November 13, 2024
ICT

Generative AI in Agriculture Market Size to Garner USD 1,287.84 Million by 2032

The global generative AI in agriculture market size was estimated to be around US$ 138.06 million in 2022. It is projected to reach US$ 1,287.84 million by 2032, indicating a CAGR of 138.06 % from 2023 to 2032.

Generative AI In Agriculture Market Size 2023 To 2032

The market research report on the Generative AI in agriculture market provides a comprehensive analysis of various key aspects. It includes the definition, classification, and application of Generative AI in agriculture products. The report examines the development trends, competitive landscape, and industrial chain structure within the industry. Furthermore, it presents an overview of the industry, analyzes national policies and planning, and offers insights into the latest market dynamics and opportunities at a global level.

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Generative AI in Agriculture Market Report Scope

Report Coverage Details
Market Size in 2023 USD 172.6 Million
Market Size by 2032 USD 1,287.84 Million
Growth Rate from 2023 to 2032 CAGR of 25.02%
Largest Market North America
Base Year 2022
Forecast Period 2023 to 2032
Segments Covered By Technology and By Application
Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa

Read More: Generative AI in Energy Market Size to Attain USD 5,338.09 Million By 2030

The report presents the volume and value-based market size for the base year 2022 and forecasts the market’s growth between 2023 and 2032. It estimates market numbers based on product form and application, providing size and forecast for each application segment in both global and regional markets.

Focusing on the global Generative AI in agriculture market, the report highlights its status, future forecasts, growth opportunities, key market players, and key market regions such as the United States, Europe, and China. The study aims to present the development of the Generative AI in agriculture market by considering factors like Year-on-Year (Y-o-Y) growth, in addition to Compound Annual Growth Rate (CAGR). This approach enables a better understanding of market certainty and the identification of lucrative opportunities.

Regarding production, the report investigates the capacity, production, value, ex-factory price, growth rate, and market share of major manufacturers, regions, and product types. On the consumption side, the report focuses on the regional consumption of Generative AI in agriculture products across different countries and applications.

Buyers of the report gain access to verified market figures, including global market size in terms of revenue and volume. The report provides reliable estimations and calculations for global revenue and volume by product type from 2023 to 2032. It also includes accurate figures for production capacity and production by region during the same period.

The research includes product parameters, production processes, cost structures, and data classified by region, technology, and application. Furthermore, it conducts SWOT analysis and investment feasibility studies for new projects.

This in-depth research report offers valuable insights into the Generative AI in agriculture market. It employs an objective and fair approach to analyze industry trends, supporting customer competition analysis, development planning, and investment decision-making. The project received support and assistance from technicians and marketing personnel across various links in the industry chain.

The competitive landscape section of the report provides detailed information on Generative AI in agriculture market competitors. It includes company overviews, financials, revenue generation, market potential, research and development investments, new market initiatives, global presence, production sites, production capacities, strengths and weaknesses, product launches, product range, and application dominance. However, the data points provided only focus on the companies’ activities related to the Generative AI in agriculture market.

Prominent players in the market are expected to face tough competition from new entrants. Key players are targeting acquisitions of startup companies to maintain their dominance. The report

Reasons to Purchase this Report:

  • Comprehensive market segmentation analysis incorporating qualitative and quantitative research, considering the impact of economic and policy factors.
  • In-depth regional and country-level analysis, examining the demand and supply dynamics that influence market growth.
  • Market size in USD million and volume in million units provided for each segment and sub-segment.
  • Detailed competitive landscape, including market share of major players, recent projects, and strategies implemented over the past five years.
  • Comprehensive company profiles encompassing product offerings, key financial information, recent developments, SWOT analysis, and employed strategies by major market players.

Key Players

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

Generative AI in Agriculture Market Segmentations

By Technology

  • Machine Learning
  • Computer Vision
  • Predictive Analytics

By Application

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

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

TABLE OF CONTENT

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology (Premium Insights)

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Generative AI in Agriculture Market 

5.1. COVID-19 Landscape: Generative AI in Agriculture Industry Impact

5.2. COVID 19 – Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Generative AI in Agriculture Market, By Technology

8.1. Generative AI in Agriculture Market, by Technology, 2023-2032

8.1.1. Machine Learning

8.1.1.1. Market Revenue and Forecast (2020-2032)

8.1.2. Computer Vision

8.1.2.1. Market Revenue and Forecast (2020-2032)

8.1.3. Predictive Analytics

8.1.3.1. Market Revenue and Forecast (2020-2032)

Chapter 9. Global Generative AI in Agriculture Market, By Application

9.1. Generative AI in Agriculture Market, by Application, 2023-2032

9.1.1. Precision Farming

9.1.1.1. Market Revenue and Forecast (2020-2032)

9.1.2. Agriculture Robots

9.1.2.1. Market Revenue and Forecast (2020-2032)

9.1.3. Livestock Monitoring

9.1.3.1. Market Revenue and Forecast (2020-2032)

9.1.4. Drone Analytics

9.1.4.1. Market Revenue and Forecast (2020-2032)

9.1.5. Labor Management

9.1.5.1. Market Revenue and Forecast (2020-2032)

9.1.6. Others

9.1.6.1. Market Revenue and Forecast (2020-2032)

Chapter 10. Global Generative AI in Agriculture Market, Regional Estimates and Trend Forecast

