Market Definition

In terms of agricultural products and in-field farming procedures, the agricultural sector is rapidly integrating modern technologies such as Artificial Intelligence and machine learning. As the human population continues to grow and land becomes more limited, individuals will need to become more inventive in their farming practises in order to improve efficiency and output. As a result, the agricultural sector is turning to artificial intelligence (AI) technologies to help produce healthier crops, control pests, monitor growth conditions and soil, and reduce labour. AI aids in the analysis of agricultural data because farmers generate massive amounts of data on a regular basis. Farmers can use AI to analyse numerous real-time variables such as water condition, water usage, soil condition, temperature, and market condition. These farmers can make better selections with their assistance. AI technology can also aid in the improvement of harvesting quality and accuracy, a practise known as precision agriculture. Precision agriculture use artificial intelligence (AI) technologies to identify plant disease, pests, and poor plant nutrition on farms. AI can also recommend appropriate herbicides by recognising weeds inside the required buffer zone.

Machine learning, specifically deep learning algorithms, examine crop performance in a variety of climates using decades of field data. Based on this information, one can create a probability model to forecast which genes are most likely to contribute to a plant's favourable attribute. Furthermore, the industry is being driven by an increase in the deployment of cattle facial recognition technology. Dairy farms may now monitor all behavioural features in a group of cattle individually by using advanced metrics such as cattle facial recognition algorithms and image classification along with body condition scores and feeding patterns. However, a lack of consistency in data collecting and data sharing is limiting market growth. Although machine learning, artificial intelligence, and innovative algorithm designs have improved quickly, the collecting of well-tagged, useful agricultural data has lagged. This could stifle market expansion during the predicted period.

The Artificial Intelligence in Agriculture market study includes regional analysis for North America, Europe, Asia Pacific, and the Rest of the World. The Artificial Intelligence in Agriculture market is further split into major nations such as the United States, Canada, Germany, the United Kingdom, France, Italy, China, India, Japan, Brazil, South Africa, and others.

Report Scope

The global market report scope consists of a comprehensive study covering primary factors impacting the industry trends. The study includes analysis of regional and country-level market dynamics. The scope also consists of a competitive overview offering company market shares coupled with company profiles for key revenue contributing companies. The report covers a detailed competitive outlook covering market shares and profiles of key participants in the market share.

Major Market Players

This report offers the major market player’s profiles, such as  International Business Machines Corp. (IBM) (US), Deere & Company (John Deere) (US), Microsoft Corporation (Microsoft) (US), Farmers Edge Inc. (Farmers Edge) (Canada), The Climate Corporation (Climate Corp.) (US), ec2ce (ec2ce) (Spain), Descartes Labs, Inc. (Descartes Labs) (US), AgEagle Aerial Systems (AgEagle) (US), and aWhere Inc. (aWhere) (US)

The Artificial Intelligence in Agriculture Market report has been categorized as below

By technology

  • Machine Learning

  • Computer Vision

  • Predictive Analytics

By offering

  • Hardware

  • Software

  • AI-as-a-Service

  • Services

By application

  • Precision Farming

  • Agriculture Robots

  • Livestock Monitoring

  • Drone Analytics

  • Labor Management

  • Others

By Region

  • North America
  • Europe
  • Asia Pacific
  • Rest of World

The years considered for the study are as follows:

  • Base year - 2020
  • Estimated year - 2021
  • Projected year – 2022
  • Forecast period - 2021 to 2027

Key Questions Addressed by the Report

  • New products/service competitors are exploring?
  • Key players in the Artificial Intelligence in Agriculture Market and how extreme is the competition?
  • What are the future market trends that manufacturers are emphasizing on in the future updates?
  • For each segment, what are the crucial opportunities in the market?
  • What are the key growth strategies embraced by key market players in the market?
  • What are the key success strategies adopted by major competitors in the market?

Why Buy this Report:

  • Obtain comprehensive insights on the Artificial Intelligence in Agriculture market trends
  • Note comprehensive analysis of the market status
  • Identifies the market opportunities and growth segments
  • Assessing business segments & product portfolios, and explain competitive dynamics
  • Provide strategy planning and industry dynamics to strengthen decision making

Report Content

1. Global Artificial Intelligence in Agriculture Market Introduction

1.1. Key Insights

1.2. Report Overview

1.3. Markets Covered

1.4. Stakeholders

2. Research Methodology

2.1. Research Scope

2.2. Market Research Process

2.3. Research Data Analysis

2.4. Market Size Estimation

3. Executive Summary 

4. Market Overview

4.1. Introduction

4.2. Market Drivers and Restraints

5. By technology

5.1.  Machine Learning
5.2.  Computer Vision

5.3. Predictive Analytics

6. By offering

6.1.  Hardware

6.2.  Software

6.3. AI-as-a-Service

6.4. Services

7. By application

7.1.  Precision Farming

7.2.  Agriculture Robots

7.3. Livestock Monitoring

7.4. Drone Analytics

7.5. Labor Management

7.6. Others

8. By Region

8.1. Key Points

8.2. North America

8.3. Europe

8.4. Asia Pacific

8.5. Rest of the World

9. Company Profile

(Profile contains company overview, products/services, financials & recent developments)

9.1. International Business Machines Corp. (IBM) (US)

9.2. Deere & Company (John Deere) (US) 

9.3. Microsoft Corporation (Microsoft) (US) 

9.4. Farmers Edge Inc. (Farmers Edge) (Canada)

9.5. The Climate Corporation (Climate Corp.) (US)

9.6. ec2ce (ec2ce) (Spain)

9.7. Descartes Labs, Inc. (Descartes Labs) (US)

9.8. AgEagle Aerial Systems (AgEagle) (US)

9.9. Where Inc. (aWhere) (US)

The Artificial Intelligence in Agriculture Market report has been categorized as below

By technology

  • Machine Learning

  • Computer Vision

  • Predictive Analytics

By offering

  • Hardware

  • Software

  • AI-as-a-Service

  • Services

By application

  • Precision Farming

  • Agriculture Robots

  • Livestock Monitoring

  • Drone Analytics

  • Labor Management

  • Others

By Region

  • North America
  • Europe
  • Asia Pacific
  • Rest of World

Licence Option

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  • Multiple User-
    5500 USD 3500 USD

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