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農業人工智慧 -精密農業市場預測（至2032年）：按農場規模、組件、技術、應用、最終用戶和地區進行的全球分析

AI in Agriculture - Precision Farming Market Forecasts to 2032 - Global Analysis By Farm Size (Small Farms, Mid-Sized Farms and Large Farms), Component, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧精密農業市場預計在 2025 年達到 59 億美元，到 2032 年將達到 304 億美元，預測期內的複合年成長率為 26.3%。

農業中的人工智慧 -精密農業是指將人工智慧技術融入農業實踐，以提高農業的精準度和管理水平。這涉及使用數據驅動演算法、模式識別和自主系統來分析和處理特定田地的變數。這種方法透過即時處理環境和生物數據來增強農業決策能力。這意味著從傳統的大規模耕作方法轉向精細化、高解析度、因地制宜的耕作方法。

根據NASSCOM預測，到2025年，數據和人工智慧技術將為印度農業部門增加約900億美元的價值。

人工智慧和物聯網技術的進步

人工智慧與物聯網 (IoT) 設備的融合正在徹底改變精密農業，使其能夠在田間層面實現數據主導的決策。在衛星影像、土壤感測器和人工智慧演算法的融合推動下，農民現在可以即時監測作物健康狀況、灌溉需求和病蟲害威脅。在政府和私部門對農業創新投資的支持下，人工智慧在已開發經濟體和新興經濟體的應用都在加速。在全球糧食安全挑戰的推動下，人工智慧賦能的精密農業正成為實現可擴展、永續農業的關鍵。

農民缺乏技術專業知識

人工智慧精密農業的推廣應用受到農民有限的數位素養和技術知識的限制。受代溝和變革阻力的影響，許多農民不願從傳統做法轉向資料密集型模式。由於部分農業地區智慧型手機和網路普及率有限，人工智慧所需的數位基礎設施仍欠缺發展。鑑於這些差距，彌合知識差距對於精密農業解決方案的廣泛應用至關重要。

提高作物產量和效率

人工智慧驅動的精密農業在提高作物產量的同時，最大限度地降低投入成本和環境影響，帶來了巨大的機會。即時數據分析和自適應學習模型使農民能夠以前所未有的精度調整施肥、灌溉和農藥施用。在雲端基礎儀錶板和農場管理軟體的推動下，即使是小農戶也開始受益於人工智慧的最佳化潛力。在精準演算法的指導下，田間決策的精細調整，產量成長正變得可衡量且可複製。

農業系統可能遭受網路攻擊

透過人工智慧和物聯網技術實現農業數位化，使農業系統面臨網路安全漏洞。智慧型設備和雲端平台的互聯互通使駭客能夠利用漏洞破壞業務或操縱資料。自動化機械和自主無人機的日益普及也引發了越來越多的威脅，如果系統遭到入侵，可能會造成更大的田間損害和經濟損失。這些風險促使相關人員將強大的網路防禦機制納入其精密農業策略。

COVID-19的影響：

新冠疫情再形成了全球農業格局。在勞動力短缺和供應鏈中斷的背景下，人工智慧主導的精密農業正日益受到青睞。受出行限制和勞動力減少的推動，農民擴大轉向自動化和遠端監控工具。為了確保糧食生產不間斷，人工智慧平台促進了及時介入和投入調整。在危機期間提供的彈性人工智慧工具的推動下，後疫情時代精密農業系統的整合度正在提高。

預計小型農場市場在預測期內將佔最大佔有率

由於不斷加強促進小農戶數位包容性，預計小農農業領域將在預測期內佔據最大市場佔有率。人工智慧技術為小農戶提供了經濟高效的解決方案，從而提高了產量和效率。行動應用程式和感測器等可擴展人工智慧工具的價格實惠，正在推動其應用。政府對小農戶的補貼增強了其獲得精密農業技術的機會。小規模農業對永續實踐的需求將推動市場成長。這些解決方案透過提高生產力，使小農戶能夠與大規模經營競爭。

預計硬體領域在預測期內將實現最高複合年成長率

預計硬體領域將在預測期內實現最高成長率，這得益於精密農業對感測器、無人機和自動化設備日益成長的需求。先進的硬體能夠精確監測土壤、天氣和作物狀況，從而提高農業產量。現代農業硬體的經濟性和擴充性正在推動市場擴張。耐用節能設備的技術進步將推動其普及。硬體與人工智慧軟體的融合將增強精密農業的能力。對智慧農業設備的投資不斷增加將支持該領域的快速成長。

