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市場調查報告書
商品編碼
1556007

全球農業人工智慧市場評估：依技術、產品、應用、部署模式、農場規模、地區、機會、預測，2017-2031年

AI in Agriculture Market Assessment, By Technology, By Offering, By Application, By Deployment Mode, By Farm Size, By Region, Opportunities and Forecast, 2017-2031F
出版日期: | 出版商: Market Xcel - Markets and Data | 英文 221 Pages | 商品交期: 3-5個工作天內

價格

2024-2031年預測期間，全球農業人工智慧市場規模將以24.63%的年複合成長率擴大，從2023年的30.1億美元成長到2031年的175.2億美元。市場的快速擴張是由於採用先進技術作為提高農業生產力和效率的手段。例如，深度學習、機器人視覺和預測技術的使用，這些都是人工智慧的例子，改變傳統的農業方法。這些工具使農民能夠進行精準農業。分析來自感測器、無人機和衛星的資料可以最佳化灌溉、施肥和病蟲害防治，減少資源使用並提高產量。此外，牲畜監測、作物管理和土壤健康分析是人工智慧工具可以發揮關鍵作用的其他潛在領域，幫助農民做出明智的決策。

當今世界對永續農業的需求很高，因為它是應對氣候變遷和不斷成長的全球糧食需求挑戰的解決方案。該領域的領先公司投入大量資源進行創新和技術開發，以開發針對農業問題的人工智慧系統。此外，基於雲端的平台、機器人使用的增加和農場自動化工具預計將促進市場成長。

在區域層面，北美憑藉先進的技術基礎設施和對農業技術的大量投資引領了該市場。然而，隨著中國和印度等國家採用人工智慧技術作為提高農作物產量以實現糧食自給自足的一種方式，亞太地區預計將出現最高的成長率。全球農業人工智慧市場具有巨大的成長潛力，為技術供應商和農民帶來了巨大的潛力。

本報告研究了全球農業人工智慧市場，並提供了市場概況，以及技術、產品、應用、部署模式、農場規模、地區的趨勢，以及進入市場的公司等方面的趨勢。

目錄

第1章 專案範圍與定義

第2章 研究方法

第3章 執行摘要

第4章 顧客回饋

第5章 2017-2031年全球農業人工智慧市場展望

  • 市場規模分析與預測
  • 市佔率分析與預測
  • 2023年市場地圖分析
    • 依技術
    • 依提供
    • 依用途
    • 依部署模式
    • 依農場規模
    • 依地區

第6章 北美農業人工智慧市場展望，2017-2031

第7章 歐洲農業人工智慧市場展望，2017-2031

第8章 亞太地區農業人工智慧市場展望，2017-2031

第9章 2017-2031年南美洲農業人工智慧市場展望

第10章 2017-2031年中東與非洲農業人工智慧市場展望

第11章 供需分析

第12章 價值鏈分析

第13章 波特五力分析

第14章 PESTLE分析

第15章 宏觀經濟指標

第16章 利潤率分析

第17章 市場動態

第18章 市場趨勢與發展

第19章 案例研究

第20章 競爭態勢

  • 前 5 名市場領導者的競爭矩陣
  • 企業生態系分析（新創企業、中小企業與大公司）
  • 前 5 名的公司的SWOT 分析
  • 前10名主要企業狀況
    • Microsoft Corporation
    • Deere & Company
    • IBM Corporation
    • Ever.Ag Corporation
    • Prospera Technologies Ltd.
    • Raven Industries, Inc.
    • Tule Technologies Inc.
    • Trimble Inc.
    • A.A.A Taranis Visual Ltd.
    • Gamaya SA

第21章 策略建議

第22章 查詢及免責聲明

Product Code: MX11907

Global AI in agriculture market is projected to witness a CAGR of 24.63% during the forecast period 2024-2031, growing from USD 3.01 billion in 2023 to USD 17.52 billion in 2031. The fast paced expansion of the market is taking place as advanced technologies are being embraced as measures of increasing agricultural productivity and efficiency. For instance, traditional farming practices have been changed through the use of deep learning, robotic vision, and prognostic techniques which are cases of artificial intelligence. With these tools, farmers can practice precision farming where data from sensors, drones, and satellites is analyzed so that irrigation, fertilization, and pest control can be optimized resulting in reduced resources usage and increased yield. Moreover, livestock monitoring, crop management, and soil health analysis are other potential areas where an AI tool plays a pivotal role, helping farmers to make informed decisions based on precise information.

