Global Artificial Intelligence in Agriculture Market Opportunities and Forecast 2023-2030

  •   DLR2917
  •   February, 2022
  •   Pages: 120
  •  Global
Artificial Intelligence in Agriculture Market Overview

Artificial intelligence techniques for farming help increase productivity and yield. Therefore, agribusiness firms adopt AI technologies in terms of predictive analytics-based solutions. AI-based applications and techniques help control pests, yield healthier crops, monitor the soil, and improve agriculture-related tasks within the entire food provide chain. AI is increasingly being adopted within the agriculture business for the development of harvest quality and accuracy since it helps analyze farm knowledge.
 
The global population is predicted to reach nine.8 billion by 2050, consistent with the un. rapidly growing population drives the necessity for bringing AI within the agriculture business. limited cultivatable land availability and want for enhanced food production for food security drive the necessity for a revolution fueled by AI, web of Things (IoT), and large data. AI-enabled applications cater to many areas within the agriculture business, like predictive and recommendation analytics, distinctive plant diseases, detecting pesterer infestations, and soil monitoring.

Report Metric Details
Market size available for years 2023–2030
Base year considered 2023
Forecast period 2024–2030
Forecast unit Value (USD Million)
Segments covered Type, Deployment Method, Application Areas, and Region
Regions covered North America (the U.S. and Canada), Europe (UK, Germany, France, Italy, Spain, Russia, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South East Asia, Rest of Asia Pacific), Latin America and the Middle East and Africa (Brazil, Saudi Arabia, UAE, Rest of LAMEA)
Companies covered IBM ,Deere & Company ,Microsoft, Farmers Edge,The Climate Corp,ec2ce,Descartes Lab ,AgEagle ,aWhere ,Gamaya ,Precision Hawk ,Granular , Prospera ,Cainthus ,Taranis ,Resson, FarmBot Inc. , Connecterra ,Vision Robotics,Harvest Croo,ATC,Trace Genomics .


The covid-19 Impact on Artificial Intelligence in Agriculture Market:

Like several different industries, COVID-19 badly knocked the electronic and semiconductor trade. This new event has compact nearly 230 countries in exactly a couple of weeks, leading to the forced conclusion of producing and transportation activities at intervals and across the countries. This has directly affected the expansion of the sector. It's calculable that COVID-19 to depart over USD thirty billion impacts on the physics and semiconductor trade. The arena is majorly affected thanks to transport restrictions on major physics and semiconductor staple suppliers. However, the rising want for semiconductors in many industries can supply fast market recovery over the longer-term amount.
 
Artificial Intelligence in Agriculture Market Segment Overview



By Technology , Machine Learning is segment accounted major market share, Machine learning-enabled solutions area unit being significantly adopted by agricultural organizations and farmers worldwide to reinforce their farm productivity and gain a competitive edge in business operations. within the coming years, the appliance of machine learning in various agricultural practices is predicted to rise exponentially.
 
By offering, software section to carry largest share of AI in agriculture market during forecast amount
The market for the code section is especially driven by the mixing of mobile technologies with farming techniques, the growing use of AI code to boost farm potency, and therefore the rising demand for real-time information management systems.
 
By  Application Areas , Precision Farming segment accounted largest share through out the forecast period. Owing to technology in agricultural and new developments in this area.
 
Market Analysis, Insights and Forecast – By Technology
·       Machine Learning,
·       Computer Vision,
·       Predictive Analytics

Market Analysis, Insights and Forecast – By Deployment Modes
·       Software,
·       Hardware,
·       AI-as-a-Service,
·       Services

Market Analysis, Insights and Forecast – By Application Areas
·       Precision Farming
·       Drone Analytics
·       Agriculture Robots
·       Livestock Monitoring
·       Others
 
Artificial Intelligence in Agriculture Market Regional Overview

Region-wise, in terms of regions,The market in North America accounted for a share of over 35.0% in 2018, owing to the leading industrial automation industry and adoption of computing solutions within the region. North America is characterised by improved purchasing power of the population, continuous investments in automation, appreciable investments in IIoT, and increasing focus from governments on in-house AI equipment production. The market additionally benefits from the presence of diverse agricultural technology providers exploring computing solutions, including IBM Corporation; deere & Company; Microsoft; Granular, Inc.; and the Climate Corporation.
 