佔比最大的地區：

在預測期內，亞太地區預計將佔據最大的市場佔有率，這得益於其對農業的高度依賴以及政府對智慧農業技術的支持力度不斷增加。中國和印度等國家正大力投資人工智慧和物聯網，以提高糧食產量。印度「數位農業計畫」等政府舉措正在推動人工智慧的應用。無人機和感測器在農業領域的日益普及，正在鞏固該地區的市場地位。都市化和不斷成長的糧食需求將進一步推動亞太地區市場的成長。

複合年成長率最高的地區：

由於農業創新水平高且先進農業設備的廣泛應用，預計北美地區在預測期內的複合年成長率最高。美國在人工智慧主導的農業解決方案和研究方面投入巨資，處於領先地位。精密農業對最佳化產量和降低成本的需求將推動成長。政府支持永續農業的政策將推動市場擴張。先進硬體和軟體解決方案的採用將推動北美市場的快速成長。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球人工智慧精密農業市場（依農場規模）

  • 小型農場
  • 中型農場
  • 大型農場

6. 全球農業人工智慧-精密農業市場（按組成部分）

  • 硬體
  • 軟體
  • 人工智慧服務

7. 全球農業人工智慧-精密農業市場（按技術）

  • 機器學習和深度學習
  • 預測分析
  • 電腦視覺

8. 全球農業人工智慧-精密農業市場（按應用）

  • 天氣追蹤
  • 精密農業
  • 農業機器人
  • 牲畜監控
  • 勞動力管理
  • 其他用途

9. 全球人工智慧精密農業市場（按最終用戶）

  • 農民
  • 農業業務
  • 農業研究所
  • 政府機構
  • 農業技術公司

10. 全球農業人工智慧-精密農業市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章 公司概況

  • Deere & Company
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • The Climate Corporation
  • Farmers Edge Inc.
  • Granular Inc.
  • AgEagle Aerial Systems Inc.
  • Descartes Labs, Inc.
  • Raven Industries Inc.
  • AGCO Corporation
  • Gamaya SA
  • Bayer AG
  • Trimble Inc.
  • Topcon Positioning Systems, Inc.
  • Taranis
  • CropX Technologies
  • PrecisionHawk Inc.
  • Prospera Technologies Ltd.
  • OneSoil
Product Code: SMRC30106

According to Stratistics MRC, the Global AI in Agriculture - Precision Farming Market is accounted for $5.9 billion in 2025 and is expected to reach $30.4 billion by 2032 growing at a CAGR of 26.3% during the forecast period. AI in Agriculture - Precision Farming refers to the integration of artificial intelligence technologies into farming practices to improve agricultural accuracy and control. It involves the use of data-driven algorithms, pattern recognition, and autonomous systems to analyze and act upon field-specific variables. This approach enhances decision-making in farming operations by enabling the real-time processing of environmental and biological data. It represents a shift from traditional broad-scale agricultural practices to fine-tuned, high-resolution, and site-specific farming techniques.

According to NASSCOM, by 2025, approximately USD 90 billion of value will be added to the agriculture sector through data and AI technologies in India.

Market Dynamics:

Driver:

Advancements in AI and IoT technologies

The convergence of artificial intelligence with Internet of Things (IoT) devices is revolutionizing precision farming by enabling data-driven decision-making at the field level. Spurred by the integration of satellite imagery, soil sensors, and AI algorithms, farmers can now monitor crop health, irrigation needs, and pest threats in real-time. Backed by government and private sector investments in agri-tech innovation, AI adoption is accelerating across both developed and emerging economies. Motivated by the global food security challenge, AI-enabled precision farming is becoming essential for scalable and sustainable agriculture.

Restraint:

Lack of technological expertise among farmers

The adoption of AI-based precision agriculture is constrained by the limited digital literacy and technical know-how among a significant portion of the farming community. Driven by generational gaps and resistance to change, many farmers are hesitant to shift from traditional practices to data-intensive models. Backed by insufficient smartphone and internet penetration in certain agricultural zones, the digital infrastructure required for AI functionality remains underdeveloped. Fueled by these gaps, addressing the knowledge divide is crucial for widespread adoption of precision agriculture solutions.

Opportunity:

Increased crop yield and efficiency

AI-powered precision farming unlocks significant opportunities for enhancing crop productivity while minimizing input costs and environmental impact. Spurred by real-time data analytics and adaptive learning models, farmers can tailor fertilization, irrigation, and pesticide application with unprecedented precision. Fueled by cloud-based dashboards and farm management software, even smallholders are beginning to benefit from AI's optimization potential. Guided by precision algorithms that fine-tune decisions at the plot level, yield improvements are becoming both measurable and repeatable.

Threat:

Potential for cyberattacks on farming systems

The digitalization of agriculture through AI and IoT technologies exposes farming systems to increasing cybersecurity vulnerabilities. Driven by the interconnectivity of smart devices and cloud platforms, hackers can exploit weak points to disrupt operations or manipulate data. Spurred by the rising use of automated machinery and autonomous drones, any system breach could result in significant field-level damage or financial loss. Motivated by these risks, stakeholders must integrate robust cyber-defense mechanisms as part of their precision farming strategies.

