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市场调查报告书
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2007783

人工智慧精密农业市场预测至2034年：按组件、技术、应用、最终用户和区域分類的全球分析

AI Precision Agriculture Market Forecasts to 2034- Global Analysis By Component (Hardware, Software and Services), Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球人工智慧精密农业市场规模将达到 29.8 亿美元，在预测期内将以 21.8% 的复合年增长率增长，到 2034 年将达到 144.5 亿美元。

人工智慧精密农业是指应用人工智慧技术，透过数据驱动的决策来优化农业生产实践。它整合了机器学习、电脑视觉、物联网感测器和预测分析等技术，即时监测作物生长、土壤状况、天气模式和资源利用。这些系统透过精准管理水、肥料和农药等投入，提高生产力，减少浪费和环境影响。人工智慧精密农业透过提升产量品质、营运效率和永续性，助力现代农业满足日益增长的全球粮食需求。

人工智慧和资料中心的快速扩张

人工智慧能力和资料中心基础设施的快速发展正显着推动市场成长。先进的运算能力能够即时处理海量农业资料集，包括卫星影像、天气模式和土壤分析等。基于云端的人工智慧平台支援扩充性的农场管理解决方案，使农民更容易实施预测分析。这项技术基础有助于实现自动化、优化资源利用、加快决策速度，并最终提高整个现代农业生态系统的作物产量和营运效率。

高昂的实施成本和基础设施成本

高昂的初始投资和基础设施成本仍然是市场发展的主要限制因素。实施人工智慧系统需要先进的感测器、无人机、资料储存解决方案和可靠的通讯基础设施，这对中小农户来说可能是一笔不小的开支。此外，维护和升级这些系统需要专业技术知识和持续的资金投入。开发中地区资金筹措困难和农村基础设施不足进一步限制了人工智慧农业技术的普及应用，并延缓了其整合进程。

先进的气体再利用及回收技术

新的机会在于将先进的气体再利用和回收技术整合到精密农业系统中。这些创新技术能够优化温室气体管理，尤其是在温室和垂直农场等可控环境中，从而支持永续农业的发展。人工智慧驱动的监测能够有效利用和再利用二氧化碳等气体，在促进作物生长的同时最大限度地减少对环境的影响。这种方法符合全球永续性目标，并为环境友善农业实践和资源优化开闢了新的途径。

原料短缺

原材料短缺对市场构成重大威胁，尤其影响感测器、半导体和电子元件的生产。全球供应链中断可能导致成本增加，并延缓关键技术的应用。对稀土元素等关键材料的依赖加剧了这些脆弱性。这些挑战阻碍了技术进步和扩充性，可能限制农业相关人员及时有效地利用人工智慧解决方案的能力。

新冠疫情的影响：

新冠疫情对人工智慧精密农业市场产生了复杂的影响。初期，供应链中断和劳动力短缺减缓了技术应用，但疫情也加速了自动化和数位化农业解决方案的普及。农民们更依赖人工智慧工具进行远端管理，即使在限制下也能维持生产力。疫情凸显了建构韧性粮食系统的重要性，刺激了对智慧农业技术的投资，并推动了人工智慧精密农业的长期发展。

在预测期内，收益率预测部分预计将占据最大的市场份额。

预计在预测期内，产量预测领域将占据最大的市场份额，因为它在农业规划和提高生产力方面发挥着至关重要的作用。人工智慧模型分析历史数据、天气状况和作物健康指标，从而提供准确的产量预测。这些资讯能够帮助农民就收割、储存和分销做出明智的决策。在已开发农业市场和新兴农业市场，人们越来越需要最大限度地提高产量，同时最大限度地降低风险和不确定性，这推动了产量预测解决方案的广泛应用。

预计在预测期内，农业技术公司板块将呈现最高的复合年增长率。

在预测期内，受数位农业技术创新和投资增加的推动，农业技术公司预计将呈现最高的成长率。这些公司处于人工智慧工具开发的前沿，包括智慧感测器、自主农业机械和高级分析平台。战略联盟、创业投资资金和政府支持进一步加速了它们的扩张。它们提供扩充性且经济高效的解决方案的能力吸引了广泛的客户群体，并推动了市场的快速成长。

