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市場調查報告書
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1534368

農業人工智慧市場 - 全球規模、佔有率、趨勢分析、機會、預測，2019-2030 年

AI in Agriculture Market - Global Size, Share, Trend Analysis, Opportunity and Forecast, 2019-2030, Segmented By Offerings; By Technology; By Deployment; By Applications; By End User; By Region
出版日期: | 出版商: Blueweave Consulting | 英文 400 Pages | 商品交期: 2-3個工作天內

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簡介目錄

農業人工智慧的全球市場規模以 11.67% 的複合年成長率成長 4.1 倍，到 2030 年將達到 83.4 億美元

全球農業市場人工智慧的主要推動力是透過提高糧食產量、增加政府的支持措施和資金以及農業技術進步的迅速採用來增強糧食安全。

領先的策略諮詢和市場研究公司 BlueWeave Consulting 在最近的一項研究中估計，2023 年全球農業人工智慧市場以金額為準20.3 億美元。 BlueWeave預測，在2024-2030年的預測期內，全球人工智慧農業市場規模將以11.67%的複合年成長率成長，到2030年將達到83.4億美元。全球人工智慧在農業市場的推動力是其在應對氣候變遷和人口成長導致的需求成長等緊迫挑戰方面發揮的日益重要的作用。到 2050 年，世界人口預計將達到 98 億，而耕地有限，人工智慧的整合對於擴大糧食生產至關重要。由物聯網和巨量資料提供支援的人工智慧正在透過增強作物監測、精密農業、預測分析和產量最佳化來改變農業。人工智慧驅動的無人機、機器人和無線感測器等創新技術正在部署用於預測分析、害蟲檢測和土壤監測等任務。微軟的人工智慧播種應用程式等合作以及 Nature Fresh Farms 等公司的舉措說明了人工智慧的變革性影響，可以提高效率和作物產量預測。廣泛採用不僅會提高工作效率，還會推動對物聯網設備的需求，並鞏固人工智慧在未來幾年在永續農業中的作用。

機會 - 開發垂直農業、水產養殖和牲畜管理的創新人工智慧應用

隨著世界人口的持續成長和對糧食需求的增加，採用高效的耕作方法以在有限的土地上最大限度地提高產量的需求變得越來越重要。人工智慧 (AI) 處於這場農業革命的前沿，它改變了垂直農業、水產養殖和牲畜管理的傳統做法。人工智慧主導的應用正在解決每個領域的獨特挑戰，從監測垂直農業中的作物健康和自動化飼餵系統，到監測水產養殖中的水質和魚類健康，再到牲畜管理中的精準飼餵和健康監測。這些進步不僅提高了營運效率，還促進了永續農業實踐，這對於滿足未來糧食需求同時最大限度地減少環境影響至關重要。 Optima Planta 由 Lennart Sor 於 2017 年創立，其人工智慧和生物資訊學主導的垂直農業方法體現了這一趨勢。該公司位於烏普薩拉的研發機構正在開拓人工智慧技術，以在受控環境農業 (CEA) 中實現顯著的效率提升，預計效率提高高達 100%。 Optima Planta 的 ADA（農業數據助手）系統使用 pH、濕度和溫度感測器來最佳化環境條件，在受控參數下將產量提高 25% 至 50%。 Optima Planta 尋求合作夥伴和投資來擴展該技術，與瑞典大學的合作推動了持續創新，並凸顯了人工智慧在現代農業實踐中的變革潛力。

北美處於農業人工智慧引進的前沿

北美地區擁有美國、加拿大等技術先進國家，是全球農業人工智慧市場的重點地區。在預測期內，由於自動化投資的增加、物聯網的採用以及政府對國內人工智慧發展的支援措施的增加，該地區預計將保持主導地位。農業科技公司正積極探索人工智慧解決方案，部署無人機、機器人、智慧監控系統。

