查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1534368

农业人工智慧市场 - 全球规模、份额、趋势分析、机会、预测，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个工作天内

价格
简介目录

农业人工智慧的全球市场规模以 11.67% 的复合年增长率增长 4.1 倍，到 2030 年将达到 83.4 亿美元

全球农业市场人工智慧的主要推动力是透过提高粮食产量、增加政府的支持措施和资金以及农业技术进步的迅速采用来增强粮食安全。

领先的策略咨询和市场研究公司 BlueWeave Consulting 在最近的一项研究中估计，2023 年全球农业人工智慧市场以金额为准20.3 亿美元。 BlueWeave预测，在2024-2030年的预测期内，全球人工智慧农业市场规模将以11.67%的复合年增长率成长，到2030年将达到83.4亿美元。全球人工智慧在农业市场的推动力是其在应对气候变迁和人口成长导致的需求成长等紧迫挑战方面发挥的日益重要的作用。到 2050 年，世界人口预计将达到 98 亿，而耕地有限，人工智慧的整合对于扩大粮食生产至关重要。由物联网和巨量资料提供支援的人工智慧正在透过增强作物监测、精密农业、预测分析和产量优化来改变农业。人工智慧驱动的无人机、机器人和无线感测器等创新技术正在部署用于预测分析、害虫检测和土壤监测等任务。微软的人工智慧播种应用程式等合作以及 Nature Fresh Farms 等公司的倡议说明了人工智慧的变革性影响，可以提高效率和作物产量预测。广泛采用不仅会提高工作效率，还会推动对物联网设备的需求，并巩固人工智慧在未来几年在永续农业中的作用。

机会 - 开发垂直农业、水产养殖和牲畜管理的创新人工智慧应用

随着世界人口的持续增长和对粮食需求的增加，采用高效的耕作方法以在有限的土地上最大限度地提高产量的需求变得越来越重要。人工智慧 (AI) 处于这场农业革命的前沿，它改变了垂直农业、水产养殖和牲畜管理的传统做法。人工智慧主导的应用正在解决每个领域的独特挑战，从监测垂直农业中的作物健康和自动化饲餵系统，到监测水产养殖中的水质和鱼类健康，再到牲畜管理中的精准饲餵和健康监测。这些进步不仅提高了营运效率，还促进了永续农业实践，这对于满足未来粮食需求同时最大限度地减少环境影响至关重要。 Optima Planta 由 Lennart Sor 于 2017 年创立，其人工智慧和生物资讯学主导的垂直农业方法体现了这一趋势。该公司位于乌普萨拉的研发机构正在开拓人工智慧技术，以在受控环境农业 (CEA) 中实现显着的效率提升，预计效率提高高达 100%。 Optima Planta 的 ADA（农业数据助手）系统使用 pH、湿度和温度感测器来优化环境条件，在受控参数下将产量提高 25% 至 50%。 Optima Planta 寻求合作伙伴和投资来扩展该技术，与瑞典大学的合作推动了持续创新，并凸显了人工智慧在现代农业实践中的变革潜力。

北美处于农业人工智慧引进的前沿

北美地区拥有美国、加拿大等技术先进国家，是全球农业人工智慧市场的重点地区。在预测期内，由于自动化投资的增加、物联网的采用以及政府对国内人工智慧发展的支援措施的增加，该地区预计将保持主导地位。农业科技公司正积极探索人工智慧解决方案，部署无人机、机器人、智慧监控系统。

地缘政治紧张局势升级对全球农业人工智慧市场的影响

不断升级的地缘政治紧张局势可能会对全球农业人工智慧市场产生多方面的影响。国家之间的衝突会扰乱供应链，阻碍国际合作，增加监管不确定性，并导致市场波动。局势不稳定的国家可能会将国内粮食安全置于技术进口之上，改变市场动态和成长轨迹。此外，全球不确定性的增加可能会削弱投资者的信心，从而限制农业人工智慧创新的资金筹措。随着地缘政治紧张局势的持续，战略伙伴关係和法律规范在引领全球农业人工智慧应用不断变化的格局方面发挥关键作用。

竞争格局

全球农业人工智慧市场高度分散，许多企业进入该市场。主导全球农业人工智慧市场的主要公司有微软公司、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。每家公司采用​​的主要行销策略包括设施扩张、产品多元化、联盟、合作、伙伴关係和收购，以扩大客户范围并获得跨市场的竞争优势。

