Global AI in Agriculture Market Report 2020-2030: Increasing Use of Robotics and Smart Sensors Propelling the $8+ Billion Industry - ResearchAndMarkets.com

DUBLIN--()--The "AI in Agriculture Market Research Report: By Type, Technology, Application - Global Industry Analysis and Growth Forecast to 2030" report has been added to ResearchAndMarkets.com's offering.

The global AI in agriculture market is predicted to generate a revenue of $8,379.5, increasing from $852.2 million, and is expected to witness a 24.8% CAGR during the forecast period (2020-2030).

As the population across the globe has been growing, the demand for agricultural products has been growing as well. Countries including Brazil, India, China, and the U.S. are witnessing high demand for food products, owing to rapid urbanization, increasing disposable income, and changing consumption habits of the growing population. In order to cater to the needs of this increasing population, the agriculture industry has been making use of advanced technologies, including the artificial intelligence (AI), for increasing efficiency and productivity on fields.

Attributed to this, the global AI in agriculture market is expected to register substantial growth in the near future. By making use of AI, farmers can monitor their live-stock in real-time. AI solutions including, image classification with body condition score and feeding patterns and facial recognition for livestock, dairy farms can now individually monitor the behavioral aspects of animals. In addition to this, farmers are using machine vision, which aids them in recognizing facial features and hide patterns.

Farmers are also able to monitor water and food intake of livestock and record their body temperature and behavior. It is because of such advantages of AI that its demand in the agricultural sector is increasing at a rapid pace.

On the basis of type, the market is divided into services and product, between which, the product division accounted for the major share of the market in 2019, owing to the growing use of AI-based software. The division is further categorized into software and hardware, between which, the hardware category held the larger share of the market in the past. The demand for data storage devices, sensing systems, and automation & control systems is increasing for farm operations.

The service division is predicted to register the faster growth during the forecast period, because of the increasing adoption of AI solutions in the agricultural sector, which is creating high demand for proper maintenance, installation, and training services among industry stakeholders and farmers. The division is further categorized into professional and managed, between which, the professional category is projected to progress at a faster pace during the forecast period. This is due to the rising need for training, support, and maintenance services by farmers.

North America emerged as the largest AI in agriculture market during the forecast period (2014-2019) and is further expected to hold the largest share of the market during the forecast period as well. The early adoption of advanced technologies, including computer vision and machine learning, for different agricultural applications, such as livestock management, precision farming, soil management, and greenhouse management. Furthermore, the growing adoption of IoT is also leading to the growth of the regional market.

Hence, the market is being driven by the need for increasing productivity on agricultural fields and rising need for real-time monitoring of livestock.

Key Topics Covered:

Chapter 1. Research Background

1.1 Research Objectives

1.2 Market Definition

1.3 Research Scope

1.4 Key Stakeholders

Chapter 2. Research Methodology

2.1 Secondary Research

2.2 Primary Research

2.3 Market Size Estimation

2.4 Data Triangulation

2.5 Assumptions for the Study

Chapter 3. Executive Summary

Chapter 4. Introduction

4.1 Definition of Market Segments

4.1.1 By Type

4.1.1.1 Product

4.1.1.1.1 Hardware

4.1.1.1.2 Software

4.1.1.2 Service

4.1.1.2.1 Professional

4.1.1.2.2 Managed

4.1.2 By Technology

4.1.2.1 Machine learning

4.1.2.2 Computer vision

4.1.2.3 Predictive analytics

4.1.3 By Application

4.1.3.1 Agricultural robots

4.1.3.2 Precision farming

4.1.3.3 Drone analytics

4.1.3.4 Livestock monitoring

4.1.3.5 Others

4.2 Value Chain Analysis

4.3 Market Dynamics

4.3.1 Trends

4.3.1.1 Increasing use of robotics in agriculture

4.3.1.2 Increasing use of smart sensors in agriculture

4.3.2 Drivers

4.3.2.1 Growing demand for agricultural production

4.3.2.2 Rising adoption of internet of things (IoT)

4.3.2.3 Increasing demand for monitoring of livestock

4.3.2.4 Increasing demand for drones in agricultural farms

4.3.2.5 Impact analysis of drivers on market forecast

4.3.3 Restraints

4.3.3.1 Lack of awareness and high cost of AI solutions

4.3.3.2 Impact analysis of restraints on market forecast

4.3.4 Opportunities

4.3.4.1 Growth opportunities from developing countries

4.3.4.2 AI powered chatbots

4.4 Impact of COVID-19 on AI in Agriculture Market

4.4.1 Current Scenario

4.4.2 COVID-19 Scenario

4.4.3 Future Scenario

4.5 Porter's Five Forces Analysis

Chapter 5. Global Market Size and Forecast

5.1 By Type

5.1.1 Product, by Type

5.1.2 Service, by type

5.2 By Technology

5.3 By Application

5.4 By Region

Chapter 6. North America Market Size and Forecast

Chapter 7. Europe Market Size and Forecast

Chapter 8. APAC Market Size and Forecast

Chapter 9. LATAM Market Size and Forecast

Chapter 10. MEA Market Size and Forecast

Chapter 11. Major Countries

11.1 U.S. AI in Agriculture Market

11.2 U.K. AI in Agriculture Market

11.3 Germany AI in Agriculture Market

11.4 China AI in Agriculture Market

11.5 Japan AI in Agriculture Market

Chapter 12. Competitive Landscape

12.1 Analysis of Key Players in the Market

12.2 List of Key Players and Their Offerings

12.3 Competitive Benchmarking of Key Players

12.4 Global Strategic Developments of Key Players

Chapter 13. Company Profiles

13.1 Business Overview

13.2 Product and Service Offerings

13.3 Key Financial Summary

  • IBM Corporation
  • Microsoft Corporation
  • Bayer AG
  • Deere & Company
  • A.A.A Taranis Visual Ltd.
  • AgEagle Aerial Systems Inc.
  • AGCO Corporation
  • Raven Industries Inc.
  • Ag Leader Technology
  • Trimble Inc.
  • Google LLC
  • Gamaya SA
  • Granular Inc.

For more information about this report visit https://www.researchandmarkets.com/r/pg6l7f

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Contacts

ResearchAndMarkets.com
Laura Wood, Senior Press Manager
press@researchandmarkets.com
For E.S.T Office Hours Call 1-917-300-0470
For U.S./CAN Toll Free Call 1-800-526-8630
For GMT Office Hours Call +353-1-416-8900