Industry Overview
The AI farming market, also known as precision agriculture or smart farming, involves the use of artificial intelligence technologies to enhance agricultural productivity and sustainability. AI applications in farming include crop monitoring, yield prediction, automated irrigation, and pest control. These technologies help farmers make data-driven decisions, optimize resource use, and improve crop quality. The market is driven by the growing global population, the need for increased food production, and advancements in AI and IoT technologies.The AI Farming market is experiencing robust growth, projected to achieve a compound annual growth rate CAGR of 14.00% during the forecast period. Valued at 3.0Billion, the market is expected to reach 5.5Billion by 2032, with a year-on-year growth rate of 11%
AI Farming Market Size in (USD Billion) CAGR Growth Rate 14.00%
| Study Period | 2020-2032 |
| Market Size (2024): | 3.0Billion |
| Market Size (2032): | 5.5Billion |
| CAGR (2024 - 2032): | 14.00% |
| Fastest Growing Region | Europe |
| Dominating Region | North America |
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Data Collection Method
Data triangulation is a method used to analyze markets by gathering and comparing information from multiple sources or utilizing different research approaches to examine the same topic. This technique involves integrating data from various sources, such as surveys, interviews, and industry reports, or combining both qualitative and quantitative methods. By employing data triangulation, researchers can cross-verify information, reduce biases, and achieve a more accurate and comprehensive understanding of market dynamics.
Key Highlights of the AI Farming
• The AI Farming is growing at a CAGR of 14.00% during the forecasted period of 2024 to {FORECAT_YEAR}
• Year on Year growth for the market is 11%
• North America dominated the market share of 3.0Billion in 2024
• Based on type, the market is bifurcated into Crop Management, Soil Monitoring, Pest Control, Yield Prediction segment dominated the market share during the forecasted period
Market Segmentation
Segmentation by Type
- Crop Management
- Soil Monitoring
- Pest Control
- Yield Prediction
AI Farming Market Segmentation by Type
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Segmentation by Application
Precision Agriculture, Crop Management, Supply Chain, Livestock Management, Resource Management
AI Farming Market Segmentation by Application
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This report also splits the market by region
Regions
- North America
- LATAM
- West Europe
- Central & Eastern Europe
- Northern Europe
- Southern Europe
- East Asia
- Southeast Asia
- South Asia
- Central Asia
- Oceania
- MEA
Fastest Growing Region
Europe
Dominating Region
North America
Regional Insights
The AI Farming market exhibits significant regional variation, shaped by different economic conditions and consumer behaviours.
- North America: High disposable incomes and a robust e-commerce sector are driving demand for premium and convenient products.
- Europe: A fragmented market where Western Europe emphasizes luxury and organic products, while Eastern Europe experiences rapid growth.
- Asia-Pacific: Urbanization and a growing middle class drive demand for both high-tech and affordable products, positioning the region as a fast-growing market.
- Latin America: Economic fluctuations make affordability a key factor, with Brazil and Mexico leading the way in market expansion.
- Middle East & Africa: Luxury products are prominent in the Gulf States, while Sub-Saharan Africa sees gradual market growth, influenced by local preferences.
Key Players
The companies highlighted in this profile were selected based on insights from primary experts and an evaluation of their market penetration, product offerings, and geographical reach:
- John Deere
- The Climate Corporation (Bayer)
- Trimble
- Raven Industries
- Granular
- AgJunction
- Farmers Business Network
- Sentera
- Deere & Company
- Bayer Crop Science
- Nutrien
- Lindsay Corporation
- Valmont Industries
- AgCO
- CNH Industrial
- Kubota
- Monsanto (Bayer)
- DowDuPont ( Corteva Agriscience)
- BASF
- Syngenta (ChemChina)
- Microsoft (Azure IoT)
- IBM (Watson IoT)
- Google (Cloud IoT)
- Amazon Web Services (AWS IoT)
- DJI
- Hexagon AB
- Topcon Positioning Systems
- AGCO Corporation
- CNH Industrial N.V.
- Kubota Corporation
- Monsanto Company
- DowDuPont Inc.