地緣政治緊張局勢升級對全球農業人工智慧市場的影響

不斷升級的地緣政治緊張局勢可能會對全球農業人工智慧市場產生多方面的影響。國家之間的衝突會擾亂供應鏈，阻礙國際合作，增加監管不確定性，並導致市場波動。局勢不穩定的國家可能會將國內糧食安全置於技術進口之上，改變市場動態和成長軌跡。此外，全球不確定性的增加可能會削弱投資者的信心，從而限制農業人工智慧創新的資金籌措。隨著地緣政治緊張局勢的持續，戰略夥伴關係和法律規範在引領全球農業人工智慧應用不斷變化的格局方面發揮關鍵作用。

競爭格局

全球農業人工智慧市場高度分散，許多企業進入該市場。主導全球農業人工智慧市場的主要公司有微軟公司、IBM公司、Granular Inc、Prospera Technologies Ltd、Gamaya SA、ec2ce、PrecisionHawk Inc、Cainthus Corp、Tule Technologies Inc、Deere & Company、AgEagle Aerial Systems Inc.等。每家公司採用​​的主要行銷策略包括設施擴張、產品多元化、聯盟、合作、夥伴關係和收購，以擴大客戶範圍並獲得跨市場的競爭優勢。

該報告的詳細分析提供了有關全球農業人工智慧市場的成長潛力、未來趨勢和統計資訊。它還涵蓋了推動市場總規模預測的因素。該報告致力於提供業界考察和全球農業人工智慧市場的最新技術趨勢，幫助決策者做出明智的策略決策。此外，我們也分析了市場的成長動力、挑戰和競爭力。

目錄

第1章 研究框架

第 2 章執行摘要

第 3 章：全球農業人工智慧市場洞察

  • 產業價值鏈分析
  • DROC分析
    • 生長促進因子
      • 糧食生產需求增加
      • 政府措施和資金
      • 技術進步
    • 抑制因素
      • 初期投資額高
      • 技術專長有限
      • 資料隱私和安全問題
    • 機會
      • 拓展新興市場
      • 開發垂直農業、水產養殖和牲畜管理的新人工智慧應用。
      • 改善供應鏈管理
    • 任務
      • 與現有系統整合
      • 監管和道德問題
    • 科技進步/最新趨勢
  • 法律規範
  • 波特五力分析

第4章 全球農業人工智慧市場：行銷策略

第5章：全球農業人工智慧市場：價格分析

第6章全球農業人工智慧市場：區域分析

  • 全球農業人工智慧市場，區域分析，2023 年
  • 全球農業人工智慧市場，市場吸引力分析，2024-2030

第7章 全球農業AI市場概況

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按報價
      • 硬體
      • 軟體
      • 人工智慧服務（AIaaS）
      • 服務
    • 依技術
      • 機器學習
      • 電腦視覺
      • 預測分析
      • 自然語言處理（NLP）
    • 按發展
      • 雲
      • 本地
      • 混合
    • 按用途
      • 精密農業
      • 牲畜監測
      • 無人機分析
      • 農業機器人
      • 勞動管理
      • 作物管理
      • 灌溉管理
      • 其他
    • 按最終用戶
      • 農民/耕種者
      • 農業合作社
      • 食品加工公司
      • 其他
    • 按地區
      • 北美洲
      • 歐洲
      • 亞太地區 (APAC)
      • 拉丁美洲 (LATAM)
      • 中東和非洲（中東/非洲）

第8章 北美農業人工智慧市場

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按報價
    • 依技術
    • 按發展
    • 按用途
    • 按最終用戶
    • 按國家/地區
      • 美國
      • 加拿大

第9章歐洲農業的人工智慧市場

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按報價
    • 依技術
    • 按發展
    • 按用途
    • 按最終用戶
    • 按國家/地區
      • 德國
      • 英國
      • 義大利
      • 法國
      • 西班牙
      • 比利時
      • 俄羅斯
      • 荷蘭
      • 其他歐洲國家