The Asia Pacific market is predicted to demonstrate the highest CAGR over the forecast amount. Its growth is attributed to increasing adoption of computing technologies in agriculture.

Artificial Intelligence in Agriculture Market, By Geography

·       North America (US & Canada)
·       Europe (UK, Germany, France, Italy, Spain, & Rest of Europe)
·       Asia-Pacific (Japan, China, India, Australia, & South Korea, & Rest of Asia-Pacific)
·       LAMEA (Brazil, Saudi Arabia, UAE & Rest of LAMEA)
 
Artificial Intelligence in Agriculture Market Competitor overview

Some key developments and strategies adopted by manufacturers in the Artificial Intelligence in Agriculture are highlighted below.
 
·       In 2023, deere & Company partnered with Cultivating New Frontiers in Agriculture (CNFA), an international agricultural development organization to extend productivity and income for smallholder farmers by implementing mechanization within the agriculture business.
 
Artificial Intelligence in Agriculture Market, Key Players

·       IBM
·       Deere & Company
·       Microsoft,
·       Farmers Edge,
·       The Climate Corp
·       ec2ce
·       Descartes Lab
·       AgEagle
·       aWhere
·       Gamaya
·       Precision Hawk
·       Granular
·       Prospera
·       Cainthus
·       Taranis
·       Resson,
·       FarmBot Inc.
·       Connecterra
·       Vision Robotics
·       Harvest Croo,
·       ATC
·       Trace Genomics
·       VineView
·       CropX
·       Tule Technologies
·       PEAT

Frequently Asked Questions (FAQ) :

Q1. What is the total CAGR expected to be recorded for the Artificial Intelligence in Agriculture market during the forecast period?

Artificial Intelligence in Agriculture market is expected to record a CAGR of ~ XX % during the forecast period.

Q2. Which segment is projected to hold the largest share in the Artificial Intelligence in Agriculture Market?

Precision Farming segment is projected to hold the largest share in the Artificial Intelligence in Agriculture Market.

Q3. What are the driving factors for the Artificial Intelligence in Agriculture market?

The growing demand for replacing the standard anti-fraud technology tools with advanced analytics is key factors that boost the growth of the Artificial Intelligence in Agriculture market progressively.

Q4. Which Segments are covered in the Artificial Intelligence in Agriculture market report?

Technology , Deployment Method, Application, and Region, these segments are covered in the Artificial Intelligence in Agriculture market report.

Q5. Which are the prominent players offering Agriculture Analytics?

IBM ,Deere & Company ,Microsoft, Farmers Edge,The Climate Corp,ec2ce,Descartes Lab ,AgEagle ,aWhere ,Gamaya ,Precision Hawk ,Granular , Prospera ,Cainthus ,Taranis ,Resson, FarmBot Inc. , Connecterra ,Vision Robotics,Harvest Croo,ATC,Trace Genomics .
Artificial Intelligence in Agriculture Market Study Global Market Analysis, Insights and Forecast, 2020-2027

    1. Introduction

    • 1.1. Research Scope
    • 1.2. Market Segmentation
    • 1.3. Research Methodology
    • 1.4. Definitions and Assumptions

    2. Executive Summary

      3. Market Dynamics

      • 3.1. Market Drivers
      • 3.2. Market Restraints
      • 3.3. Market Opportunities

      4. Key Insights

      • 4.1. Key Emerging Trends – For Major Countries
      • 4.2. Latest Technological Advancement
      • 4.3. Regulatory Landscape
      • 4.4. Industry SWOT Analysis
      • 4.5. Porters Five Forces Analysis