- BASF SE
- Syngenta AG
- Microsoft Corporation
- International Business Machines Corporation
- Alphabet Inc. (Google)
- Amazon.com
AI Farming Market Segmentation by Players
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Companies within the industry are increasingly concentrating on broadening their market presence through a variety of strategic initiatives. These include mergers and acquisitions, as well as green investments, particularly in underdeveloped regions. Such strategies are proving instrumental in enabling these companies to capture a larger share of the market. By consolidating resources and expanding their geographical footprint, they not only enhance their competitive edge but also contribute to sustainable development in emerging markets. This approach not only fosters growth but also aligns with global trends toward environmental responsibility and corporate sustainability.
Competitive Landscape
The competitive landscape is shaped by a mix of global leaders and regional players, with large companies like John Deere, The Climate Corporation (Bayer), Trimble, Raven Industries, Granular, AgJunction, Farmers Business Network, Sentera, Deere & Company, Bayer Crop Science, Nutrien, Lindsay Corporation, Valmont Industries, AgCO, CNH Industrial, Kubota, Monsanto (Bayer), DowDuPont ( Corteva Agriscience), BASF, Syngenta (ChemChina), Microsoft (Azure IoT), IBM (Watson IoT), Google (Cloud IoT), Amazon Web Services (AWS IoT), DJI, Hexagon AB, Topcon Positioning Systems, AGCO Corporation, CNH Industrial N.V., Kubota Corporation, Monsanto Company, DowDuPont Inc., BASF SE, Syngenta AG, Microsoft Corporation, International Business Machines Corporation, Alphabet Inc. (Google), Amazon.com dominating the market through their extensive resources, innovation, and established brand presence. However, emerging players are disrupting the market with niche products and innovative technologies, challenging the incumbents. Pricing strategies vary, with larger firms benefiting from economies of scale while smaller players offer value-added services or customization. Geographical reach is key, as global companies expand across regions, while regional firms focus on local markets. Strategic partnerships and mergers continue to reshape the landscape, and barriers to entry remain high due to capital requirements and regulatory hurdles.
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Price Trend Analysis
Price trend analysis is the study of historical pricing data to identify patterns and predict future price movements. It provides businesses with insights into how prices for goods or services change over time due to factors like market demand, supply levels, economic conditions, and external influences such as inflation or raw material costs.This analysis is critical for businesses as it helps in developing effective pricing strategies. By understanding pricing trends, companies can adjust their prices to remain competitive while safeguarding their profit margins. For example, if a business anticipates a rise in material costs, it can adjust its pricing or production plan to mitigate the impact.
Price trend analysis is also essential for forecasting. It allows companies to predict future price fluctuations and plan accordingly, whether for purchasing, production, or sales strategies. This is particularly important for industries where price volatility is common, such as commodities or seasonal products.
Furthermore, analysing price trends offers valuable market insights. Businesses can gain a clearer view of consumer behaviour, competitor pricing tactics, and overall market health. This helps in making informed decisions about product positioning, promotions, and inventory management.
In short, price trend analysis is a crucial tool that enables businesses to remain agile, mitigate risks, and drive profitability.
Dynamics
Market dynamics refer to the forces that influence the supply and demand of products and services within a market. These forces include factors such as consumer preferences, technological advancements, regulatory changes, economic conditions, and competitive actions. Understanding market dynamics is crucial for businesses as it helps them anticipate changes, identify opportunities, and mitigate risks.
By analyzing market dynamics, companies can better understand market trends, predict potential shifts, and develop strategic responses. This analysis enables businesses to align their product offerings, pricing strategies, and marketing efforts with evolving market conditions, ultimately leading to more informed decision-making and a stronger competitive position in the marketplace.
- Precision Agriculture Adoption
- Crop Yield Improvement Needs
- Labor Cost Reduction
- Sustainable Farming Practices
- IoT Integration
- Autonomous equipment
- AI-powered crop monitoring
- predictive analytics
- drone technology
- soil health management
- Increased Crop Productivity
- Resource Efficiency
- New Agri-tech Startups
- Data Monetization
- Tailored Solutions
- High Initial Investment
- Technical Complexity
- Data Privacy
- Farmer Adoption Resistance
- Infrastructure Needs
Research Process
The research process is a systematic approach to gathering and analyzing information in order to address specific questions or hypotheses. It typically begins with identifying a problem or research question that needs exploration. Once the question is defined, researchers review existing literature to gain a deeper understanding of the subject and identify gaps that need addressing.