第10章 亞太地區農業人工智慧市場

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按報價
    • 依技術
    • 按發展
    • 按用途
    • 按最終用戶
    • 按國家/地區
      • 中國
      • 印度
      • 日本
      • 韓國
      • 澳洲和紐西蘭
      • 印尼
      • 馬來西亞
      • 新加坡
      • 越南
      • 亞太地區其他國家

第11章拉丁美洲農業人工智慧市場

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按國家/地區
      • 巴西
      • 墨西哥
      • 阿根廷
      • 秘魯
      • 其他拉丁美洲

第12章 中東和非洲農業人工智慧市場

  • 2019-2030年市場規模及預測
    • 按金額
  • 市場佔有率及預測
    • 按報價
    • 依技術
    • 按發展
    • 按用途
    • 按最終用戶
    • 按國家/地區
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 科威特
      • 南非
      • 奈及利亞
      • 阿爾及利亞
      • 中東和非洲其他地區

第13章競爭格局

  • 主要企業名單及其應用
  • 2023年全球農業AI企業市場佔有率分析
  • 透過管理參數進行競爭基準化分析
  • 重大策略發展（合併、收購、聯盟等）

第14章 地緣政治緊張局勢加劇對全球農業人工智慧市場的影響

第15章 公司簡介（公司簡介、財務矩陣、競爭格局、關鍵人員、主要競爭對手、聯絡方式、策略展望、SWOT分析）

  • Microsoft Corporation
  • IBM Corporation
  • Granular Inc.
  • Prospera Technologies Ltd
  • Gamaya SA
  • ec2ce
  • PrecisionHawk Inc.
  • Cainthus Corp.
  • Tule Technologies Inc.
  • Deere &Company
  • AgEagle Aerial Systems Inc
  • 其他主要企業

第16章 主要策略建議

第17章調查方法

簡介目錄
Product Code: BWC19397

Global AI in Agriculture Market Size Exploding 4.1X at Accelerating CAGR of 11.67% to Touch Whopping USD 8.34 Billion by 2030

Global AI in Agriculture Market is booming primarily due to a heightened focus on strengthening food security by enhancing food production, governments' increasingly supportive initiatives and funding, and rapid adoption of technological advancements in agriculture.

BlueWeave Consulting, a leading strategic consulting and market research firm, in its recent study, estimated Global AI in Agriculture Market size by value at USD 2.03 billion in 2023. During the forecast period between 2024 and 2030, BlueWeave expects Global AI in Agriculture Market size to expand at a CAGR of 11.67% reaching a value of USD 8.34 billion by 2030. The AI in Global Agriculture Market is propelled by its increasing role in addressing pressing challenges like climate change and the rising demand driven by population growth. With the global population projected to reach 9.8 billion by 2050 and with the limited arable land, AI integration becomes essential for scaling food production. AI, supported by IoT and big data, is transforming agriculture through enhanced crop monitoring, precision farming, predictive analytics, and yield optimization. Innovations like AI-powered drones, robots, and wireless sensors are deployed for tasks, such as predictive analysis, pest detection, and soil monitoring. Collaborations such as Microsoft's AI Sowing App and initiatives by companies like Nature Fresh Farms exemplify AI's transformative impact, improving efficiency and predicting harvest yields. The widespread adoption not only enhances operational efficiency but also drives demand for IoT devices, solidifying AI's role in sustainable agriculture in the coming years.