      5. Global Artificial Intelligence in Agriculture Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 5.1. Key Findings / Summary
      • 5.2. Market Analysis, Insights and Forecast – By Technology
        • 5.2.1. •Machine Learning,
        • 5.2.2. •Computer Vision,
        • 5.2.3. •Predictive Analytics
      • 5.3. Market Analysis, Insights and Forecast – By Deployment Modes
        • 5.3.1. •Software,
        • 5.3.2. •Hardware,
        • 5.3.3. •AI-as-a-Service,
        • 5.3.4. • Services
      • 5.4. Market Analysis, Insights and Forecast – By Application Areas
        • 5.4.1. •Precision Farming
        • 5.4.2. •Drone Analytics
        • 5.4.3. •Agriculture Robots
        • 5.4.4. •Livestock Monitoring
        • 5.4.5. •Others
      • 5.5. Market Analysis, Insights and Forecast – By Region
        • 5.5.1. North America
        • 5.5.2. Europe
        • 5.5.3. Asia Pacific
        • 5.5.4. Latin America, Middle East, and Africa

      6. North America Artificial Intelligence in Agriculture Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 6.1. Key Findings / Summary
      • 6.2. Market Analysis, Insights and Forecast – By Technology
        • 6.2.1. •Machine Learning,
        • 6.2.2. •Computer Vision,
        • 6.2.3. •Predictive Analytics
      • 6.3. Market Analysis, Insights and Forecast – By Deployment Modes
        • 6.3.1. •Software,
        • 6.3.2. •Hardware,
        • 6.3.3. •AI-as-a-Service,
        • 6.3.4. • Services
      • 6.4. Market Analysis, Insights and Forecast – By Application Areas
        • 6.4.1. •Precision Farming
        • 6.4.2. •Drone Analytics
        • 6.4.3. •Agriculture Robots
        • 6.4.4. •Livestock Monitoring
        • 6.4.5. •Others
      • 6.5. Market Analysis, Insights and Forecast – By Country
        • 6.5.1. U.S.
        • 6.5.2. Canada

      7. Europe Artificial Intelligence in Agriculture Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 7.1. Key Findings / Summary
      • 7.2. Market Analysis, Insights and Forecast – By Technology
        • 7.2.1. •Machine Learning,
        • 7.2.2. •Computer Vision,
        • 7.2.3. •Predictive Analytics
      • 7.3. Market Analysis, Insights and Forecast – By Deployment Modes
        • 7.3.1. •Software,
        • 7.3.2. •Hardware,
        • 7.3.3. •AI-as-a-Service,
        • 7.3.4. • Services
      • 7.4. Market Analysis, Insights and Forecast – By Application Areas
        • 7.4.1. •Precision Farming
        • 7.4.2. •Drone Analytics
        • 7.4.3. •Agriculture Robots
        • 7.4.4. •Livestock Monitoring
        • 7.4.5. •Others
      • 7.5. Market Analysis, Insights and Forecast – By Country
        • 7.5.1. UK
        • 7.5.2. Germany
        • 7.5.3. France
        • 7.5.4. Italy
        • 7.5.5. Spain
        • 7.5.6. Russia
        • 7.5.7. Rest of Europe

      8. Asia Pacific Artificial Intelligence in Agriculture Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 8.1. Key Findings / Summary
      • 8.2. Market Analysis, Insights and Forecast – By Technology
        • 8.2.1. •Machine Learning,
        • 8.2.2. •Computer Vision,
        • 8.2.3. •Predictive Analytics
      • 8.3. Market Analysis, Insights and Forecast – By Deployment Modes
        • 8.3.1. •Software,
        • 8.3.2. •Hardware,
        • 8.3.3. •AI-as-a-Service,
        • 8.3.4. • Services
      • 8.4. Market Analysis, Insights and Forecast – By Application Areas
        • 8.4.1. •Precision Farming
        • 8.4.2. •Drone Analytics
        • 8.4.3. •Agriculture Robots
        • 8.4.4. •Livestock Monitoring
        • 8.4.5. •Others
      • 8.5. Market Analysis, Insights and Forecast – By Country
        • 8.5.1. China
        • 8.5.2. India
        • 8.5.3. Japan
        • 8.5.4. Australia
        • 8.5.5. South East Asia
        • 8.5.6. Rest of Asia Pacific