该报告的详细分析提供了有关全球农业人工智慧市场的成长潜力、未来趋势和统计资讯。它还涵盖了推动市场总规模预测的因素。该报告致力于提供业界考察和全球农业人工智慧市场的最新技术趋势，帮助决策者做出明智的策略决策。此外，我们也分析了市场的成长动力、挑战和竞争力。

目录

第一章 研究框架

第 2 章执行摘要

第 3 章：全球农业人工智慧市场洞察

  • 产业价值链分析
  • DROC分析
    • 生长促进因子
      • 粮食生产需求增加
      • 政府措施和资金
      • 技术进步
    • 抑制因素
      • 初期投资额高
      • 技术专长有限
      • 资料隐私和安全问题
    • 机会
      • 拓展新兴市场
      • 开发垂直农业、水产养殖和牲畜管理的新人工智慧应用。
      • 改善供应链管理
    • 任务
      • 与现有系统集成
      • 监管和道德问题
    • 科技进步/最新趋势
  • 法律规范
  • 波特五力分析

第四章 全球农业人工智慧市场：行销策略

第五章：全球农业人工智慧市场：价格分析

第六章全球农业人工智慧市场：区域分析

  • 全球农业人工智慧市场，区域分析，2023 年
  • 全球农业人工智慧市场，市场吸引力分析，2024-2030

第七章 全球农业AI市场概况

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按报价
      • 硬体
      • 软体
      • 人工智慧服务（AIaaS）
      • 服务
    • 依技术
      • 机器学习
      • 电脑视觉
      • 预测分析
      • 自然语言处理（NLP）
    • 按发展
      • 云
      • 本地
      • 混合
    • 按用途
      • 精密农业
      • 牲畜监测
      • 无人机分析
      • 农业机器人
      • 劳动管理
      • 作物管理
      • 灌溉管理
      • 其他的
    • 按最终用户
      • 农民/耕种者
      • 农业合作社
      • 食品加工公司
      • 其他的
    • 按地区
      • 北美洲
      • 欧洲
      • 亚太地区 (APAC)
      • 拉丁美洲 (LATAM)
      • 中东和非洲（中东/非洲）

第八章 北美农业人工智慧市场

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按报价
    • 依技术
    • 按发展
    • 按用途
    • 按最终用户
    • 按国家/地区
      • 美国
      • 加拿大

第九章欧洲农业的人工智慧市场

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按报价
    • 依技术
    • 按发展
    • 按用途
    • 按最终用户
    • 按国家/地区
      • 德国
      • 英国
      • 义大利
      • 法国
      • 西班牙
      • 比利时
      • 俄罗斯
      • 荷兰
      • 其他欧洲国家

第十章 亚太地区农业人工智慧市场

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按报价
    • 依技术
    • 按发展
    • 按用途
    • 按最终用户
    • 按国家/地区
      • 中国
      • 印度
      • 日本
      • 韩国
      • 澳洲和纽西兰
      • 印尼
      • 马来西亚
      • 新加坡
      • 越南
      • 亚太地区其他国家

第十一章拉丁美洲农业人工智慧市场

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按国家/地区
      • 巴西
      • 墨西哥
      • 阿根廷
      • 秘鲁
      • 其他拉丁美洲

第十二章 中东和非洲农业人工智慧市场

  • 2019-2030年市场规模及预测
    • 按金额
  • 市场占有率及预测
    • 按报价
    • 依技术
    • 按发展
    • 按用途
    • 按最终用户
    • 按国家/地区
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 科威特
      • 南非
      • 奈及利亚
      • 阿尔及利亚
      • 中东和非洲其他地区

第十三章竞争格局

  • 主要企业名单及其应用
  • 2023年全球农业AI企业市场占有率分析
  • 透过管理参数进行竞争基准化分析
  • 重大策略发展（合併、收购、联盟等）

第十四章 地缘政治紧张局势加剧对全球农业人工智慧市场的影响

第十五章 公司简介（公司简介、财务矩阵、竞争格局、关键人员、主要竞争对手、联络方式、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
  • 其他主要企业

第十六章 主要策略建议

第十七章调查方法

简介目录
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