Opportunity - Development of innovative AI applications for vertical farming, aquaculture, and livestock management

As the world population continues to grow and food demand escalates, the need for efficient farming methods becomes increasingly critical to maximize production on limited land. Artificial Intelligence (AI) is at the forefront of this agricultural revolution, transforming traditional practices across vertical farming, aquaculture, and livestock management. AI-driven applications are tailored to each sector's unique challenges, from monitoring crop health and automating feeding systems in vertical farms, to overseeing water quality and fish health in aquaculture, and implementing precision feeding and health monitoring in livestock management. These advancements not only enhance operational efficiency but also promote sustainable farming practices, crucial for meeting future food demands while minimizing environmental impact. Optima Planta, founded in 2017 by Lennart Sor, exemplifies this trend with their AI and bio-informatics-driven approach to vertical farming. Based in Uppsala, their research and development facility pioneers AI technologies to achieve substantial efficiency gains in Controlled Environment Agriculture (CEA), projecting up to 100% improvement. Optima Planta's ADA (Agriculture Data Assistant) system optimizes environmental conditions with sensors for pH, humidity, and temperature, enhancing yields by 25%-50% under controlled parameters. Collaborations with Swedish universities drive ongoing innovation, underscoring AI's transformative potential in modern farming practices as Optima Planta seeks partnerships and investment to scale their technology.

North America at Forefront in Adopting AI for Agriculture

North America, the home to technologically advanced United States and Canada, is the leading region in Global AI in Agriculture Market. During the forecast period, the region is also going to sustain its leadership position due to increasing investments in automation, adoption of IoT, and governments' increasing supportive measures for domestic AI development. Agricultural technology firms are actively exploring AI solutions, deploying drones, robots, and intelligent monitoring systems.

Impact of Escalating Geopolitical Tensions on Global AI in Agriculture Market

Intensifying geopolitical tensions can have a multifaceted impact on Global AI in Agriculture Market. Conflicts between countries disrupt supply chains, impede international collaborations, and heighten regulatory uncertainties, leading to market volatility. Nations experiencing instability may prioritize domestic food security over technological imports, thereby altering market dynamics and growth trajectories. Moreover, increased global uncertainty may erode investor confidence, thereby restricting funding for AI innovations in agriculture. As geopolitical tensions continue, strategic partnerships and regulatory frameworks assume critical roles in navigating the evolving landscape of AI adoption in agriculture worldwide.

Competitive Landscape

Global AI in Agriculture Market is highly fragmented, with numerous players serving the market. The key players dominating Global AI in Agriculture Market include Microsoft Corporation, IBM Corporation, Granular Inc, Prospera Technologies Ltd, Gamaya SA, ec2ce, PrecisionHawk Inc, Cainthus Corp, Tule Technologies Inc, Deere & Company, and AgEagle Aerial Systems Inc. The key marketing strategies adopted by the players are facility expansion, product diversification, alliances, collaborations, partnerships, and acquisitions to expand their customer reach and gain a competitive edge in the overall market.

The report's in-depth analysis provides information about growth potential, upcoming trends, and Global AI in Agriculture Market statistics. It also highlights the factors driving forecasts of total market size. The report promises to provide recent technology trends in Global AI in Agriculture Market along with industry insights to help decision-makers make sound strategic decisions. Furthermore, the report also analyses the growth drivers, challenges, and competitive dynamics of the market.

Table of Contents

1. Research Framework

  • 1.1. Research Objective
  • 1.2. Product Overview
  • 1.3. Market Segmentation

2. Executive Summary

3. Global AI in Agriculture Market Insights

  • 3.1. Industry Value Chain Analysis
  • 3.2. DROC Analysis
    • 3.2.1. Growth Drivers
      • 3.2.1.1. Growing demand for food production
      • 3.2.1.2. Government initiatives and funding
      • 3.2.1.3. Advancements in technology
    • 3.2.2. Restraints
      • 3.2.2.1. High initial investment
      • 3.2.2.2. Limited technical expertise
      • 3.2.2.3. Data privacy and security concerns
    • 3.2.3. Opportunities
      • 3.2.3.1. Expansion into emerging markets
      • 3.2.3.2. Development of new ai applications for vertical farming, aquaculture, and livestock management.
      • 3.2.3.3. Improved supply chain management
    • 3.2.4. Challenges
      • 3.2.4.1. Integration with existing systems
      • 3.2.4.2. Regulatory and ethical issues
    • 3.2.5. Technological Advancements/Recent Developments
  • 3.3. Regulatory Framework
  • 3.4. Porter's Five Forces Analysis
    • 3.4.1. Bargaining Power of Suppliers
    • 3.4.2. Bargaining Power of Buyers
    • 3.4.3. Threat of New Entrants
    • 3.4.4. Threat of Substitutes
    • 3.4.5. Intensity of Rivalry