      9. Latin America, Middle East, and Africa Artificial Intelligence in Agriculture Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 9.1. Key Findings / Summary
      • 9.2. Market Analysis, Insights and Forecast – By Technology
        • 9.2.1. •Machine Learning,
        • 9.2.2. •Computer Vision,
        • 9.2.3. •Predictive Analytics
      • 9.3. Market Analysis, Insights and Forecast – By Deployment Modes
        • 9.3.1. •Software,
        • 9.3.2. •Hardware,
        • 9.3.3. •AI-as-a-Service,
        • 9.3.4. • Services
      • 9.4. Market Analysis, Insights and Forecast – By Application Areas
        • 9.4.1. •Precision Farming
        • 9.4.2. •Drone Analytics
        • 9.4.3. •Agriculture Robots
        • 9.4.4. •Livestock Monitoring
        • 9.4.5. •Others
      • 9.5. Market Analysis, Insights and Forecast – By Country
        • 9.5.1. Brazil
        • 9.5.2. Saudi Arabia
        • 9.5.3. UAE
        • 9.5.4. Rest of LAMEA

      10. Competitive Analysis

      • 10.1. Company Market Share Analysis, 2018
      • 10.2. Key Industry Developments
      • 10.3. Company Profile
      • 10.4. IBM Corporation
        • 10.4.1. Business Overview
        • 10.4.2. Segment 1 & Service Offering
        • 10.4.3. Overall Revenue
        • 10.4.4. Geographic Presence
        • 10.4.5. Recent Development
      *Similar details will be provided for the following companies
      • 10.5. •IBM
      • 10.6. •Deere & Company
      • 10.7. •Microsoft,
      • 10.8. •Farmers Edge,
      • 10.9. •The Climate Corp
      • 10.10. •ec2ce
      • 10.11. • Descartes Lab
      • 10.12. •AgEagle
      • 10.13. •aWhere
      • 10.14. •Gamaya
      • 10.15. •Precision Hawk
      • 10.16. •Granular
      • 10.17. • Prospera
      • 10.18. •Cainthus
      • 10.19. •Taranis
      • 10.20. •Resson,
      • 10.21. • FarmBot Inc.
      • 10.22. •Connecterra
      • 10.23. •Vision Robotics
      • 10.24. •Harvest Croo,
      • 10.25. •ATC

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      Research Process

      Data Library Research are conducted by industry experts who offer insight on industry structure, market segmentations technology assessment and competitive landscape (CL), and penetration, as well as on emerging trends. Their analysis is based on primary interviews (~ 80%) and secondary research (~ 20%) as well as years of professional expertise in their respective industries. Adding to this, by analysing historical trends and current market positions, our analysts predict where the market will be headed for the next five years. Furthermore, the varying trends of segment & categories geographically presented are also studied and the estimated based on the primary & secondary research.

      In this particular report from the supply side Data Library Research has conducted primary surveys (interviews) with the key level executives (VP, CEO’s, Marketing Director, Business Development Manager and SOFT) of the companies that active & prominent as well as the midsized organization

      FIGURE 1: DLR RESEARH PROCESS

      Primary Research

      Extensive primary research was conducted to gain a deeper insight of the market and industry performance. The analysis is based on both primary and secondary research as well as years of professional expertise in the respective industries.

      In addition to analysing current and historical trends, our analysts predict where the market is headed over the next five years.

      It varies by segment for these categories geographically presented in the list of market tables. Speaking about this particular report we have conducted primary surveys (interviews) with the key level executives (VP, CEO’s, Marketing Director, Business Development Manager and many more) of the major players active in the market.

      Secondary Research

      Secondary research was mainly used to collect and identify information useful for the extensive, technical, market-oriented, and Friend’s study of the Global Extra Neutral Alcohol. It was also used to obtain key information about major players, market classification and segmentation according to the industry trends, geographical markets, and developments related to the market and technology perspectives. For this study, analysts have gathered information from various credible sources, such as annual reports, sec filings, journals, white papers, SOFT presentations, and company web sites.

      Market Size Estimation

      Both, top-down and bottom-up approaches were used to estimate and validate the size of the Global market and to estimate the size of various other dependent submarkets in the overall Extra Neutral Alcohol. The key players in the market were identified through secondary research and their market contributions in the respective geographies were determined through primary and secondary research.

      Forecast Model