Sustainable farming practices are in high demand in today's world as they are solutions to climate change challenges and the ever-growing global food requirements. Major companies in this field have put a lot of resources into innovation and technology to come up with artificial intelligence systems that specifically address agricultural issues. Also, cloud-based platforms, rising use of robots, and automation tools in farms are expected to support market growth.

At the regional level, North America is leading this market due to advanced technological infrastructure and large investments in agri-tech. Nevertheless, Asia-Pacific is projected to have the highest growth rates as countries such as China and India have been embracing AI technologies as a way of boosting crop production to be self-sufficient in terms of food. The global AI in agriculture market has potential for immense growth which presents enormous possibilities for technology suppliers and farmers.

In March 2024, a new robot called TOOGO from the French company SIZA Robotics was launched and available for pre-order, with delivery expected in 2025. TOOGO is a commercial pre-series of an autonomous vegetable and beet robot.

Growing Need for Sustainable Agricultural Practices Spur the Adoption of AI in Agriculture

Growing requirements for climatic change and safe food production are major factors in AI in agriculture market which drives its growth. With climate change affecting nations and increasing populations at alarming rates, the world has started emphasizing the use of sustainable agricultural systems that would help in ensuring the availability of food whilst reducing the harm done to nature.

Excessive water, fertilizer, and pesticide applications are often part of the traditional farming exercises that lead to soil degradation, water pollution as well as increased amounts of greenhouse gases in the atmosphere. AI technologies provide solutions by making better use of resources, improving soil health and enhancing efficiency in crop yield. For instance, in February 2024, Carbon Autonomous Robotics Systems launched Track LaserWeeder, an extension to the company's LaserWeeder model. It is made to support the LaserWeeder's weight more effectively in muddy areas and soft soils. When the machine is outfitted with tracks instead of wheels, its ground pressure is limited to 6.5 psi. The improvements include multilingual support for the iPad operator app and spatial data intelligence in the Carbon Ops Center.

In addition, AI instruments support observation of plant well-being, forecasting climatic systems and early detection of pests that enable timely measures which minimize the use of chemicals. Since sustainability is a priority for buyers, governments, and farm owners, AI-based eco-friendly agricultural systems will witness a steady rise in demand, increasing the market size.

Labor Shortages and High Labor Costs Fuel the Market Growth

The adoption of AI technologies in agriculture is being driven essentially by factors such as labor shortages and high labor costs. The declining rural workforce and the rising difficulty in finding skilled labor willing to take up intensive farming tasks present as major challenges faced by the farming industry in many parts of the world today. Additionally, this problem is worsened by an increment in aged farming communities and the migration of youthful workers to cities for improved employment prospects.

Consequently, farmers have a hard time due to mounting labor costs. In this case, there are effective solutions such as the use of AI technologies such as robotics and automation that can help in addressing these challenges by automating repetitive and labor-intensive tasks such as planting, weeding, harvesting, and monitoring crops and livestock. It reduces the reliance on human work and makes it more efficient. In May 2024, DigiFarm AS, a Norwegian company, created an artificial intelligence model capable of autonomously detecting field boundaries. A deep neural network is trained to recognize boundaries and other field features, such trees, grain, and water. With 57 countries providing 4 million hectares of training data, their model has grown to be very vast and requires a substantial amount of processing power for training.

Natural Language Processing Technology Holds a Substantial Market Share

Natural Language Processing (NLP) technology has a huge market share in the AI in agriculture market as it is able to improve communication and decision-making in the farming community. NLP allows user-friendly interfaces and voice-activated systems that can recognize oral language, thus making complex AI applications available to farmers who are less technically skilled. It enables farmers to have conversations with artificial intelligence systems so that they can have access to important information such as weather predictions, pest and disease alerts, and crop management.