4. Global AI in Agriculture Market: Marketing Strategies

5. Global AI in Agriculture Market: Pricing Analysis

6. Global AI in Agriculture Market: Geography Analysis

  • 6.1. Global AI in Agriculture Market, Geographical Analysis, 2023
  • 6.2. Global AI in Agriculture, Market Attractiveness Analysis, 2024-2030

7. Global AI in Agriculture Market Overview

  • 7.1. Market Size & Forecast, 2019-2030
    • 7.1.1. By Value (USD Billion)
  • 7.2. Market Share and Forecast
    • 7.2.1. By Offerings
      • 7.2.1.1. Hardware
      • 7.2.1.2. Software
      • 7.2.1.3. AI-as-a-Service (AIaaS)
      • 7.2.1.4. Service
    • 7.2.2. By Technology
      • 7.2.2.1. Machine Learning
      • 7.2.2.2. Computer Vision
      • 7.2.2.3. Predictive Analytics
      • 7.2.2.4. Natural Language Processing (NLP)
    • 7.2.3. By Deployment
      • 7.2.3.1. Cloud
      • 7.2.3.2. On-Premises
      • 7.2.3.3. Hybrid
    • 7.2.4. By Applications
      • 7.2.4.1. Precision Farming
      • 7.2.4.2. Livestock Monitoring
      • 7.2.4.3. Drone Analytics
      • 7.2.4.4. Agriculture Robots
      • 7.2.4.5. Labor Management
      • 7.2.4.6. Crop Management
      • 7.2.4.7. Irrigation Management
      • 7.2.4.8. Others
    • 7.2.5. By End User
      • 7.2.5.1. Farmers/Growers
      • 7.2.5.2. Agriculture Cooperatives
      • 7.2.5.3. Food Processing Companies
      • 7.2.5.4. Others
    • 7.2.6. By Region
      • 7.2.6.1. North America
      • 7.2.6.2. Europe
      • 7.2.6.3. Asia Pacific (APAC)
      • 7.2.6.4. Latin America (LATAM)
      • 7.2.6.5. Middle East and Africa (MEA)

8. North America AI in Agriculture Market

  • 8.1. Market Size & Forecast, 2019-2030
    • 8.1.1. By Value (USD Billion)
  • 8.2. Market Share & Forecast
    • 8.2.1. By Offerings
    • 8.2.2. By Technology
    • 8.2.3. By Deployment
    • 8.2.4. By Applications
    • 8.2.5. By End User
    • 8.2.6. By Country
      • 8.2.6.1. United States
      • 8.2.6.1.1. By Offerings
      • 8.2.6.1.2. By Technology
      • 8.2.6.1.3. By Deployment
      • 8.2.6.1.4. By Applications
      • 8.2.6.1.5. By End User
      • 8.2.6.2. Canada
      • 8.2.6.2.1. By Offerings
      • 8.2.6.2.2. By Technology
      • 8.2.6.2.3. By Deployment
      • 8.2.6.2.4. By Applications
      • 8.2.6.2.5. By End User