市占率最大的地区：

在预测期内，北美预计将占据最大的市场份额，这得益于其强大的技术基础设施和先进的农业技术普及率。该地区受益于许多大型农业技术公司的存在、活跃的研发活动以及政府推行的有利于智慧农业的政策。该地区的农民率先采用者人工智慧驱动的解决方案，利用数据分析和自动化来提高生产力、降低成本并确保农业生产的永续。

复合年增长率最高的地区：

在预测期内，由于人口成长带来的压力以及对粮食安全日益增长的需求，亚太地区预计将呈现最高的复合年增长率。该地区各国政府正积极透过补贴和政策支持来推广数位农业。通讯基础设施的快速发展、人们对精密农业益处的认识不断提高以及农业技术生态系统的扩展，都在加速其普及应用。此外，大规模的农业经济体也为人工智慧驱动的农业解决方案提供了巨大的成长机会。

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  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
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    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章：执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球人工智慧精密农业市场：按组件划分

  • 硬体
  • 软体
  • 服务

第六章：全球人工智慧精密农业市场：依技术划分

  • 机器学习
  • 电脑视觉
  • 机器人与自动化
  • 预测分析
  • 无人机和无人飞行器
  • 物联网感测器

第七章 全球人工智慧精密农业市场：按应用领域划分

  • 作物监测与管理
  • 土壤和养分管理
  • 灌溉管理
  • 病虫害检测
  • 收益率预测
  • 农业机械自动化

第八章：全球人工智慧精密农业市场：依最终用户划分

  • 农民
  • 农业技术公司
  • 研究和学术机构
  • 政府和监管机构

第九章 全球人工智慧精密农业市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十章 战略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十一章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十二章：公司简介

  • Microsoft Corporation
  • IBM Corporation
  • Deere & Company（John Deere）
  • Bayer AG
  • SAP SE
  • Intel Corporation
  • Yara International ASA
  • PrecisionHawk Inc.
  • Prospera Technologies Ltd.
  • Taranis Visual Ltd.
  • Agworld Inc.
  • FarmWise Labs Inc.
  • Granular Inc.
  • AGCO Corporation
  • Trimble Inc.
Product Code: SMRC34655

According to Stratistics MRC, the Global AI Precision Agriculture Market is accounted for $2.98 billion in 2026 and is expected to reach $14.45 billion by 2034 growing at a CAGR of 21.8% during the forecast period. AI Precision Agriculture refers to the application of artificial intelligence technologies to optimize farming practices by enabling data-driven decision-making. It integrates machine learning, computer vision, IoT sensors, and predictive analytics to monitor crop health, soil conditions, weather patterns, and resource usage in real time. These systems enhance productivity by delivering precise inputs such as water, fertilizers, and pesticides, reducing waste and environmental impact. By improving yield quality, operational efficiency, and sustainability, AI precision agriculture supports modern farming in meeting the rising global food demand.

Market Dynamics:

Driver:

Surge in AI and data centers

The rapid expansion of artificial intelligence capabilities and data center infrastructure is significantly driving the market. Advanced computing power enables real-time processing of vast agricultural datasets, including satellite imagery, weather patterns, and soil analytics. Cloud-based AI platforms support scalable farm management solutions, allowing farmers to adopt predictive insights with ease. This technological backbone enhances automation, optimizes resource utilization, and accelerates decision-making, ultimately improving crop productivity and operational efficiency across modern agricultural ecosystems.

Restraint:

High purification and infrastructure costs

High initial investment and infrastructure costs remain a key restraint for the market. Deployment of AI systems requires advanced sensors, drones, data storage solutions, and reliable connectivity, which can be expensive for small and medium-scale farmers. Additionally, maintaining and upgrading these systems demands technical expertise and continuous financial input. Limited access to capital and inadequate rural infrastructure in developing regions further restrict widespread adoption, slowing down the integration of AI-driven agricultural practices.

Opportunity:

Advanced gas recycling and reclamation

Emerging opportunities lie in the integration of advanced gas recycling and reclamation technologies within precision agriculture systems. These innovations can support sustainable farming by optimizing greenhouse gas management, particularly in controlled environments such as greenhouses and vertical farms. AI-driven monitoring enables efficient utilization and recycling of gases like carbon dioxide, enhancing crop growth while minimizing environmental impact. This approach aligns with global sustainability goals and opens new avenues for eco-friendly agricultural practices and resource optimization.