Next, researchers develop a research plan or methodology, outlining how data will be collected and analyzed. This may involve choosing between qualitative, quantitative, or mixed methods depending on the nature of the research. Data collection methods can include surveys, experiments, observations, or secondary data analysis.
Once data is collected, the next step is analyzing the information using appropriate tools or techniques, such as statistical software for quantitative data or thematic analysis for qualitative data. This analysis helps draw conclusions and identify patterns relevant to the research question.
Finally, the findings are interpreted and communicated through reports, presentations, or publications. The results are often compared against the initial hypotheses, and limitations or further areas of study are highlighted. This structured process ensures that research is rigorous, transparent, and reliable, contributing valuable insights to the field of study.
|
Report Features |
Details |
|
Base Year |
2025 |
|
Based Year Market Size (2023) |
3.0Billion |
|
Historical Period Market Size (2019) |
1.8Billion |
|
CAGR (2024 to 2030) |
14.00% |
|
Forecast Period |
2025 to 2032 |
|
Forecasted Period Market Size (2030) |
5.5Billion |
|
Scope of the Report |
Crop Management, Soil Monitoring, Pest Control, Yield Prediction, Precision Agriculture, Crop Management, Supply Chain, Livestock Management, Resource Management |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and MEA |
|
Year on Year Growth |
11% |
|
Companies Covered |
John Deere, The Climate Corporation (Bayer), Trimble, Raven Industries, Granular, AgJunction, Farmers Business Network, Sentera, Deere & Company, Bayer Crop Science, Nutrien, Lindsay Corporation, Valmont Industries, AgCO, CNH Industrial, Kubota, Monsanto (Bayer), DowDuPont ( Corteva Agriscience), BASF, Syngenta (ChemChina), Microsoft (Azure IoT), IBM (Watson IoT), Google (Cloud IoT), Amazon Web Services (AWS IoT), DJI, Hexagon AB, Topcon Positioning Systems, AGCO Corporation, CNH Industrial N.V., Kubota Corporation, Monsanto Company, DowDuPont Inc., BASF SE, Syngenta AG, Microsoft Corporation, International Business Machines Corporation, Alphabet Inc. (Google), Amazon.com |
|
Customization Scope |
15% Free Customization (For EG) |
|
Delivery Format |
PDF and Excel through Email |
AI Farming - Table of Contents
Chapter 1: Market Preface
- 1.1 Global AI Farming Market Landscape
- 1.2 Scope of the Study
- 1.3 Relevant Findings & Stakeholder Advantages
Chapter 2: Strategic Overview
- 2.1 Global AI Farming Market Outlook
- 2.2 Total Addressable Market versus Serviceable Market
- 2.3 Market Rivalry Projection
Chapter 3 : Global AI Farming Market Business Environment & Changing Dynamics
-
3.1 Growth Drivers
- 3.1.1 Precision agriculture adoption
- 3.1.2 crop yield improvement needs
- 3.1.3 labor cost reduction
- 3.1.4 sustainable farming practices
- 3.1.5 IoT integration
-
3.2 Available Opportunities
- 3.2.1 Increased crop productivity
- 3.2.2 resource efficiency
- 3.2.3 new agri-tech startups
- 3.2.4 data monetization
- 3.2.5 tailored solutions
- 3.2.6
-
3.3 Influencing Trends
- 3.3.1 Autonomous equipment
- 3.3.2 AI-powered crop monitoring
- 3.3.3 predictive analytics
- 3.3.4 drone technology
- 3.3.5 soil health management
- 3.3.6
-
3.4 Challenges
- 3.4.1 High initial investment
- 3.4.2 technical complexity
- 3.4.3 data privacy
- 3.4.4 farmer adoption resistance
- 3.4.5 infrastructure needs
- 3.4.6 re
- 3.5 Regional Dynamics
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Chapter 4 : Global AI Farming Industry Factors Assessment
- 4.1 Current Scenario
- 4.2 PEST Analysis
- 4.3 Business Environment - PORTER 5-Forces Analysis
- 4.3.1 Supplier Leverage
- 4.3.2 Bargaining Power of Buyers
- 4.3.3 Threat of Substitutes
- 4.3.4 Threat from New Entrant
- 4.3.5 Market Competition Level
- 4.4 Roadmap of AI Farming Market
- 4.5 Impact of Macro-Economic Factors
- 4.6 Market Entry Strategies
- 4.7 Political and Regulatory Landscape