9. Europe AI in Agriculture Market

  • 9.1. Market Size & Forecast, 2019-2030
    • 9.1.1. By Value (USD Billion)
  • 9.2. Market Share & Forecast
    • 9.2.1. By Offerings
    • 9.2.2. By Technology
    • 9.2.3. By Deployment
    • 9.2.4. By Applications
    • 9.2.5. By End User
    • 9.2.6. By Country
      • 9.2.6.1. Germany
      • 9.2.6.1.1. By Offerings
      • 9.2.6.1.2. By Technology
      • 9.2.6.1.3. By Deployment
      • 9.2.6.1.4. By Applications
      • 9.2.6.1.5. By End User
      • 9.2.6.2. United Kingdom
      • 9.2.6.2.1. By Offerings
      • 9.2.6.2.2. By Technology
      • 9.2.6.2.3. By Deployment
      • 9.2.6.2.4. By Applications
      • 9.2.6.2.5. By End User
      • 9.2.6.3. Italy
      • 9.2.6.3.1. By Offerings
      • 9.2.6.3.2. By Technology
      • 9.2.6.3.3. By Deployment
      • 9.2.6.3.4. By Applications
      • 9.2.6.3.5. By End User
      • 9.2.6.4. France
      • 9.2.6.4.1. By Offerings
      • 9.2.6.4.2. By Technology
      • 9.2.6.4.3. By Deployment
      • 9.2.6.4.4. By Applications
      • 9.2.6.4.5. By End User
      • 9.2.6.5. Spain
      • 9.2.6.5.1. By Offerings
      • 9.2.6.5.2. By Technology
      • 9.2.6.5.3. By Deployment
      • 9.2.6.5.4. By Applications
      • 9.2.6.5.5. By End User
      • 9.2.6.6. Belgium
      • 9.2.6.6.1. By Offerings
      • 9.2.6.6.2. By Technology
      • 9.2.6.6.3. By Deployment
      • 9.2.6.6.4. By Applications
      • 9.2.6.6.5. By End User
      • 9.2.6.7. Russia
      • 9.2.6.7.1. By Offerings
      • 9.2.6.7.2. By Technology
      • 9.2.6.7.3. By Deployment
      • 9.2.6.7.4. By Applications
      • 9.2.6.7.5. By End User
      • 9.2.6.8. The Netherlands
      • 9.2.6.8.1. By Offerings
      • 9.2.6.8.2. By Technology
      • 9.2.6.8.3. By Deployment
      • 9.2.6.8.4. By Applications
      • 9.2.6.8.5. By End User
      • 9.2.6.9. Rest of Europe
      • 9.2.6.9.1. By Offerings
      • 9.2.6.9.2. By Technology
      • 9.2.6.9.3. By Deployment
      • 9.2.6.9.4. By Applications
      • 9.2.6.9.5. By End User

