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2007783

人工智慧精密農業市場預測至2034年：按組件、技術、應用、最終用戶和區域分類的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球人工智慧精密農業市場規模將達到 29.8 億美元，在預測期內將以 21.8% 的複合年成長率成長，到 2034 年將達到 144.5 億美元。

人工智慧精密農業是指應用人工智慧技術，透過數據驅動的決策來最佳化農業生產實踐。它整合了機器學習、電腦視覺、物聯網感測器和預測分析等技術，即時監測作物生長、土壤狀況、天氣模式和資源利用。這些系統透過精準管理水、肥料和農藥等投入，提高生產力，減少浪費和環境影響。人工智慧精密農業透過提升產量品質、營運效率和永續性，助力現代農業滿足日益成長的全球糧食需求。

人工智慧和資料中心的快速擴張

人工智慧能力和資料中心基礎設施的快速發展正顯著推動市場成長。先進的運算能力能夠即時處理海量農業資料集，包括衛星影像、天氣模式和土壤分析等。基於雲端的人工智慧平台支援擴充性的農場管理解決方案，使農民更容易實施預測分析。這項技術基礎有助於實現自動化、最佳化資源利用、加快決策速度，並最終提高整個現代農業生態系統的作物產量和營運效率。

高昂的實施成本和基礎設施成本

高昂的初始投資和基礎設施成本仍然是市場發展的主要限制因素。實施人工智慧系統需要先進的感測器、無人機、資料儲存解決方案和可靠的通訊基礎設施，這對中小農戶來說可能是一筆不小的開支。此外，維護和升級這些系統需要專業技術知識和持續的資金投入。開發中地區資金籌措困難和農村基礎設施不足進一步限制了人工智慧農業技術的普及應用，並延緩了其整合進程。

先進的氣體再利用及回收技術

新的機會在於將先進的氣體再利用和回收技術整合到精密農業系統中。這些創新技術能夠最佳化溫室氣體管理，尤其是在溫室和垂直農場等可控環境中，從而支持永續農業的發展。人工智慧驅動的監測能夠有效利用和再利用二氧化碳等氣體，在促進作物生長的同時最大限度地減少對環境的影響。這種方法符合全球永續性目標，並為環境友善農業實踐和資源最佳化開闢了新的途徑。

原料短缺

原料短缺對市場構成重大威脅，尤其影響感測器、半導體和電子元件的生產。全球供應鏈中斷可能導致成本增加，並延緩關鍵技術的應用。對稀土元素等關鍵材料的依賴加劇了這些脆弱性。這些挑戰阻礙了技術進步和擴充性，可能限制農業相關人員及時有效地利用人工智慧解決方案的能力。

新冠疫情的影響：

新冠疫情對人工智慧精密農業市場產生了複雜的影響。初期，供應鏈中斷和勞動力短缺減緩了技術應用，但疫情也加速了自動化和數位化農業解決方案的普及。農民們更依賴人工智慧工具進行遠端管理，即使在限制下也能維持生產力。疫情凸顯了建構韌性糧食系統的重要性，刺激了對智慧農業技術的投資，並推動了人工智慧精密農業的長期發展。

在預測期內，收益率預測部分預計將佔據最大的市場佔有率。

預計在預測期內，產量預測領域將佔據最大的市場佔有率，因為它在農業規劃和提高生產力方面發揮著至關重要的作用。人工智慧模型分析歷史數據、天氣狀況和作物健康指標，從而提供準確的產量預測。這些資訊能夠幫助農民就收割、儲存和分銷做出明智的決策。在已開發農業市場和新興農業市場，人們越來越需要最大限度地提高產量，同時最大限度地降低風險和不確定性，這推動了產量預測解決方案的廣泛應用。

預計在預測期內，農業技術公司板塊將呈現最高的複合年成長率。

在預測期內，受數位農業技術創新和投資增加的推動，農業技術公司預計將呈現最高的成長率。這些公司處於人工智慧工具開發的前沿，包括智慧感測器、自主農業機械和高級分析平台。戰略聯盟、創業投資資金和政府支持進一步加速了它們的擴張。它們提供擴充性且經濟高效的解決方案的能力吸引了廣泛的客戶群體，並推動了市場的快速成長。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其強大的技術基礎設施和先進的農業技術普及率。該地區受益於許多大型農業技術公司的存在、活躍的研發活動以及政府推行的有利於智慧農業的政策。該地區的農民率先採用者人工智慧驅動的解決方案，利用數據分析和自動化來提高生產力、降低成本並確保農業生產的永續。

複合年成長率最高的地區：

在預測期內，由於人口成長帶來的壓力以及對糧食安全日益成長的需求，亞太地區預計將呈現最高的複合年成長率。該地區各國政府正積極透過補貼和政策支持來推廣數位農業。通訊基礎設施的快速發展、人們對精密農業益處的認知不斷提高以及農業技術生態系統的擴展，都在加速其普及應用。此外，大規模的農業經濟體也為人工智慧驅動的農業解決方案提供了巨大的成長機會。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 根據客戶要求，我們可以提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章：執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧精密農業市場：按組件分類

  • 硬體
  • 軟體
  • 服務

第6章：全球人工智慧精密農業市場：依技術分類

  • 機器學習
  • 電腦視覺
  • 機器人與自動化
  • 預測分析
  • 無人機和無人飛行器
  • 物聯網感測器

第7章 全球人工智慧精密農業市場：按應用領域分類

  • 作物監測與管理
  • 土壤和養分管理
  • 灌溉管理
  • 病蟲害檢測
  • 收益率預測
  • 農業機械自動化

第8章：全球人工智慧精密農業市場：依最終用戶分類

  • 農民
  • 農業技術公司
  • 研究和學術機構
  • 政府和監管機構

第9章 全球人工智慧精密農業市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第10章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第11章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第12章：公司簡介

  • 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.