10.1. North America

10.1.1. Market Revenue and Forecast, by Technology (2020-2032)

10.1.2. Market Revenue and Forecast, by Application (2020-2032)

10.1.3. U.S.

10.1.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.1.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.1.4. Rest of North America

10.1.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.1.4.2. Market Revenue and Forecast, by Application (2020-2032)

10.2. Europe

10.2.1. Market Revenue and Forecast, by Technology (2020-2032)

10.2.2. Market Revenue and Forecast, by Application (2020-2032)

10.2.3. UK

10.2.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.2.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.2.4. Germany

10.2.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.2.4.2. Market Revenue and Forecast, by Application (2020-2032)

10.2.5. France

10.2.5.1. Market Revenue and Forecast, by Technology (2020-2032)

10.2.5.2. Market Revenue and Forecast, by Application (2020-2032)

10.2.6. Rest of Europe

10.2.6.1. Market Revenue and Forecast, by Technology (2020-2032)

10.2.6.2. Market Revenue and Forecast, by Application (2020-2032)

10.3. APAC

10.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.3.3. India

10.3.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.3.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.3.4. China

10.3.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.3.4.2. Market Revenue and Forecast, by Application (2020-2032)

10.3.5. Japan

10.3.5.1. Market Revenue and Forecast, by Technology (2020-2032)

10.3.5.2. Market Revenue and Forecast, by Application (2020-2032)

10.3.6. Rest of APAC

10.3.6.1. Market Revenue and Forecast, by Technology (2020-2032)

10.3.6.2. Market Revenue and Forecast, by Application (2020-2032)

10.4. MEA

10.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.4.2. Market Revenue and Forecast, by Application (2020-2032)

10.4.3. GCC

10.4.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.4.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.4.4. North Africa

10.4.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.4.4.2. Market Revenue and Forecast, by Application (2020-2032)

10.4.5. South Africa

10.4.5.1. Market Revenue and Forecast, by Technology (2020-2032)

10.4.5.2. Market Revenue and Forecast, by Application (2020-2032)

10.4.6. Rest of MEA

10.4.6.1. Market Revenue and Forecast, by Technology (2020-2032)

10.4.6.2. Market Revenue and Forecast, by Application (2020-2032)

10.5. Latin America

10.5.1. Market Revenue and Forecast, by Technology (2020-2032)

10.5.2. Market Revenue and Forecast, by Application (2020-2032)

10.5.3. Brazil

10.5.3.1. Market Revenue and Forecast, by Technology (2020-2032)

10.5.3.2. Market Revenue and Forecast, by Application (2020-2032)

10.5.4. Rest of LATAM

10.5.4.1. Market Revenue and Forecast, by Technology (2020-2032)

10.5.4.2. Market Revenue and Forecast, by Application (2020-2032)

Chapter 11. Company Profiles

11.1. Google LLC

11.1.1. Company Overview

11.1.2. Product Offerings

11.1.3. Financial Performance

11.1.4. Recent Initiatives

11.2. Microsoft Corporation

11.2.1. Company Overview

11.2.2. Product Offerings

11.2.3. Financial Performance

11.2.4. Recent Initiatives

11.3. AGCO Corporation

11.3.1. Company Overview

11.3.2. Product Offerings

11.3.3. Financial Performance

11.3.4. Recent Initiatives

11.4. Deere & Company

11.4.1. Company Overview

11.4.2. Product Offerings

11.4.3. Financial Performance

11.4.4. Recent Initiatives

11.5. A.A.A Taranis Visual L

11.5.1. Company Overview

11.5.2. Product Offerings

11.5.3. Financial Performance

11.5.4. Recent Initiatives

11.6. AgEagle Aerial Systems Inc.

11.6.1. Company Overview

11.6.2. Product Offerings

11.6.3. Financial Performance

11.6.4. Recent Initiatives

11.7. Bayer AG

11.7.1. Company Overview

11.7.2. Product Offerings

11.7.3. Financial Performance

11.7.4. Recent Initiatives

11.8. Raven Industries Inc.

11.8.1. Company Overview

11.8.2. Product Offerings

11.8.3. Financial Performance

11.8.4. Recent Initiatives

11.9. Ag Leader Technology

11.9.1. Company Overview

11.9.2. Product Offerings

11.9.3. Financial Performance

11.9.4. Recent Initiatives

11.10. Trimble Inc.

11.10.1. Company Overview

11.10.2. Product Offerings

11.10.3. Financial Performance

11.10.4. Recent Initiatives

Chapter 12. Research Methodology

12.1. Primary Research

12.2. Secondary Research

12.3. Assumptions

Chapter 13. Appendix

13.1. About Us

13.2. Glossary of Terms

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Prathamesh

I have completed my education in Bachelors in Computer Application. A focused learner having a keen interest in the field of digital marketing, SEO, SMM, and Google Analytics enthusiastic to learn new things along with building leadership skills.

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