10. Asia Pacific AI in Agriculture Market

  • 10.1. Market Size & Forecast, 2019-2030
    • 10.1.1. By Value (USD Billion)
  • 10.2. Market Share & Forecast
    • 10.2.1. By Offerings
    • 10.2.2. By Technology
    • 10.2.3. By Deployment
    • 10.2.4. By Applications
    • 10.2.5. By End User
    • 10.2.6. By Country
      • 10.2.6.1. China
      • 10.2.6.1.1. By Offerings
      • 10.2.6.1.2. By Technology
      • 10.2.6.1.3. By Deployment
      • 10.2.6.1.4. By Applications
      • 10.2.6.1.5. By End User
      • 10.2.6.2. India
      • 10.2.6.2.1. By Offerings
      • 10.2.6.2.2. By Technology
      • 10.2.6.2.3. By Deployment
      • 10.2.6.2.4. By Applications
      • 10.2.6.2.5. By End User
      • 10.2.6.3. Japan
      • 10.2.6.3.1. By Offerings
      • 10.2.6.3.2. By Technology
      • 10.2.6.3.3. By Deployment
      • 10.2.6.3.4. By Applications
      • 10.2.6.3.5. By End User
      • 10.2.6.4. South Korea
      • 10.2.6.4.1. By Offerings
      • 10.2.6.4.2. By Technology
      • 10.2.6.4.3. By Deployment
      • 10.2.6.4.4. By Applications
      • 10.2.6.4.5. By End User
      • 10.2.6.5. Australia & New Zealand
      • 10.2.6.5.1. By Offerings
      • 10.2.6.5.2. By Technology
      • 10.2.6.5.3. By Deployment
      • 10.2.6.5.4. By Applications
      • 10.2.6.5.5. By End User
      • 10.2.6.6. Indonesia
      • 10.2.6.6.1. By Offerings
      • 10.2.6.6.2. By Technology
      • 10.2.6.6.3. By Deployment
      • 10.2.6.6.4. By Applications
      • 10.2.6.6.5. By End User
      • 10.2.6.7. Malaysia
      • 10.2.6.7.1. By Offerings
      • 10.2.6.7.2. By Technology
      • 10.2.6.7.3. By Deployment
      • 10.2.6.7.4. By Applications
      • 10.2.6.7.5. By End User
      • 10.2.6.8. Singapore
      • 10.2.6.8.1. By Offerings
      • 10.2.6.8.2. By Technology
      • 10.2.6.8.3. By Deployment
      • 10.2.6.8.4. By Applications
      • 10.2.6.8.5. By End User
      • 10.2.6.9. Vietnam
      • 10.2.6.9.1. By Offerings
      • 10.2.6.9.2. By Technology
      • 10.2.6.9.3. By Deployment
      • 10.2.6.9.4. By Applications
      • 10.2.6.9.5. By End User
      • 10.2.6.10. Rest of APAC
      • 10.2.6.10.1. By Offerings
      • 10.2.6.10.2. By Technology
      • 10.2.6.10.3. By Deployment
      • 10.2.6.10.4. By Applications
      • 10.2.6.10.5. By End User

11. Latin America AI in Agriculture Market

  • 11.1. Market Size & Forecast, 2019-2030
    • 11.1.1. By Value (USD Billion)
  • 11.2. Market Share & Forecast
      • 11.2.1.1. By Offerings
      • 11.2.1.2. By Technology
      • 11.2.1.3. By Deployment
      • 11.2.1.4. By Applications
      • 11.2.1.5. By End User
    • 11.2.2. By Country
      • 11.2.2.1. Brazil
      • 11.2.2.1.1. By Offerings
      • 11.2.2.1.2. By Technology
      • 11.2.2.1.3. By Deployment
      • 11.2.2.1.4. By Applications
      • 11.2.2.1.5. By End User
      • 11.2.2.2. Mexico
      • 11.2.2.2.1. By Offerings
      • 11.2.2.2.2. By Technology
      • 11.2.2.2.3. By Deployment
      • 11.2.2.2.4. By Applications
      • 11.2.2.2.5. By End User
      • 11.2.2.3. Argentina
      • 11.2.2.3.1. By Offerings
      • 11.2.2.3.2. By Technology
      • 11.2.2.3.3. By Deployment
      • 11.2.2.3.4. By Applications
      • 11.2.2.3.5. By End User
      • 11.2.2.4. Peru
      • 11.2.2.4.1. By Offerings
      • 11.2.2.4.2. By Technology
      • 11.2.2.4.3. By Deployment
      • 11.2.2.4.4. By Applications
      • 11.2.2.4.5. By End User
      • 11.2.2.5. Rest of LATAM
      • 11.2.2.5.1. By Offerings
      • 11.2.2.5.2. By Technology
      • 11.2.2.5.3. By Deployment
      • 11.2.2.5.4. By Applications
      • 11.2.2.5.5. By End User