In addition, natural language processing can be integrated into virtual assistants and chatbots offering real-time substitutes to aid farmers make choices quickly. Furthermore, it allows conversion of specialist farming knowledge into several dialects, thus creating a broad scope of its application over diverse territories and among different languages. There is a growing need for agriculture-driven AI solutions that are seamless and intuitive together with NLP advantages, including better accessibility and increased data interpretation, contributing to its great acceptance rate in the larger landscape of agricultural AI. In March 2024, Bayer AG launched a GenAI system pilot program planned to help agronomists and farmers in their day-to-day work. The launch is an expert system that can swiftly and precisely respond to agronomy, farm management, and Bayer agricultural goods inquiries. The intuitive technology responds to natural language and produces expert knowledge in a matter of seconds, as opposed to a laborious procedure.

North America Holds the Largest Market Share

North America is dominating global AI in agriculture market due to several reasons. The region has a large technology base and is one of the leading regions in the world that adopt modern technologies in various industries including agriculture. As a result, farmers in North America are advocating for the use of artificial intelligence to optimize their farming practices, increase yields, and minimize costs through using machine learning, computer vision, predictive analytics and other forms of AI. The existence of large agritech firms along with startups in the United States and Canada has contributed to a rapid progress and coverage of inventive AI solutions to suit demands by farmers across the continent. In February 2024, Deere & Company launched its AI-powered weed-sensing system, See & Spray Premium, which triggers individual spray nozzles when target weeds are seen by boom-mounted cameras scanning a crop, covering more than 2,100 square feet every second.

In addition, the robust government backing of sustainable farming methods and technological breakthroughs, for instance, subsidies to promote precision farming, is helping farmers buy AI instruments. Furthermore, automation and AI solutions that answer issues of labor scarcity and elevated production expenses are helping economies to grow in this sector. Thus, North America dominates the agricultural AI market with influences that shape the world's activities.

Future Market Scenario (2024 - 2031F)

As AI technologies evolve, their use in agriculture is expected to become more advanced, incorporating features such as real-time data analysis, predictive modeling, and automated decision-making.

The launch of robots and machine tools is expected to drastically change the way farming is done by enhancing efficiency and minimizing reliance on human labor especially in areas that are characterized by acute shortages of workers.

The amalgamation of AI with other advancing technologies such as Internet of Things (IoT), cloud computing, and blockchain will result in the rise of intelligent agricultural systems that avail intelligent and informed choices to farmers.

Key Players Landscape and Outlook

The key players in global AI in agriculture market are a mix of established technology firms, specialized agri-tech companies, and innovative startups, competing to offer advanced AI solutions tailored for the agricultural sector. These players are heavily investing in research and development to create cutting-edge technologies such as machine learning, computer vision, predictive analytics, and robotics that cater to various agricultural needs, including crop management, soil monitoring, pest detection, and yield prediction. For instance, in July 2024, A.A.A Taranis Visual Ltd. introduced Ag Assistant, driven by a generative artificial intelligence model with a deep grasp of agronomy that incorporates data sources from multiple modalities, including text, voice, and images.

The competitive landscape is expected to intensify as new entrants bring innovative solutions to the market, driving further advancements and adoption of AI in agriculture. Key players are focusing on developing scalable cloud-based platforms that integrate AI with IoT devices, providing real-time insights and fostering precision farming practices. As the demand for sustainable and efficient farming solutions continues to grow, the outlook for the AI in agriculture market remains robust, with significant opportunities for players to expand their presence globally and drive technological innovation.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

  • 4.1. Demographics (Age/Cohort Analysis - Baby Boomers and Gen X, Millennials, Gen Z; Gender; Income - Low, Mid and High; Geography; Nationality; etc.)
  • 4.2. Market Awareness and Product Information
  • 4.3. Brand Awareness and Loyalty
  • 4.4. Factors Considered in Purchase Decision
    • 4.4.1. Cost
    • 4.4.2. Return on Investment
    • 4.4.3. Ease of Use and Integration
    • 4.4.4. Scalability and Flexibility
    • 4.4.5. Reliability
    • 4.4.6. Accuracy
    • 4.4.7. Support and Training
    • 4.4.8. Compliance with Regulations
    • 4.4.9. Technology Compatibility
    • 4.4.10. Vendor Reputation and Experience
  • 4.5. Existing or Intended User

