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精密畜産におけるAIの世界市場 (2025-2032年)

Global Artificial Intelligence (AI) In Precision Livestock Farming Market- 2025-2032

出版日
ページ情報
英文 180 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=143.57円
精密畜産におけるAIの世界市場 (2025-2032年)
出版日: 2025年04月10日
発行: DataM Intelligence
ページ情報: 英文 180 Pages
納期: 即日から翌営業日
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  • 概要
  • 目次
概要

世界の精密畜産におけるAIの市場規模は、2024年の22億3,000万米ドルから、予測期間中はCAGR 15.39%で推移し、2032年には198億7,000万米ドルに達すると予測されています。

精密畜産におけるAIの世界市場は、効率的かつ持続可能な畜産の需要が高まる中で、急速に成長しています。AI技術は、リアルタイムのモニタリング、予測分析、自動化を通じて畜産管理に革新をもたらし、家畜の健康、生産性、資源の最適化を向上させています。

特に大規模農場では、給餌管理、疾病検出、行動監視といった応用が注目を集めています。世界的な肉類・乳製品の消費増加、労働力不足、データ駆動型農業への移行が進む中で、この市場は北米、欧州、そしてアジア太平洋の新興国を中心に大きく拡大すると予測されています。

市場動向

AIを活用したコンピュータビジョンツールは、カメラと連携して動物の行動や健康状態を追跡するために導入されています。アイルランドの企業Cainthusは、顔認識と映像モニタリング技術を活用して牛の行動を評価し、異常を特定し、乳牛の不快感やストレスを検出することで乳量の向上を図っています。

また、クラウドコンピューティングとAIの融合により、複数の場所にまたがる家畜管理が可能になっています。AfimilkのAfiFarmソフトウェアは、センサー、搾乳機、給餌システムなどからのデータを分析する集中管理型プラットフォームを提供し、実用的なインサイトと遠隔での意思決定を支援しています。

市場力学

効率的な家畜モニタリングへの需要の高まり

牛乳、肉、卵などの動物性食品に対する世界的な需要の増加に伴い、酪農家には家畜の健康を維持しながら生産性を最大化することが求められています。AIツールは家畜をリアルタイムで監視し、病気の早期発見、給餌の最適化、タイムリーな繁殖サイクルを可能にします。

例えば、ZenaDrone 1000はリアルタイムのGPS技術で家畜の追跡を簡素化し、広大な場所やアクセスしにくい場所でも正確な位置データを確保します。GPS技術を搭載し、大規模なモニタリングを行うUAVは、このような分野で非常に有利です。ZenadroneのGPSトラッキングは、牧場主に迷子の家畜の正確な座標を提供します。

当レポートでは、世界の精密畜産におけるAIの市場を調査し、市場概要、市場成長への各種影響因子の分析、各種区分・地域/主要国別の詳細分析、主要企業のプロファイルなどをまとめています。

目次

第1章 調査手法・調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
    • 抑制要因
    • 機会
    • 影響分析

第5章 業界分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制およびコンプライアンス分析
  • 持続可能性分析
  • DMIオピニオン

第6章 コンポーネント別

  • ハードウェア
    • センサー
    • スマートカメラ
    • ドローン
    • RFIDタグ&リーダー
    • GPSデバイス
  • ソフトウェア
    • AIアルゴリズム
    • 予測分析
    • 農場管理ソフトウェア
  • サービス

第7章 展開モード別

  • クラウドベース
  • オンプレミス

第8章 家畜タイプ別

  • 牛
  • 家禽
  • 豚
  • 羊・ヤギ
  • その他

第9章 用途別

  • 給餌管理
  • 搾乳およびモニタリング
  • 生殖管理
  • 動物の健康監視と病気検出
  • 家畜の行動と福祉のモニタリング
  • サプライチェーンと農場管理
  • その他

第10章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • スペイン
    • その他
  • 南米
    • ブラジル
    • アルゼンチン
    • その他
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他
  • 中東・アフリカ

第11章 企業プロファイル

  • Connecterra
  • Cainthus
  • Vence
  • DeLaval
  • Afimilk Ltd.
  • BouMatic
  • Allflex Livestock Intelligence（MSD Animal Health）
  • Quantified Ag
  • Cargill, Incorporated
  • GEA Group
  • Moocall

第12章 付録

目次
Product Code: AG9480

Global artificial intelligence (AI) in precision livestock farming market reached US$ 2.23 billion in 2024 and is expected to reach US$ 19.87 billion by 2032, growing with a CAGR of 15.39% during the forecast period 2025-2032.

