  • Granular Inc
  • Harvest CROO Robotics LLC
  • IBM
  • Microsoft Corp
  • PEAT GmbH
  • Precision Hawk Inc
  • Prospera Technologies Ltd
  • Resson Inc
  • The Climate Corp
  • Trace Genomics Inc
  • Tule Technologies Inc
  • VineView (SkySquirrel Technologies Inc)
  • Vision Robotics Corp