- 4.8 Supply Chain Analysis
- 4.9 Impact of Tariff War
Chapter 5: AI Farming : Competition Benchmarking & Performance Evaluation
- 5.1 Global AI Farming Market Concentration Ratio
- 5.1.1 CR4, CR8 and HH Index
- 5.1.2 % Market Share - Top 3
- 5.1.3 Market Holding by Top 5
- 5.2 Market Position of Manufacturers by AI Farming Revenue 2024
- 5.3 Global AI Farming Sales Volume by Manufacturers (2024)
- 5.4 BCG Matrix
- 5.4 Market Entropy
- 5.5 FPNV Positioning Matrix
- 5.6 Heat Map Analysis
Chapter 6: Global AI Farming Market: Company Profiles
- 6.1 John Deere
- 6.1.1 John Deere Company Overview
- 6.1.2 John Deere Product/Service Portfolio & Specifications
- 6.1.3 John Deere Key Financial Metrics
- 6.1.4 John Deere SWOT Analysis
- 6.1.5 John Deere Development Activities
- 6.2 The Climate Corporation (Bayer)
- 6.3 Trimble
- 6.4 Raven Industries
- 6.5 Granular
- 6.6 AgJunction
- 6.7 Farmers Business Network
- 6.8 Sentera
- 6.9 Deere & Company
- 6.10 Bayer Crop Science
- 6.11 Nutrien
- 6.12 Lindsay Corporation
- 6.13 Valmont Industries
- 6.14 AgCO
- 6.15 CNH Industrial
- 6.16 Kubota
- 6.17 Monsanto (Bayer)
- 6.18 DowDuPont ( Corteva Agriscience)
- 6.19 BASF
- 6.20 Syngenta (ChemChina)
- 6.21 Microsoft (Azure IoT)
- 6.22 IBM (Watson IoT)
- 6.23 Google (Cloud IoT)
- 6.24 Amazon Web Services (AWS IoT)
- 6.25 DJI
- 6.26 Hexagon AB
- 6.27 Topcon Positioning Systems
- 6.28 AGCO Corporation
- 6.29 CNH Industrial N.V.
- 6.30 Kubota Corporation
- 6.31 Monsanto Company
- 6.32 DowDuPont Inc.
- 6.33 BASF SE
- 6.34 Syngenta AG
- 6.35 Microsoft Corporation
- 6.36 International Business Machines Corporation
- 6.37 Alphabet Inc. (Google)
- 6.38 Amazon.com
- 6.39 Inc.
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Chapter 7 : Global AI Farming by Type & Application (2020-2032)
-
7.1 Global AI Farming Market Revenue Analysis (USD Million) by Type (2020-2024)
- 7.1.1 Crop Management
- 7.1.2 Soil Monitoring
- 7.1.3 Pest Control
- 7.1.4 Yield Prediction
- 7.1.5 Farm Automation
-
7.2 Global AI Farming Market Revenue Analysis (USD Million) by Application (2020-2024)
- 7.2.1 Precision Agriculture
- 7.2.2 Crop Management
- 7.2.3 Supply Chain
- 7.2.4 Livestock Management
- 7.2.5 Resource Management
- 7.3 Global AI Farming Market Revenue Analysis (USD Million) by Type (2024-2032)
- 7.4 Global AI Farming Market Revenue Analysis (USD Million) by Application (2024-2032)
Chapter 8 : North America AI Farming Market Breakdown by Country, Type & Application
- 8.1 North America AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 8.1.1 United States
- 8.1.2 Canada
-
8.2 North America AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 8.2.1 Crop Management
- 8.2.2 Soil Monitoring
- 8.2.3 Pest Control
- 8.2.4 Yield Prediction
- 8.2.5 Farm Automation
-
8.3 North America AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 8.3.1 Precision Agriculture
- 8.3.2 Crop Management
- 8.3.3 Supply Chain
- 8.3.4 Livestock Management
- 8.3.5 Resource Management
- 8.4 North America AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 8.5 North America AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 8.6 North America AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
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Chapter 9 : LATAM AI Farming Market Breakdown by Country, Type & Application
- 9.1 LATAM AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 9.1.1 Brazil
- 9.1.2 Argentina
- 9.1.3 Chile
- 9.1.4 Mexico
- 9.1.5 Rest of LATAM
-
9.2 LATAM AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 9.2.1 Crop Management
- 9.2.2 Soil Monitoring
- 9.2.3 Pest Control
- 9.2.4 Yield Prediction
- 9.2.5 Farm Automation
-
9.3 LATAM AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 9.3.1 Precision Agriculture
- 9.3.2 Crop Management
- 9.3.3 Supply Chain
- 9.3.4 Livestock Management
- 9.3.5 Resource Management
- 9.4 LATAM AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 9.5 LATAM AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 9.6 LATAM AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 10 : West Europe AI Farming Market Breakdown by Country, Type & Application