The global artificial intelligence (AI) in precision livestock farming market is experiencing rapid growth, driven by the increasing demand for efficient and sustainable animal farming practices. AI technologies are revolutionizing livestock management through real-time monitoring, predictive analytics, and automation, enhancing animal health, productivity, and resource optimization.

Applications like feeding management, disease detection, and behavior monitoring are gaining traction, especially in large-scale farms. With rising global meat and dairy consumption, labor shortages, and the push for data-driven farming, the market is projected to expand significantly across North America, Europe, and emerging economies in Asia-Pacific.

Market Trend

AI-based computer vision tools are being integrated with cameras to track animal behavior and well-being. Cainthus, an Irish company, uses facial recognition and visual monitoring to assess cow behavior, identify abnormalities, and improve milk yield by detecting discomfort or stress in dairy cattle.

Cloud computing combined with AI is enabling integrated livestock management across multiple locations. Afimilk's AfiFarm software offers a centralized platform that analyzes data from sensors, milking machines, and feeding systems, enabling actionable insights and remote decision-making.

Dynamics

Rising Demand for Efficient Livestock Monitoring

With the global increase in demand for animal products such as milk, meat, and eggs, there is pressure on farmers to maximize productivity while maintaining animal health. AI tools help monitor livestock in real-time, enabling early disease detection, optimized feeding, and timely reproduction cycles.

For instance, the ZenaDrone 1000 simplifies livestock tracking with real-time GPS technology, ensuring precise location data even in expansive or inaccessible areas. UAVs equipped with GPS technology and large-scale monitoring are highly advantageous in these areas. Zenadrone's GPS tracking provides ranchers with the exact coordinates of lost animals.

High Initial Investment and Maintenance Costs

High initial investment and maintenance costs significantly restrain the adoption of AI in precision livestock farming, particularly among small and medium-scale farmers. The expensive nature of AI-integrated systems-such as automated milking machines, health sensors, and smart monitoring platforms-creates a financial barrier, especially in developing regions.

Additionally, the long payback period and recurring expenses for maintenance, software subscriptions, and data management deter widespread implementation. Limited access to financing options and poor rural infrastructure further add to the challenge, making it difficult for many farmers to justify or sustain the cost of such advanced technologies.

Segment Analysis

The global artificial intelligence (AI) in precision livestock farming market is segmented based on component, deployment mode, livestock type, application and region.

Cloud-Based Solutions Accelerate Adoption of AI in Precision Livestock Farming

The cloud-based deployment mode is a key driver in the AI precision livestock farming market due to its scalability, real-time data access, and lower upfront infrastructure costs. Cloud platforms enable farmers to monitor and manage livestock remotely through smartphones or computers, making operations more efficient and responsive.

For instance, Afimilk's AfiCloud and Connecterra's Ida platform offer cloud-based solutions that collect and analyze data from sensors and wearable devices to deliver actionable insights on animal health, feeding, and reproduction. These systems allow continuous updates, seamless integration with multiple devices, and data storage without the need for expensive local servers.

Additionally, the cloud model supports multi-location farm management, which is increasingly essential for large commercial operations. As internet connectivity improves in rural areas and subscription-based pricing models become more accessible, cloud deployment continues to gain traction, driving digital transformation across the livestock farming industry.

Geographical Penetration

North America Leads AI Adoption in Precision Livestock Farming with Strong Tech Infrastructure and Agri-Tech Investments

North America dominates the AI in precision livestock farming market due to its advanced technological infrastructure, early adoption of smart farming solutions, and significant investments in agri-tech innovation. The US, in particular, is home to major players like Connecterra, Cargill, and Allflex, which are actively deploying AI tools for health monitoring, feeding optimization, and productivity tracking.

For instance, in 2024, Precision Livestock Technologies (PLT), a provider of software and hardware solutions for livestock feeding and health, has recently announced the launch of a new system that integrates artificial intelligence (AI) to forecast cattle feed intake and generate feeding recommendations. This system represents a significant advancement in the use of technology within the livestock industry. High digital literacy and greater access to funding make North America a frontrunner in this evolving market.

Sustainability Analysis

AI in precision livestock farming plays a crucial role in promoting sustainability by enabling resource-efficient, eco-friendly, and welfare-centric agricultural practices. Through real-time monitoring and predictive analytics, farmers can reduce overfeeding, optimize water usage, and minimize waste generation, thereby lowering the environmental footprint.

