by The generative AI in agriculture market size is poised to grow by USD 1,287.84 million by 2032 from USD 138.06 million in 2022, exhibiting a CAGR of 25.02% during the forecast period 2023-2032.
Key Takeaways:
- North America generated more than 48% of revenue share in 2022.
- By technology, the computer vision segment is expected to grow at the highest CAGR during the forecast period.
- By application, the precision farming segment is expected to dominate the market over the forecast period.
Precedence Research has conducted a comprehensive market study that provides valuable insights into the performance of the market during the forecast period. The study identifies significant trends that are shaping the growth of the Generative AI in agriculture market. In this recently published report, essential dynamics such as drivers, restraints, and opportunities are highlighted for both established market players and emerging participants involved in production and supply.
To begin with, the Generative AI in agriculture Market report features an executive summary that offers a concise overview of the marketplace. It outlines the key players and industry categories expected to have an impact on the market in the coming years. The executive summary provides an unbiased summary of the market.
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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 Gain USD 5,338.09 Mn By 2032
The empirical study on the global Generative AI in agriculture market primarily focuses on the drivers in subsequent sections. It demonstrates how changing demographics are projected to influence the supply and demand dynamics in the Generative AI in agriculture Market. Our market report for the Generative AI in agriculture market also delves into the significant rules and regulations that are likely to impact the future growth of this sector. Moreover, in order to comprehend the underlying demand factors, industry experts have provided insights into its fundamental origins.
Regional Snapshot:
The North American market is projected to dominate the industry throughout the forecast period, primarily driven by the extensive adoption of precision farming. Precision farming, an essential application of generative AI in the agricultural sector, has gained considerable momentum in North America. The region boasts vast agricultural landscapes, prompting the widespread adoption of precision farming techniques, including generative AI and associated technologies. These advanced practices aim to optimize resource utilization and minimize environmental impact. Through the utilization of drones, satellite imagery, and sophisticated data analytics, farmers in North America have successfully implemented precise resource management strategies. Consequently, they have experienced improved crop yields, reduced operational costs, and enhanced sustainability in their farming operations.
Furthermore, strategic collaborations and alliances are prevalent in this region as a means for cloud-based solution providers to strengthen their market presence. An example of such collaboration is the partnership between Progeny Drone Inc., a startup affiliated with Purdue University. They have developed the Plot Phenix program, which enables the conversion of aerial crop images into meaningful data for applications such as plant breeding, crop modeling, and precision agriculture.
Top 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.
Data Sources and Methodology
To gather comprehensive insights on the Global Generative AI in agriculture Market, we relied on a range of data sources and followed a well-defined methodology. Our approach involved interactions with industry experts and key stakeholders across the market’s value chain, including management organizations, processing organizations, and analytics service providers.
We followed a rigorous data analysis process to ensure the quality and credibility of our research. The gathered information was carefully evaluated, and relevant quantitative data was subjected to statistical analysis. By employing robust analytical techniques, we were able to derive meaningful insights and present a comprehensive overview of the Global Generative AI in agriculture Market.
The most resonating, simple, genuine, and important causes because of which you must decide to buy the Generative AI in agriculture market report exclusively from precedence research
- The research report has been meticulously crafted to provide comprehensive knowledge on essential marketing strategies and a holistic understanding of crucial marketing plans spanning the forecasted period from 2023 to 2032.
Key Features of the Report:
- Comprehensive Coverage: The report extensively encompasses a detailed explanation of highly effective analytical marketing methods applicable to companies across all industry sectors.
- Decision-Making Enhancement: It outlines a concise overview of the decision-making process while highlighting key techniques to enhance it, ensuring favorable business outcomes in the future.
- Articulated R&D Approach: The report presents a well-defined approach to conducting research and development (R&D) activities, enabling accurate data acquisition on current and future marketing conditions.
Generative AI in Agriculture Market Segmentation:
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
Reasons to Consider Purchasing the Report:
- Enhance your market research capabilities by accessing this comprehensive and precise report on the global Generative AI in agriculture market.
- Gain a thorough understanding of the overall market landscape and be prepared to overcome challenges while ensuring robust growth.
- Benefit from in-depth research and analysis of the latest trends shaping the global Generative AI in agriculture market.
- Obtain detailed insights into evolving market trends, current and future technologies, and strategic approaches employed by key players in the global Generative AI in agriculture market.
- Receive valuable recommendations and guidance for both new entrants and established players seeking further market expansion.
- Discover not only the cutting-edge technological advancements in the global Generative AI in agriculture market but also the strategic plans of industry leaders.
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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