Artificial Intelligence in Agriculture Market

Artificial Intelligence in Agriculture Market

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The global artificial intelligence in agriculture market size was valued at USD 1.38 billion in 2022 and is estimated to reach USD 8.96 billion by 2031, expanding at a CAGR of 23.1% during the forecast period, between 2023 - 2031. The growth of the market is attributed to the adoption of Artificial Intelligence (AI) in agriculture for increasing productivity and yield.

Agriculture plays important role in economic sector and adoption of AI in farming has brought agriculture revolution. With the growing population across the globe, the demand for foods is increasing yet the agricultural lands are constantly shrinking over the years. Thus, it has become important aspect to cultivate the land with high yield crops within a fixed portion of the agricultural space using innovative technology.

Artificial Intelligence in Agriculture Market 0utlook

Therefore, the use of AI during farming is increasingly popular as it can be used in various farming applications including computerized water system frameworks and ruler automation. With the use of AI technology, farmers can observer growing conditions, organizing data for other farmers, yield healthier crops, control pests, and monitor their soil to enhance the overall crops productivity.

The COVID-19 pandemic outbreak has had a positive impact on the market. During pandemic, there is rise in the adoption of AI through a software as a service model, sensors, and drones. The use of AI technology has enabled farmers to save their crops from pests and diseases as well as to recover from the loss they faced due to the lockdown imposed by various government bodies.

Market Trends, Drivers, Restraints, and Opportunities

  • Increasing adoption of AI for improvement in harvest quality and accuracy since it helps analyze farm data presents a key factor driving the market growth.

  • Using AI in the agriculture helps in distributing resources such as water and fertilizers, determine the optimal date for seed sowing, and detect disease in plants. This is projected to drive the market expansion during the forecast period.

  • Lack of standardization in data sharing and data collection acts as a major challenge that can restrict the market growth in the coming years.

  • High cost of initial investment in AI technology is another major restraining factor, which can hamper the market growth during the projected timeline.

  • Developing cost effective AI technology and expansion of advanced devices for everyone to gain access to this technology are projected to create significant growth opportunities for the market.

Scope of the Artificial Intelligence in Agriculture Market Report

The report on the global artificial intelligence in agriculture market includes an assessment of the market, trends, segments, and regional markets. Overview and dynamics have also been included in the report.

Attributes

Details

Report Title

Artificial Intelligence in Agriculture Market - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast

Base Year

2022

Historic Data

2016–2021

Forecast Period

2023–2031

Segmentation

Applications (Livestock Monitoring, Agriculture Robots, Drone Analytics, Precision Farming, and Others), Components (Service, Hardware, and Software), and Technology (Computer Vision, Machine Learning & Deep Learning, and Predictive Analytics)

Regional Scope

Asia Pacific, North America, Latin America, Europe, and Middle East & Africa

Report Coverage

Company Share, Market Analysis and Size, Competitive Landscape, Growth Factors, and Trends, and Revenue Forecast

Key Players Covered in the Report

Microsoft Corp.; AgEagle Aerial Systems Inc.; Granular, Inc.; Prospera Technologies; aWhere Inc.; ec2ce; VineView; IBM Corp.; Deere & Company; The Climate Corp.; Descartes Labs, Inc.; Taranis; GAMAYA; Tule Technologies Inc.; and PrecisionHawk

Artificial Intelligence in Agriculture Market Segment Insights

Customized fertilizer supply to the crops drive the precision farming segment

Based on applications, the market is divided into livestock monitoring, agriculture robots, drone analytics, precision farming, and others. The precision farming segment is expected to grow at a rapid pace during the forecast period attributed to its help to farmers for optimizing resources and minimizing cost.

Furthermore, with the help of AI precision farming, farmer can collect, analyzed, and convert digital data for customized fertilizer supply to the crops, which is projected to accelerate the segment growth further. However, the agriculture robots segment is anticipated to expand at a substantial CAGR during the forecast period due to the recent developments in robotics and its ability to hoe and weed.

Artificial Intelligence in Agriculture Market Applications

Service segment is projected to expand at considerable CAGR

In terms of components, the global artificial intelligence in agriculture market is segregated into service, hardware, and software. The software segment is expected to account for a major market share during the projected timeline owing to wide availability of AI based software, which increases the crop yield and productivity by computer vision and prediction based analytics.

On the other hand, the service
segment is projected to register a robust growth rate during the forecast period due to increasing implementation of AI solutions by farmers in several developed countries. Moreover, rising awareness of the availability of the technology among farmers has created high necessity for training services to farmers for correct installation as well as maintenance of technology.

Artificial Intelligence in Agriculture Market Components

Escalated use by farmers increase the predictive analytics segment market share

On the basis of technology, the market is fragmented into computer vision, machine learning & deep learning, and predictive analytics. The predictive analytics segment is estimated to account for a significant market share during the forecast period owing to its escalated use by farmers to address the problems such as weed management, weather tracking, and crop diseases analysis.