- 10.1 West Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 10.1.1 Germany
- 10.1.2 France
- 10.1.3 Benelux
- 10.1.4 Switzerland
- 10.1.5 Rest of West Europe
-
10.2 West Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 10.2.1 Crop Management
- 10.2.2 Soil Monitoring
- 10.2.3 Pest Control
- 10.2.4 Yield Prediction
- 10.2.5 Farm Automation
-
10.3 West Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 10.3.1 Precision Agriculture
- 10.3.2 Crop Management
- 10.3.3 Supply Chain
- 10.3.4 Livestock Management
- 10.3.5 Resource Management
- 10.4 West Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 10.5 West Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 10.6 West Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 11 : Central & Eastern Europe AI Farming Market Breakdown by Country, Type & Application
- 11.1 Central & Eastern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 11.1.1 Bulgaria
- 11.1.2 Poland
- 11.1.3 Hungary
- 11.1.4 Romania
- 11.1.5 Rest of CEE
-
11.2 Central & Eastern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 11.2.1 Crop Management
- 11.2.2 Soil Monitoring
- 11.2.3 Pest Control
- 11.2.4 Yield Prediction
- 11.2.5 Farm Automation
-
11.3 Central & Eastern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 11.3.1 Precision Agriculture
- 11.3.2 Crop Management
- 11.3.3 Supply Chain
- 11.3.4 Livestock Management
- 11.3.5 Resource Management
- 11.4 Central & Eastern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 11.5 Central & Eastern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 11.6 Central & Eastern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 12 : Northern Europe AI Farming Market Breakdown by Country, Type & Application
- 12.1 Northern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 12.1.1 The United Kingdom
- 12.1.2 Sweden
- 12.1.3 Norway
- 12.1.4 Baltics
- 12.1.5 Ireland
- 12.1.6 Rest of Northern Europe
-
12.2 Northern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 12.2.1 Crop Management
- 12.2.2 Soil Monitoring
- 12.2.3 Pest Control
- 12.2.4 Yield Prediction
- 12.2.5 Farm Automation
-
12.3 Northern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 12.3.1 Precision Agriculture
- 12.3.2 Crop Management
- 12.3.3 Supply Chain
- 12.3.4 Livestock Management
- 12.3.5 Resource Management
- 12.4 Northern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 12.5 Northern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 12.6 Northern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 13 : Southern Europe AI Farming Market Breakdown by Country, Type & Application
- 13.1 Southern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 13.1.1 Spain
- 13.1.2 Italy
- 13.1.3 Portugal
- 13.1.4 Greece
- 13.1.5 Rest of Southern Europe
-
13.2 Southern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 13.2.1 Crop Management
- 13.2.2 Soil Monitoring
- 13.2.3 Pest Control
- 13.2.4 Yield Prediction
- 13.2.5 Farm Automation
-
13.3 Southern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 13.3.1 Precision Agriculture
- 13.3.2 Crop Management
- 13.3.3 Supply Chain
- 13.3.4 Livestock Management
- 13.3.5 Resource Management
- 13.4 Southern Europe AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 13.5 Southern Europe AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 13.6 Southern Europe AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 14 : East Asia AI Farming Market Breakdown by Country, Type & Application
- 14.1 East Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 14.1.1 China
- 14.1.2 Japan
- 14.1.3 South Korea
- 14.1.4 Taiwan
- 14.1.5 Others
-
14.2 East Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 14.2.1 Crop Management
- 14.2.2 Soil Monitoring
- 14.2.3 Pest Control
- 14.2.4 Yield Prediction
- 14.2.5 Farm Automation
-
14.3 East Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 14.3.1 Precision Agriculture
- 14.3.2 Crop Management