Threat:

Raw material shortages

Raw material shortages pose a significant threat to the market, particularly affecting the production of sensors, semiconductors, and electronic components. Disruptions in global supply chains can lead to increased costs and delayed deployment of essential technologies. Dependence on critical materials such as rare earth elements further intensifies vulnerability. These challenges can hinder technological advancement and scalability, limiting the ability of agricultural stakeholders to fully leverage AI driven solutions in a timely manner.

Covid-19 Impact:

The COVID-19 pandemic had a mixed impact on the AI precision agriculture market. While initial disruptions in supply chains and labor availability slowed technology deployment, the crisis accelerated the adoption of automation and digital farming solutions. Farmers increasingly turned to AI-driven tools to manage operations remotely and ensure productivity amid restrictions. The pandemic highlighted the importance of resilient food systems, encouraging investments in smart agriculture technologies and fostering long-term growth in AI-enabled precision farming.

The yield prediction segment is expected to be the largest during the forecast period

The yield prediction segment is expected to account for the largest market share during the forecast period, due to its critical role in enhancing agricultural planning and productivity. AI-powered models analyze historical data, weather conditions, and crop health indicators to provide accurate yield forecasts. These insights enable farmers to make informed decisions regarding harvesting, storage, and distribution. The growing need to maximize output while minimizing risks and uncertainties is driving the widespread adoption of yield prediction solutions across both developed and emerging agricultural markets.

The agritech companies segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the agritech companies segment is predicted to witness the highest growth rate, due to increasing innovation and investment in digital farming technologies. These companies are at the forefront of developing AI-powered tools, including smart sensors, autonomous machinery, and advanced analytics platforms. Strategic collaborations, venture funding, and government support are further accelerating their expansion. Their ability to offer scalable, cost-effective solutions is attracting a broad customer base, fueling rapid market growth.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to strong technological infrastructure and high adoption of advanced farming practices. The region benefits from the presence of leading agritech firms, robust research and development activities, and favorable government initiatives promoting smart agriculture. Farmers in this region are early adopters of AI-driven solutions, leveraging data analytics and automation to enhance productivity, reduce costs, and ensure sustainable agricultural operations.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to increasing population pressure and the rising need for food security. Governments across the region are actively promoting digital agriculture through subsidies and policy support. Rapid advancements in connectivity, growing awareness of precision farming benefits, and expanding agritech ecosystems are accelerating adoption. Additionally, the presence of large agricultural economies provides significant growth opportunities for AI-driven farming solutions.

Key players in the market

Some of the key players in AI Precision Agriculture Market include Microsoft Corporation, IBM Corporation, Deere & Company (John Deere), Bayer AG, SAP SE, Intel Corporation, Yara International ASA, PrecisionHawk Inc., Prospera Technologies Ltd., Taranis Visual Ltd., Agworld Inc., FarmWise Labs Inc., Granular Inc., AGCO Corporation and Trimble Inc.

Key Developments:

In February 2026, IBM introduced the next-generation autonomous storage portfolio featuring IBM Flash System 5600, 7600, and 9600, powered by agentic AI. The systems automate storage management, improve cyber-resilience, and optimize enterprise data operations, helping organizations manage AI workloads more efficiently. This launch strengthens IBM's hybrid cloud and AI infrastructure ecosystem by reducing manual IT operations and enabling autonomous data storage environments.

In January 2026, IBM partnered with telecom group e& to deploy enterprise-grade agentic AI solutions for governance and regulatory compliance. The collaboration focuses on implementing advanced AI agents capable of automating compliance monitoring, operational decision-making, and enterprise analytics. Announced at the World Economic Forum in Davos, the initiative demonstrates IBM's growing focus on enterprise AI ecosystems.