Covid-19 Impact:

The COVID-19 pandemic reshaped global agriculture, with AI-driven precision farming gaining traction amid labor shortages and supply chain disruptions. Spurred by mobility restrictions and reduced workforce availability, farmers increasingly turned to automation and remote monitoring tools. Driven by the urgency to ensure uninterrupted food production, AI platforms facilitated timely interventions and input adjustments. Motivated by the resilience AI tools offered during the crisis, the post-COVID era is seeing deeper integration of precision farming systems.

The small farms segment is expected to be the largest during the forecast period

The small farms segment is expected to account for the largest market share during the forecast period, owing to widespread initiatives promoting digital inclusion among smallholder farmers.AI technologies offer cost-effective solutions for small farms, improving yields and efficiency. The affordability of scalable AI tools, such as mobile apps and sensors, supports adoption. Government subsidies for small farmers enhance access to precision farming technologies. The need for sustainable practices in small-scale farming drives market growth. These solutions empower small farms to compete with larger operations through enhanced productivity.

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

Over the forecast period, the hardware segment is predicted to witness the highest growth rate, impelled by rising demand for sensors, drones, and automated equipment in precision agriculture. Advanced hardware enables precise monitoring of soil, weather, and crop conditions, improving farming outcomes. The affordability and scalability of modern farming hardware fuel market expansion. Technological advancements in durable and energy-efficient devices drive adoption. The integration of hardware with AI software enhances precision farming capabilities. Growing investments in smart farming equipment support the segment's rapid growth.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, driven by strong agricultural dependence and rising government support for smart farming technologies. Countries like China and India are investing heavily in AI and IoT to boost food production. Government initiatives, such as India's Digital Agriculture Mission, promote AI adoption. The growing use of drones and sensors in agriculture strengthens the region's market position. Rising urbanization and food demand further fuel market growth in Asia Pacific.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR attributed to high levels of agri-tech innovation and widespread use of advanced farming equipment. The U.S. leads with significant investments in AI-driven farming solutions and research. High demand for precision farming to optimize yields and reduce costs drives growth. Government policies supporting sustainable agriculture accelerate market expansion. The adoption of advanced hardware and software solutions boosts North America's rapid market growth.

Key players in the market

Some of the key players in AI in Agriculture - Precision Farming Market include Deere & Company, IBM Corporation, Microsoft Corporation, Google LLC, The Climate Corporation, Farmers Edge Inc., Granular Inc., AgEagle Aerial Systems Inc., Descartes Labs, Inc., Raven Industries Inc., AGCO Corporation, Gamaya SA, Bayer AG, Trimble Inc., Topcon Positioning Systems, Inc., Taranis, CropX Technologies, PrecisionHawk Inc., Prospera Technologies Ltd., and OneSoil.

Key Developments:

In June 2025, Deere & Company launched an AI-powered precision farming platform integrating satellite imagery and IoT sensors. It provides real-time crop health monitoring, enabling farmers to optimize yields and reduce resource waste through data-driven insights and automated field management.

In May 2025, IBM Corporation introduced Watson AgriSense, an AI-driven solution for predictive analytics. It analyzes soil data to optimize management practices, enhancing yield forecasts and reducing costs through precise resource allocation for sustainable farming operations.

In April 2025, Microsoft Corporation unveiled Azure FarmSync, a cloud-based AI tool for automated irrigation and pest detection. It leverages real-time data to optimize water use and protect crops, improving efficiency and sustainability for precision agriculture.

In February 2025, Trimble Inc. unveiled an AI-based variable-rate seeding system to maximize planting efficiency based on soil conditions.

Farm Sizes Covered:

  • Small Farms
  • Mid-Sized Farms
  • Large Farms

Components Covered:

  • Hardware
  • Software
  • AI-as-a-Service

Technologies Covered:

  • Machine Learning & Deep Learning
  • Predictive Analytics
  • Computer Vision

Applications Covered:

  • Weather Tracking
  • Precision Farming
  • Agriculture Robots
  • Livestock Monitoring
  • Labor Management
  • Other Applications

End Users Covered:

  • Farmers
  • Agribusinesses
  • Agriculture Research Institutes
  • Government Agencies
  • Agritech Companies

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & 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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI in Agriculture - Precision Farming Market, By Farm Size

  • 5.1 Introduction
  • 5.2 Small Farms
  • 5.3 Mid-Sized Farms
  • 5.4 Large Farms