- 14.3.3 Supply Chain
- 14.3.4 Livestock Management
- 14.3.5 Resource Management
- 14.4 East Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 14.5 East Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 14.6 East Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 15 : Southeast Asia AI Farming Market Breakdown by Country, Type & Application
- 15.1 Southeast Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 15.1.1 Vietnam
- 15.1.2 Singapore
- 15.1.3 Thailand
- 15.1.4 Malaysia
- 15.1.5 Indonesia
- 15.1.6 Philippines
- 15.1.7 Rest of SEA Countries
-
15.2 Southeast Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 15.2.1 Crop Management
- 15.2.2 Soil Monitoring
- 15.2.3 Pest Control
- 15.2.4 Yield Prediction
- 15.2.5 Farm Automation
-
15.3 Southeast Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 15.3.1 Precision Agriculture
- 15.3.2 Crop Management
- 15.3.3 Supply Chain
- 15.3.4 Livestock Management
- 15.3.5 Resource Management
- 15.4 Southeast Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 15.5 Southeast Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 15.6 Southeast Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 16 : South Asia AI Farming Market Breakdown by Country, Type & Application
- 16.1 South Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 16.1.1 India
- 16.1.2 Bangladesh
- 16.1.3 Others
-
16.2 South Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 16.2.1 Crop Management
- 16.2.2 Soil Monitoring
- 16.2.3 Pest Control
- 16.2.4 Yield Prediction
- 16.2.5 Farm Automation
-
16.3 South Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 16.3.1 Precision Agriculture
- 16.3.2 Crop Management
- 16.3.3 Supply Chain
- 16.3.4 Livestock Management
- 16.3.5 Resource Management
- 16.4 South Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 16.5 South Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 16.6 South Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 17 : Central Asia AI Farming Market Breakdown by Country, Type & Application
- 17.1 Central Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 17.1.1 Kazakhstan
- 17.1.2 Tajikistan
- 17.1.3 Others
-
17.2 Central Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 17.2.1 Crop Management
- 17.2.2 Soil Monitoring
- 17.2.3 Pest Control
- 17.2.4 Yield Prediction
- 17.2.5 Farm Automation
-
17.3 Central Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 17.3.1 Precision Agriculture
- 17.3.2 Crop Management
- 17.3.3 Supply Chain
- 17.3.4 Livestock Management
- 17.3.5 Resource Management
- 17.4 Central Asia AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 17.5 Central Asia AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 17.6 Central Asia AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 18 : Oceania AI Farming Market Breakdown by Country, Type & Application
- 18.1 Oceania AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 18.1.1 Australia
- 18.1.2 New Zealand
- 18.1.3 Others
-
18.2 Oceania AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 18.2.1 Crop Management
- 18.2.2 Soil Monitoring
- 18.2.3 Pest Control
- 18.2.4 Yield Prediction
- 18.2.5 Farm Automation
-
18.3 Oceania AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 18.3.1 Precision Agriculture
- 18.3.2 Crop Management
- 18.3.3 Supply Chain
- 18.3.4 Livestock Management
- 18.3.5 Resource Management
- 18.4 Oceania AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 18.5 Oceania AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 18.6 Oceania AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 19 : MEA AI Farming Market Breakdown by Country, Type & Application
- 19.1 MEA AI Farming Market by Country (USD Million) & Sales Volume (Units) [2020-2024]
- 19.1.1 Turkey
- 19.1.2 South Africa
- 19.1.3 Egypt
- 19.1.4 UAE
- 19.1.5 Saudi Arabia
- 19.1.6 Israel
- 19.1.7 Rest of MEA
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19.2 MEA AI Farming Market by Type (USD Million) & Sales Volume (Units) [2020-2024]
- 19.2.1 Crop Management
- 19.2.2 Soil Monitoring
- 19.2.3 Pest Control