Components Covered:

  • Hardware
  • Software
  • Services

Technologies Covered:

  • Machine Learning
  • Computer Vision
  • Robotics & Automation
  • Predictive Analytics
  • Drones & UAVs
  • IoT Sensors

Applications Covered:

  • Crop Monitoring & Management
  • Soil & Nutrient Management
  • Irrigation Management
  • Pest & Disease Detection
  • Yield Prediction
  • Farm Equipment Automation

End Users Covered:

  • Farmers
  • Agritech Companies
  • Research & Academic Institutes
  • Government & Regulatory Bodies

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Precision Agriculture Market, By Component

  • 5.1 Hardware
  • 5.2 Software
  • 5.3 Services

6 Global AI Precision Agriculture Market, By Technology

  • 6.1 Machine Learning
  • 6.2 Computer Vision
  • 6.3 Robotics & Automation
  • 6.4 Predictive Analytics
  • 6.5 Drones & UAVs
  • 6.6 IoT Sensors

7 Global AI Precision Agriculture Market, By Application

  • 7.1 Crop Monitoring & Management
  • 7.2 Soil & Nutrient Management
  • 7.3 Irrigation Management
  • 7.4 Pest & Disease Detection
  • 7.5 Yield Prediction
  • 7.6 Farm Equipment Automation

8 Global AI Precision Agriculture Market, By End User

  • 8.1 Farmers
  • 8.2 Agritech Companies
  • 8.3 Research & Academic Institutes
  • 8.4 Government & Regulatory Bodies

9 Global AI Precision Agriculture Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 Microsoft Corporation
  • 12.2 IBM Corporation
  • 12.3 Deere & Company (John Deere)
  • 12.4 Bayer AG
  • 12.5 SAP SE
  • 12.6 Intel Corporation
  • 12.7 Yara International ASA
  • 12.8 PrecisionHawk Inc.
  • 12.9 Prospera Technologies Ltd.
  • 12.10 Taranis Visual Ltd.
  • 12.11 Agworld Inc.
  • 12.12 FarmWise Labs Inc.
  • 12.13 Granular Inc.
  • 12.14 AGCO Corporation
  • 12.15 Trimble Inc.

List of Tables

  • Table 1 Global AI Precision Agriculture Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Precision Agriculture Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI Precision Agriculture Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI Precision Agriculture Market Outlook, By Software (2023-2034) ($MN)
  • Table 5 Global AI Precision Agriculture Market Outlook, By Services (2023-2034) ($MN)
  • Table 6 Global AI Precision Agriculture Market Outlook, By Technology (2023-2034) ($MN)
  • Table 7 Global AI Precision Agriculture Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 8 Global AI Precision Agriculture Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 9 Global AI Precision Agriculture Market Outlook, By Robotics & Automation (2023-2034) ($MN)
  • Table 10 Global AI Precision Agriculture Market Outlook, By Predictive Analytics (2023-2034) ($MN)
  • Table 11 Global AI Precision Agriculture Market Outlook, By Drones & UAVs (2023-2034) ($MN)
  • Table 12 Global AI Precision Agriculture Market Outlook, By IoT Sensors (2023-2034) ($MN)
  • Table 13 Global AI Precision Agriculture Market Outlook, By Application (2023-2034) ($MN)
  • Table 14 Global AI Precision Agriculture Market Outlook, By Crop Monitoring & Management (2023-2034) ($MN)
  • Table 15 Global AI Precision Agriculture Market Outlook, By Soil & Nutrient Management (2023-2034) ($MN)
  • Table 16 Global AI Precision Agriculture Market Outlook, By Irrigation Management (2023-2034) ($MN)
  • Table 17 Global AI Precision Agriculture Market Outlook, By Pest & Disease Detection (2023-2034) ($MN)
  • Table 18 Global AI Precision Agriculture Market Outlook, By Yield Prediction (2023-2034) ($MN)
  • Table 19 Global AI Precision Agriculture Market Outlook, By Farm Equipment Automation (2023-2034) ($MN)
  • Table 20 Global AI Precision Agriculture Market Outlook, By End User (2023-2034) ($MN)
  • Table 21 Global AI Precision Agriculture Market Outlook, By Farmers (2023-2034) ($MN)
  • Table 22 Global AI Precision Agriculture Market Outlook, By Agritech Companies (2023-2034) ($MN)
  • Table 23 Global AI Precision Agriculture Market Outlook, By Research & Academic Institutes (2023-2034) ($MN)
  • Table 24 Global AI Precision Agriculture Market Outlook, By Government & Regulatory Bodies (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.