However, the
machine learning & deep learning segment is anticipated to grow at a high CAGR during the forecast period attributed to the use of machine learning integrated with sensors increasing the product quality. Additionally, AI-based machine learning is evolving farm management system into real artificial intelligence system, which acts as a major driver of the segment.

North America is anticipated to constitute a key market share

In terms of region, the global artificial intelligence in agriculture market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America is anticipated to constitute a key share of the market during the projected period owing to the increasing focus of government on the production of AI-based equipment for the farmers in the region.

However, the Asia Pacific market is anticipated to grow at a rapid pace during the forecast period attributed to the rising implementation of AI technology by emerging economies in the region especially China and India.

Segments

The global indoor farming market has been segmented on the basis of

Applications

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

Components

  • Service
  • Hardware
  • Software

Technology

  • Computer Vision
  • Machine Learning & Deep Learning
  • Predictive Analytics

Regions

  • Asia Pacific
  • North America
  • Latin America
  • Europe
  • Middle East & Africa

Key Players

  • Microsoft Corp.
  • AgEagle Aerial Systems Inc.
  • Granular, Inc.
  • Prospera Technologies
  • aWhere Inc.
  • ec2ce
  • VineView
  • IBM Corp.
  • Deere & Company
  • The Climate Corp.
  • Descartes Labs, Inc.
  • Taranis
  • GAMAYA
  • Tule Technologies Inc.
  • PrecisionHawk

Competitive Landscape

Key players competing in the global indoor farming market are Microsoft Corp.; AgEagle Aerial Systems Inc.; Granular, Inc.; Prospera Technologies; aWhere Inc.; ec2ce; VineView; IBM Corp.; Deere & Company; The Climate Corp.; Descartes Labs, Inc.; Taranis; GAMAYA; Tule Technologies Inc.; and PrecisionHawk

Companies are focusing on R&D investment for the development of new and innovative AI solutions for agriculture. Furthermore, companies are widely engaging in strategic partnership, new product development, contracts, and business expansions to boost their market share and add up new buyers.

For instance, in May 2019, Cultivating New Frontiers in Agriculture (CNFA), an international agricultural development organization, announced partnership with a U.S.-based corporation that manufactures agricultural machinery, Deere & Company. The aim of this partnership was to increase income and productivity of smallholder farmers by installation of mechanization in the farm.


In March 2020, Farmers Edge Inc. and Nufarm Brasil Ltda. entered into a three year partnership to digitize minimum three million acres of farms in Brazil by 2023. The former company is a digital agriculture solution provider, and the latter company is a major crop protection company.