6 Global AI in Agriculture - Precision Farming Market, By Component

  • 6.1 Introduction
  • 6.2 Hardware
  • 6.3 Software
  • 6.4 AI-as-a-Service

7 Global AI in Agriculture - Precision Farming Market, By Technology

  • 7.1 Introduction
  • 7.2 Machine Learning & Deep Learning
  • 7.3 Predictive Analytics
  • 7.4 Computer Vision

8 Global AI in Agriculture - Precision Farming Market, By Application

  • 8.1 Introduction
  • 8.2 Weather Tracking
  • 8.3 Precision Farming
  • 8.4 Agriculture Robots
  • 8.5 Livestock Monitoring
  • 8.6 Labor Management
  • 8.7 Other Applications

9 Global AI in Agriculture - Precision Farming Market, By End User

  • 9.1 Introduction
  • 9.2 Farmers
  • 9.3 Agribusinesses
  • 9.4 Agriculture Research Institutes
  • 9.5 Government Agencies
  • 9.6 Agritech Companies

10 Global AI in Agriculture - Precision Farming Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Deere & Company
  • 12.2 IBM Corporation
  • 12.3 Microsoft Corporation
  • 12.4 Google LLC
  • 12.5 The Climate Corporation
  • 12.6 Farmers Edge Inc.
  • 12.7 Granular Inc.
  • 12.8 AgEagle Aerial Systems Inc.
  • 12.9 Descartes Labs, Inc.
  • 12.10 Raven Industries Inc.
  • 12.11 AGCO Corporation
  • 12.12 Gamaya SA
  • 12.13 Bayer AG
  • 12.14 Trimble Inc.
  • 12.15 Topcon Positioning Systems, Inc.
  • 12.16 Taranis
  • 12.17 CropX Technologies
  • 12.18 PrecisionHawk Inc.
  • 12.19 Prospera Technologies Ltd.
  • 12.20 OneSoil

List of Tables

  • Table 1 Global AI in Agriculture - Precision Farming Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI in Agriculture - Precision Farming Market Outlook, By Farm Size (2024-2032) ($MN)
  • Table 3 Global AI in Agriculture - Precision Farming Market Outlook, By Small Farms (2024-2032) ($MN)
  • Table 4 Global AI in Agriculture - Precision Farming Market Outlook, By Mid-Sized Farms (2024-2032) ($MN)
  • Table 5 Global AI in Agriculture - Precision Farming Market Outlook, By Large Farms (2024-2032) ($MN)
  • Table 6 Global AI in Agriculture - Precision Farming Market Outlook, By Component (2024-2032) ($MN)
  • Table 7 Global AI in Agriculture - Precision Farming Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 8 Global AI in Agriculture - Precision Farming Market Outlook, By Software (2024-2032) ($MN)
  • Table 9 Global AI in Agriculture - Precision Farming Market Outlook, By AI-as-a-Service (2024-2032) ($MN)
  • Table 10 Global AI in Agriculture - Precision Farming Market Outlook, By Technology (2024-2032) ($MN)
  • Table 11 Global AI in Agriculture - Precision Farming Market Outlook, By Machine Learning & Deep Learning (2024-2032) ($MN)
  • Table 12 Global AI in Agriculture - Precision Farming Market Outlook, By Predictive Analytics (2024-2032) ($MN)
  • Table 13 Global AI in Agriculture - Precision Farming Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 14 Global AI in Agriculture - Precision Farming Market Outlook, By Application (2024-2032) ($MN)
  • Table 15 Global AI in Agriculture - Precision Farming Market Outlook, By Weather Tracking (2024-2032) ($MN)
  • Table 16 Global AI in Agriculture - Precision Farming Market Outlook, By Precision Farming (2024-2032) ($MN)
  • Table 17 Global AI in Agriculture - Precision Farming Market Outlook, By Agriculture Robots (2024-2032) ($MN)
  • Table 18 Global AI in Agriculture - Precision Farming Market Outlook, By Livestock Monitoring (2024-2032) ($MN)
  • Table 19 Global AI in Agriculture - Precision Farming Market Outlook, By Labor Management (2024-2032) ($MN)
  • Table 20 Global AI in Agriculture - Precision Farming Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 21 Global AI in Agriculture - Precision Farming Market Outlook, By End User (2024-2032) ($MN)
  • Table 22 Global AI in Agriculture - Precision Farming Market Outlook, By Farmers (2024-2032) ($MN)
  • Table 23 Global AI in Agriculture - Precision Farming Market Outlook, By Agribusinesses (2024-2032) ($MN)
  • Table 24 Global AI in Agriculture - Precision Farming Market Outlook, By Agriculture Research Institutes (2024-2032) ($MN)
  • Table 25 Global AI in Agriculture - Precision Farming Market Outlook, By Government Agencies (2024-2032) ($MN)
  • Table 26 Global AI in Agriculture - Precision Farming Market Outlook, By Agritech Companies (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.