12. Middle East & Africa AI in Agriculture Market

  • 12.1. Market Size & Forecast, 2019-2030
    • 12.1.1. By Value (USD Billion)
  • 12.2. Market Share & Forecast
    • 12.2.1. By Offerings
    • 12.2.2. By Technology
    • 12.2.3. By Deployment
    • 12.2.4. By Applications
    • 12.2.5. By End User
    • 12.2.6. By Country
      • 12.2.6.1. Saudi Arabia
      • 12.2.6.1.1. By Offerings
      • 12.2.6.1.2. By Technology
      • 12.2.6.1.3. By Deployment
      • 12.2.6.1.4. By Applications
      • 12.2.6.1.5. By End User
      • 12.2.6.2. UAE
      • 12.2.6.2.1. By Offerings
      • 12.2.6.2.2. By Technology
      • 12.2.6.2.3. By Deployment
      • 12.2.6.2.4. By Applications
      • 12.2.6.2.5. By End User
      • 12.2.6.3. Qatar
      • 12.2.6.3.1. By Offerings
      • 12.2.6.3.2. By Technology
      • 12.2.6.3.3. By Deployment
      • 12.2.6.3.4. By Applications
      • 12.2.6.3.5. By End User
      • 12.2.6.4. Kuwait
      • 12.2.6.4.1. By Offerings
      • 12.2.6.4.2. By Technology
      • 12.2.6.4.3. By Deployment
      • 12.2.6.4.4. By Applications
      • 12.2.6.4.5. By End User
      • 12.2.6.5. South Africa
      • 12.2.6.5.1. By Offerings
      • 12.2.6.5.2. By Technology
      • 12.2.6.5.3. By Deployment
      • 12.2.6.5.4. By Applications
      • 12.2.6.5.5. By End User
      • 12.2.6.6. Nigeria
      • 12.2.6.6.1. By Offerings
      • 12.2.6.6.2. By Technology
      • 12.2.6.6.3. By Deployment
      • 12.2.6.6.4. By Applications
      • 12.2.6.6.5. By End User
      • 12.2.6.7. Algeria
      • 12.2.6.7.1. By Offerings
      • 12.2.6.7.2. By Technology
      • 12.2.6.7.3. By Deployment
      • 12.2.6.7.4. By Applications
      • 12.2.6.7.5. By End User
      • 12.2.6.8. Rest of MEA
      • 12.2.6.8.1. By Offerings
      • 12.2.6.8.2. By Technology
      • 12.2.6.8.3. By Deployment
      • 12.2.6.8.4. By Applications
      • 12.2.6.8.5. By End User

13. Competitive Landscape

  • 13.1. List of Key Players and Their Applications
  • 13.2. Global AI in Agriculture Company Market Share Analysis, 2023
  • 13.3. Competitive Benchmarking, By Operating Parameters
  • 13.4. Key Strategic Developments (Mergers, Acquisitions, Partnerships, etc.)

14. Impact of Escalating Geopolitical Tensions on Global AI in Agriculture Market

15. Company Profiles (Company Overview, Financial Matrix, Competitive Landscape, Key Personnel, Key Competitors, Contact Address, Strategic Outlook, and SWOT Analysis)

  • 15.1. Microsoft Corporation
  • 15.2. IBM Corporation
  • 15.3. Granular Inc.
  • 15.4. Prospera Technologies Ltd
  • 15.5. Gamaya SA
  • 15.6. ec2ce
  • 15.7. PrecisionHawk Inc.
  • 15.8. Cainthus Corp.
  • 15.9. Tule Technologies Inc.
  • 15.10. Deere & Company
  • 15.11. AgEagle Aerial Systems Inc
  • 15.12. Other Prominent Players

16. Key Strategic Recommendations

17. Research Methodology

  • 17.1. Qualitative Research
    • 17.1.1. Primary & Secondary Research
  • 17.2. Quantitative Research
  • 17.3. Market Breakdown & Data Triangulation
    • 17.3.1. Secondary Research
    • 17.3.2. Primary Research
  • 17.4. Breakdown of Primary Research Respondents, By Region
  • 17.5. Assumptions & Limitations

*Financial information of non-listed companies can be provided as per availability.

**The segmentation and the companies are subject to modifications based on in-depth secondary research for the final deliverable