- 19.2.4 Yield Prediction
- 19.2.5 Farm Automation
-
19.3 MEA AI Farming Market by Application (USD Million) & Sales Volume (Units) [2020-2024]
- 19.3.1 Precision Agriculture
- 19.3.2 Crop Management
- 19.3.3 Supply Chain
- 19.3.4 Livestock Management
- 19.3.5 Resource Management
- 19.4 MEA AI Farming Market by Country (USD Million) & Sales Volume (Units) [2025-2032]
- 19.5 MEA AI Farming Market by Type (USD Million) & Sales Volume (Units) [2025-2032]
- 19.6 MEA AI Farming Market by Application (USD Million) & Sales Volume (Units) [2025-2032]
Chapter 20: Research Findings & Conclusion
- 20.1 Key Findings
- 20.2 Conclusion
Chapter 21: Methodology and Data Source
-
21.1 Research Methodology & Approach
- 21.1.1 Research Program/Design
- 21.1.2 Market Size Estimation
- 21.1.3 Market Breakdown and Data Triangulation
-
21.2 Data Source
- 21.2.1 Secondary Sources
- 21.2.2 Primary Sources
Chapter 22: Appendix & Disclaimer
- 22.1 Acronyms & bibliography
- 22.2 Disclaimer
Frequently Asked Questions (FAQ):
The AI Farming Market is growing at a steady pace over the last few years and is expected to grow at a CAGR of 14.00% from 2024 to 2032 to reach a market size of 14.00% 5.5 billion
The AI Farming Market is growing at a CAGR of 14.00% over the forecasted period 2024 - 2032.
Some of the prominent trends that are influencing and driving the growth of Global AI Farming Market are Autonomous Equipment, AI-powered Crop Monitoring, Predictive Analytics, Drone Technology, Soil Health Management, Robotics
- Precision Agriculture Adoption
- Crop Yield Improvement Needs
- Labor Cost Reduction
- Sustainable Farming Practices
- IoT Integration
- Climate Change Adaptation
As Industry players prepare to scale up, AI Farming Market sees major concern such as High Initial Investment, Technical Complexity, Data Privacy, Farmer Adoption Resistance, Infrastructure Needs, Regulatory Compliance.
The market opportunity is clear from the flow of investment into Global AI Farming Market, some of them are Increased Crop Productivity, Resource Efficiency, New Agri-tech Startups, Data Monetization, Tailored Solutions, Government Incentives.
John Deere, The Climate Corporation (Bayer), Trimble, Raven Industries, Granular, AgJunction, Farmers Business Network, Sentera, Deere & Company, Bayer Crop Science, Nutrien, Lindsay Corporation, Valmont Industries, AgCO, CNH Industrial, Kubota, Monsanto (Bayer), DowDuPont ( Corteva Agriscience), BASF, Syngenta (ChemChina), Microsoft (Azure IoT), IBM (Watson IoT), Google (Cloud IoT), Amazon Web Services (AWS IoT), DJI, Hexagon AB, Topcon Positioning Systems, AGCO Corporation, CNH Industrial N.V., Kubota Corporation, Monsanto Company, DowDuPont Inc., BASF SE, Syngenta AG, Microsoft Corporation, International Business Machines Corporation, Alphabet Inc. (Google), Amazon.com, Inc. are the major operating companies profiled in AI Farming market study.
The Global AI Farming Market Study is Broken down by applications such as Precision Agriculture, Crop Management, Supply Chain, Livestock Management, Resource Management.
The Global AI Farming Market Study is segmented by Crop Management, Soil Monitoring, Pest Control, Yield Prediction, Farm Automation.
The Global AI Farming Market Study includes regional breakdown as North America, LATAM, West Europe,Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA
Historical Year: 2020 - Base year: 2024. Forecast period**: 2025 to 2032 [** unless otherwise stated]
The AI farming market, also known as precision agriculture or smart farming, involves the use of artificial intelligence technologies to enhance agricultural productivity and sustainability. AI applications in farming include crop monitoring, yield prediction, automated irrigation, and pest control. These technologies help farmers make data-driven decisions, optimize resource use, and improve crop quality. The market is driven by the growing global population, the need for increased food production, and advancements in AI and IoT technologies.