5. Global AI in Agriculture Market Outlook, 2017-2031F

  • 5.1. Market Size Analysis & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share Analysis & Forecast
    • 5.2.1. By Technology
      • 5.2.1.1. Machine Learning
      • 5.2.1.2. Computer Vision
      • 5.2.1.3. Predictive Analytics
      • 5.2.1.4. Natural Language Processing (NLP)
      • 5.2.1.5. Robotics and Automation
    • 5.2.2. By Offering
      • 5.2.2.1. Hardware
      • 5.2.2.2. Software
      • 5.2.2.3. Services
    • 5.2.3. By Application
      • 5.2.3.1. Precision Farming
      • 5.2.3.2. Livestock Monitoring
      • 5.2.3.3. Drone Analytics
      • 5.2.3.4. Agricultural Robots
      • 5.2.3.5. Weather Forecasting
      • 5.2.3.6. Others
    • 5.2.4. By Deployment Mode
      • 5.2.4.1. Cloud-based
      • 5.2.4.2. On-premises
    • 5.2.5. By Farm Size
      • 5.2.5.1. Small and Medium Farms
      • 5.2.5.2. Large Farms
    • 5.2.6. By Region
      • 5.2.6.1. North America
      • 5.2.6.2. Europe
      • 5.2.6.3. Asia-Pacific
      • 5.2.6.4. South America
      • 5.2.6.5. Middle East and Africa
    • 5.2.7. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2023)
  • 5.3. Market Map Analysis, 2023
    • 5.3.1. By Technology
    • 5.3.2. By Offering
    • 5.3.3. By Application
    • 5.3.4. By Deployment Mode
    • 5.3.5. By Farm Size
    • 5.3.6. By Region

6. North America AI in Agriculture Market Outlook, 2017-2031F*

  • 6.1. Market Size Analysis & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share Analysis & Forecast
    • 6.2.1. By Technology
      • 6.2.1.1. Machine Learning
      • 6.2.1.2. Computer Vision
      • 6.2.1.3. Predictive Analytics
      • 6.2.1.4. Natural Language Processing (NLP)
      • 6.2.1.5. Robotics and Automation
    • 6.2.2. By Offering
      • 6.2.2.1. Hardware
      • 6.2.2.2. Software
      • 6.2.2.3. Services
    • 6.2.3. By Application
      • 6.2.3.1. Precision Farming
      • 6.2.3.2. Livestock Monitoring
      • 6.2.3.3. Drone Analytics
      • 6.2.3.4. Agricultural Robots
      • 6.2.3.5. Weather Forecasting
      • 6.2.3.6. Others
    • 6.2.4. By Deployment Mode
      • 6.2.4.1. Cloud-based
      • 6.2.4.2. On-premises
    • 6.2.5. By Farm Size
      • 6.2.5.1. Small and Medium Farms
      • 6.2.5.2. Large Farms
    • 6.2.6. By Country Share
      • 6.2.6.1. United States
      • 6.2.6.2. Canada
      • 6.2.6.3. Mexico
  • 6.3. Country Market Assessment
    • 6.3.1. United States AI in Agriculture Market Outlook, 2017-2031F*
      • 6.3.1.1. Market Size Analysis & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share Analysis & Forecast
        • 6.3.1.2.1. By Technology
          • 6.3.1.2.1.1. Machine Learning
          • 6.3.1.2.1.2. Computer Vision
          • 6.3.1.2.1.3. Predictive Analytics
          • 6.3.1.2.1.4. Natural Language Processing (NLP)
          • 6.3.1.2.1.5. Robotics and Automation
        • 6.3.1.2.2. By Offering
          • 6.3.1.2.2.1. Hardware
          • 6.3.1.2.2.2. Software
          • 6.3.1.2.2.3. Services
        • 6.3.1.2.3. By Application
          • 6.3.1.2.3.1. Precision Farming
          • 6.3.1.2.3.2. Livestock Monitoring
          • 6.3.1.2.3.3. Drone Analytics
          • 6.3.1.2.3.4. Agricultural Robots
          • 6.3.1.2.3.5. Weather Forecasting
          • 6.3.1.2.3.6. Others
        • 6.3.1.2.4. By Deployment Mode
          • 6.3.1.2.4.1. Cloud-based
          • 6.3.1.2.4.2. On-premises
        • 6.3.1.2.5. By Farm Size
          • 6.3.1.2.5.1. Small and Medium Farms
          • 6.3.1.2.5.2. Large Farms
    • 6.3.2. Canada
    • 6.3.3. Mexico