Artificial Intelligence in Agriculture Market Key Players

1. Executive Summary
2. Assumptions and Acronyms Used
3. Research Methodology
4. Artificial Intelligence in Agriculture Market Overview
  4.1. Introduction
     4.1.1. Market Taxonomy
     4.1.2. Market Definition
  4.2. Macro-Economic Factors
     4.2.1. Industry Outlook
  4.3. Artificial Intelligence in Agriculture Market Dynamics
     4.3.1. Market Drivers
     4.3.2. Market Restraints
     4.3.3. Opportunity
     4.3.4. Market Trends
  4.4. Artificial Intelligence in Agriculture Market - Supply Chain
  4.5. Global Artificial Intelligence in Agriculture Market Forecast
     4.5.1. Artificial Intelligence in Agriculture Market Size (US$ Mn) and Y-o-Y Growth
     4.5.2. Artificial Intelligence in Agriculture Market Size (000’ Units) and Y-o-Y Growth
     4.5.3. Artificial Intelligence in Agriculture Market Absolute $ Opportunity
5. Global Artificial Intelligence in Agriculture Market Analysis and Forecast by Applications
  5.1. Market Trends
  5.2. Introduction
     5.2.1. Basis Point Share (BPS) Analysis by Applications
     5.2.2. Y-o-Y Growth Projections by Applications
  5.3. Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     5.3.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  5.4. Absolute $ Opportunity Assessment by Applications
  5.5. Market Attractiveness/Growth Potential Analysis by Applications
6. Global Artificial Intelligence in Agriculture Market Analysis and Forecast by Region
  6.1. Market Trends
  6.2. Introduction
     6.2.1. Basis Point Share (BPS) Analysis by Region
     6.2.2. Y-o-Y Growth Projections by Region
  6.3. Artificial Intelligence in Agriculture Market Size and Volume Forecast by Region
     6.3.1. North America
     6.3.2. Latin America
     6.3.3. Europe
     6.3.4. Asia Pacific
     6.3.5. Middle East and Africa (MEA)
  6.4. Absolute $ Opportunity Assessment by Region
  6.5. Market Attractiveness/Growth Potential Analysis by Region
  6.6. Global Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
7. North America Artificial Intelligence in Agriculture Market Analysis and Forecast
  7.1. Introduction
     7.1.1. Basis Point Share (BPS) Analysis by Country
     7.1.2. Y-o-Y Growth Projections by Country
  7.2. North America Artificial Intelligence in Agriculture Market Size and Volume Forecast by Country
     7.2.1. U.S.
     7.2.2. Canada
  7.3. Absolute $ Opportunity Assessment by Country
  7.4. North America Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     7.4.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  7.5. Basis Point Share (BPS) Analysis by Applications
  7.6. Y-o-Y Growth Projections by Applications
  7.7. Market Attractiveness/Growth Potential Analysis
     7.7.1. By Country
     7.7.2. By Product Type
     7.7.3. By Application
  7.8. North America Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
8. Latin America Artificial Intelligence in Agriculture Market Analysis and Forecast
  8.1. Introduction
     8.1.1. Basis Point Share (BPS) Analysis by Country
     8.1.2. Y-o-Y Growth Projections by Country
     8.1.3. Latin America Average Pricing Analysis
  8.2. Latin America Artificial Intelligence in Agriculture Market Size and Volume Forecast by Country
      8.2.1. Brazil
      8.2.2. Mexico
      8.2.3. Rest of Latin America
   8.3. Absolute $ Opportunity Assessment by Country
  8.4. Latin America Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     8.4.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  8.5. Basis Point Share (BPS) Analysis by Applications
  8.6. Y-o-Y Growth Projections by Applications
  8.7. Market Attractiveness/Growth Potential Analysis
     8.7.1. By Country
     8.7.2. By Product Type
     8.7.3. By Application
  8.8. Latin America Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
9. Europe Artificial Intelligence in Agriculture Market Analysis and Forecast
  9.1. Introduction
     9.1.1. Basis Point Share (BPS) Analysis by Country
     9.1.2. Y-o-Y Growth Projections by Country
     9.1.3. Europe Average Pricing Analysis
  9.2. Europe Artificial Intelligence in Agriculture Market Size and Volume Forecast by Country
     9.2.1. Germany
     9.2.2. France
     9.2.3. Italy
     9.2.4. U.K.
     9.2.5. Spain
     9.2.6. Russia
     9.2.7. Rest of Europe
  9.3. Absolute $ Opportunity Assessment by Country
  9.4. Europe Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     9.4.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  9.5. Basis Point Share (BPS) Analysis by Applications
  9.6. Y-o-Y Growth Projections by Applications
  9.7. Market Attractiveness/Growth Potential Analysis
     9.7.1. By Country
     9.7.2. By Product Type
     9.7.3. By Application
  9.8. Europe Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
10. Asia Pacific Artificial Intelligence in Agriculture Market Analysis and Forecast
  10.1. Introduction
     10.1.1. Basis Point Share (BPS) Analysis by Country
     10.1.2. Y-o-Y Growth Projections by Country
     10.1.3. Asia Pacific Average Pricing Analysis
  10.2. Asia Pacific Artificial Intelligence in Agriculture Market Size and Volume Forecast by Country
     10.2.1. China
     10.2.2. Japan
     10.2.3. South Korea
     10.2.4. India
     10.2.5. Australia
     10.2.6. Rest of Asia Pacific (APAC)
  10.3. Absolute $ Opportunity Assessment by Country
  10.4. Asia Pacific Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     10.4.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  10.5. Basis Point Share (BPS) Analysis by Applications
  10.6. Y-o-Y Growth Projections by Applications
  10.7. Market Attractiveness/Growth Potential Analysis
     10.7.1. By Country
     10.7.2. By Product Type
     10.7.3. By Application
  10.8. Asia Pacific Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
11. Middle East & Africa Artificial Intelligence in Agriculture Market Analysis and Forecast
  11.1. Introduction
     11.1.1. Basis Point Share (BPS) Analysis by Country
     11.1.2. Y-o-Y Growth Projections by Country
     11.1.3. Middle East & Africa Average Pricing Analysis
  11.2. Middle East & Africa Artificial Intelligence in Agriculture Market Size and Volume Forecast by Country
     11.2.1. Saudi Arabia
     11.2.2. South Africa
     11.2.3. UAE
     11.2.4. Rest of Middle East & Africa (MEA)
  11.3. Absolute $ Opportunity Assessment by Country
  11.4. Middle East & Africa Artificial Intelligence in Agriculture Market Size and Volume Forecast by Applications
     11.4.1. Agriculture Robots Drone Analytics Livestock Monitoring Precision Farming Others
  11.5. Basis Point Share (BPS) Analysis by Applications
  11.6. Y-o-Y Growth Projections by Applications
  11.7. Market Attractiveness/Growth Potential Analysis
     11.7.1. By Country
     11.7.2. By Product Type
     11.7.3. By Application
  11.8. Middle East & Africa Artificial Intelligence in Agriculture Demand Share Forecast, 2019-2026
12. Competition Landscape
  12.1. Global Artificial Intelligence in Agriculture Market: Market Share Analysis
  12.2. Artificial Intelligence in Agriculture Distributors and Customers
  12.3. Artificial Intelligence in Agriculture Market: Competitive Dashboard
  12.4. Company Profiles (Details: Overview, Financials, Developments, Strategy)
     12.4.1. Microsoft Corp. AgEagle Aerial Systems Inc. Granular, Inc. Prospera Technologies aWhere Inc. ec2ce  

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