For example, AI-driven feeding systems ensure precise nutrient delivery, which reduces methane emissions and enhances feed conversion efficiency. Automated health monitoring helps detect diseases early, minimizing the need for antibiotics and veterinary interventions.

Competitive Landscape

The major global players in the market include Connecterra, Cainthus, Vence, DeLaval, Afimilk Ltd, BouMatic, Allflex Livestock Intelligence (MSD Animal Health), Quantified Ag, Cargill, Incorporated, GEA Group, Moocall and among others.

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Target Audience 2024

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Component
  • 3.2. Snippet by Deployment Mode
  • 3.3. Snippet by Livestock Type
  • 3.4. Snippet by Application
  • 3.5. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Rising Demand for Efficient Livestock Monitoring
    • 4.1.2. Restraints
      • 4.1.2.1. High Initial Investment and Maintenance Costs
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory and Compliance Analysis
  • 5.5. Sustainability Analysis
  • 5.6. DMI Opinion

6. By Component

  • 6.1. Introduction
    • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 6.1.2. Market Attractiveness Index, By Component
  • 6.2. Hardware *
    • 6.2.1. Introduction
    • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
    • 6.2.3. Sensors
    • 6.2.4. Smart Cameras
    • 6.2.5. Drones
    • 6.2.6. RFID Tags & Readers
    • 6.2.7. GPS Devices
  • 6.3. Software
    • 6.3.1. AI Algorithms
    • 6.3.2. Predictive Analytics
    • 6.3.3. Farm Management Software
  • 6.4. Services

7. By Deployment Mode

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 7.1.2. Market Attractiveness Index, By Deployment Mode
  • 7.2. Cloud-Based *
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. On-Premise

8. By Livestock Type

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 8.1.2. Market Attractiveness Index, By Livestock Type
  • 8.2. Cattle *
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Poultry
  • 8.4. Swine
  • 8.5. Sheep & Goats
  • 8.6. Others

9. By Application

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 9.1.2. Market Attractiveness Index, By Application
  • 9.2. Feeding Management *
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Milk Harvesting & Monitoring
  • 9.4. Reproduction Management
  • 9.5. Animal Health Monitoring & Disease Detection
  • 9.6. Livestock Behavior & Welfare Monitoring
  • 9.7. Supply Chain & Farm Management
  • 9.8. Others

10. By Region

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 10.1.2. Market Attractiveness Index, By Region
  • 10.2. North America
    • 10.2.1. Introduction
    • 10.2.2. Key Region-Specific Dynamics
    • 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.2.7.1. US
      • 10.2.7.2. Canada
      • 10.2.7.3. Mexico
  • 10.3. Europe
    • 10.3.1. Introduction
    • 10.3.2. Key Region-Specific Dynamics
    • 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.3.7.1. Germany
      • 10.3.7.2. UK
      • 10.3.7.3. France
      • 10.3.7.4. Italy
      • 10.3.7.5. Spain
      • 10.3.7.6. Rest of Europe
  • 10.4. South America
    • 10.4.1. Introduction
    • 10.4.2. Key Region-Specific Dynamics
    • 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.4.7.1. Brazil
      • 10.4.7.2. Argentina
      • 10.4.7.3. Rest of South America
  • 10.5. Asia-Pacific
    • 10.5.1. Introduction
    • 10.5.2. Key Region-Specific Dynamics
    • 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.5.7.1. China
      • 10.5.7.2. India
      • 10.5.7.3. Japan
      • 10.5.7.4. Australia
      • 10.5.7.5. Rest of Asia-Pacific
  • 10.6. Middle East and Africa
    • 10.6.1. Introduction
    • 10.6.2. Key Region-Specific Dynamics
    • 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Livestock Type
    • 10.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application

11. Company Profiles

  • 11.1. Connecterra *
    • 11.1.1. Company Overview
    • 11.1.2. Product Portfolio and Description
    • 11.1.3. Financial Overview
    • 11.1.4. Key Developments
  • 11.2. Cainthus
  • 11.3. Vence
  • 11.4. DeLaval
  • 11.5. Afimilk Ltd.
  • 11.6. BouMatic
  • 11.7. Allflex Livestock Intelligence (MSD Animal Health)
  • 11.8. Quantified Ag
  • 11.9. Cargill, Incorporated
  • 11.10. GEA Group
  • 11.11. Moocall

LIST NOT EXHAUSTIVE

12. Appendix

  • 12.1. About Us and Services
  • 12.2. Contact Us