All segments will be provided for all regions and countries covered

7. Europe AI in Agriculture Market Outlook, 2017-2031F

  • 7.1. Germany
  • 7.2. France
  • 7.3. Italy
  • 7.4. United Kingdom
  • 7.5. Russia
  • 7.6. Netherlands
  • 7.7. Spain
  • 7.8. Turkey
  • 7.9. Poland

8. Asia-Pacific AI in Agriculture Market Outlook, 2017-2031F

  • 8.1. India
  • 8.2. China
  • 8.3. Japan
  • 8.4. Australia
  • 8.5. Vietnam
  • 8.6. South Korea
  • 8.7. Indonesia
  • 8.8. Philippines

9. South America AI in Agriculture Market Outlook, 2017-2031F

  • 9.1. Brazil
  • 9.2. Argentina

10. Middle East and Africa AI in Agriculture Market Outlook, 2017-2031F

  • 10.1. Saudi Arabia
  • 10.2. UAE
  • 10.3. South Africa

11. Demand Supply Analysis

12. Value Chain Analysis

13. Porter's Five Forces Analysis

14. PESTLE Analysis

15. Macro-economic Indicators

16. Profit Margin Analysis

17. Market Dynamics

  • 17.1. Market Drivers
  • 17.2. Market Challenges

18. Market Trends and Developments

19. Case Studies

20. Competitive Landscape

  • 20.1. Competition Matrix of Top 5 Market Leaders
  • 20.2. Company Ecosystem Analysis (Startup v/s SME v/s Large-scale)
  • 20.3. SWOT Analysis for Top 5 Players
  • 20.4. Key Players Landscape for Top 10 Market Players
    • 20.4.1. Microsoft Corporation
      • 20.4.1.1. Company Details
      • 20.4.1.2. Key Management Personnel
      • 20.4.1.3. Products and Services
      • 20.4.1.4. Financials (As Reported)
      • 20.4.1.5. Key Market Focus and Geographical Presence
      • 20.4.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
    • 20.4.2. Deere & Company
    • 20.4.3. IBM Corporation
    • 20.4.4. Ever.Ag Corporation
    • 20.4.5. Prospera Technologies Ltd.
    • 20.4.6. Raven Industries, Inc.
    • 20.4.7. Tule Technologies Inc.
    • 20.4.8. Trimble Inc.
    • 20.4.9. A.A.A Taranis Visual Ltd.
    • 20.4.10. Gamaya SA

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

21. Strategic Recommendations

22. About Us and Disclaimer

List of Tables

  • Table 1. Pricing Analysis of Products from Key Players
  • Table 2. Competition Matrix of Top 5 Market Leaders
  • Table 3. Mergers & Acquisitions/ Joint Ventures (If Applicable)
  • Table 4. About Us - Regions and Countries Where We Have Executed Client Projects

List of Figures

  • Figure 1. Global AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 2. Global AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 3. Global AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 4. Global AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 5. Global AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 6. Global AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 7. Global AI in Agriculture Market Share (%), By Region, 2017-2031F
  • Figure 8. North America AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 9. North America AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 10. North America AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 11. North America AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 12. North America AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 13. North America AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 14. North America AI in Agriculture Market Share (%), By Country, 2017-2031F
  • Figure 15. United States AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 16. United States AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 17. United States AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 18. United States AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 19. United States AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 20. United States AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 21. Canada AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 22. Canada AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 23. Canada AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 24. Canada AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 25. Canada AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 26. Canada AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 27. Mexico AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 28. Mexico AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 29. Mexico AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 30. Mexico AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 31. Mexico AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 32. Mexico AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 33. Europe AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 34. Europe AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 35. Europe AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 36. Europe AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 37. Europe AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 38. Europe AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 39. Europe AI in Agriculture Market Share (%), By Country, 2017-2031F
  • Figure 40. Germany AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 41. Germany AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 42. Germany AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 43. Germany AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 44. Germany AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 45. Germany AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 46. France AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 47. France AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 48. France AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 49. France AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 50. France AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 51. France AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 52. Italy AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 53. Italy AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 54. Italy AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 55. Italy AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 56. Italy AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 57. Italy AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 58. United Kingdom AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 59. United Kingdom AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 60. United Kingdom AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 61. United Kingdom AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 62. United Kingdom AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 63. United Kingdom AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 64. Russia AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 65. Russia AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 66. Russia AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 67. Russia AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 68. Russia AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 69. Russia AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 70. Netherlands AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 71. Netherlands AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 72. Netherlands AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 73. Netherlands AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 74. Netherlands AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 75. Netherlands AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 76. Spain AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 77. Spain AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 78. Spain AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 79. Spain AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 80. Spain AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 81. Spain AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 82. Turkey AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 83. Turkey AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 84. Turkey AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 85. Turkey AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 86. Turkey AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 87. Turkey AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 88. Poland AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 89. Poland AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 90. Poland AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 91. Poland AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 92. Poland AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 93. Poland AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 94. South America AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 95. South America AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 96. South America AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 97. South America AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 98. South America AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 99. South America AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 100. South America AI in Agriculture Market Share (%), By Country, 2017-2031F
  • Figure 101. Brazil AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 102. Brazil AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 103. Brazil AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 104. Brazil AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 105. Brazil AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 106. Brazil AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 107. Argentina AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 108. Argentina AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 109. Argentina AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 110. Argentina AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 111. Argentina AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 112. Argentina AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 113. Asia-Pacific AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 114. Asia-Pacific AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 115. Asia-Pacific AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 116. Asia-Pacific AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 117. Asia-Pacific AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 118. Asia-Pacific AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 119. Asia-Pacific AI in Agriculture Market Share (%), By Country, 2017-2031F
  • Figure 120. India AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 121. India AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 122. India AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 123. India AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 124. India AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 125. India AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 126. China AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 127. China AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 128. China AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 129. China AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 130. China AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 131. China AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 132. Japan AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 133. Japan AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 134. Japan AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 135. Japan AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 136. Japan AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 137. Japan AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 138. Australia AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 139. Australia AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 140. Australia AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 141. Australia AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 142. Australia AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 143. Australia AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 144. Vietnam AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 145. Vietnam AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 146. Vietnam AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 147. Vietnam AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 148. Vietnam AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 149. Vietnam AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 150. South Korea AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 151. South Korea AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 152. South Korea AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 153. South Korea AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 154. South Korea AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 155. South Korea AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 156. Indonesia AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 157. Indonesia AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 158. Indonesia AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 159. Indonesia AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 160. Indonesia AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 161. Indonesia AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 162. Philippines AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 163. Philippines AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 164. Philippines AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 165. Philippines AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 166. Philippines AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 167. Philippines AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 168. Middle East & Africa AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 169. Middle East & Africa AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 170. Middle East & Africa AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 171. Middle East & Africa AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 172. Middle East & Africa AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 173. Middle East & Africa AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 174. Middle East & Africa AI in Agriculture Market Share (%), By Country, 2017-2031F
  • Figure 175. Saudi Arabia AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 176. Saudi Arabia AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 177. Saudi Arabia AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 178. Saudi Arabia AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 179. Saudi Arabia AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 180. Saudi Arabia AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 181. UAE AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 182. UAE AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 183. UAE AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 184. UAE AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 185. UAE AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 186. UAE AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 187. South Africa AI in Agriculture Market, By Value, In USD Billion, 2017-2031F
  • Figure 188. South Africa AI in Agriculture Market Share (%), By Technology, 2017-2031F
  • Figure 189. South Africa AI in Agriculture Market Share (%), By Offering, 2017-2031F
  • Figure 190. South Africa AI in Agriculture Market Share (%), By Application, 2017-2031F
  • Figure 191. South Africa AI in Agriculture Market Share (%), By Deployment Mode, 2017-2031F
  • Figure 192. South Africa AI in Agriculture Market Share (%), By Farm Size, 2017-2031F
  • Figure 193. By Technology Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 194. By Offering Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 195. By Application Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 196. By Deployment Mode Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 197. By Farm Size Map-Market Size (USD Billion) & Growth Rate (%), 2023
  • Figure 198. By Region Map-Market Size (USD Billion) & Growth Rate (%), 2023