インテリジェント農業市場の2030年までの予測：農場規模、技術、用途、地域別の世界分析

Stratistics MRCによると、世界のインテリジェント農業市場は2024年に180億8,000万米ドルを占め、予測期間中のCAGRは11.6％で成長し、2030年には349億3,000万米ドルに達すると予測されています。

インテリジェント農業は、スマート農業としても知られ、農業慣行を最適化するための先進技術、データ分析、自動化の利用を指します。モノのインターネット（IoT）デバイス、ドローン、センサー、人工知能（AI）、機械学習などのツールを組み込み、作物の生育から家畜の管理まで、農業のさまざまな側面を監視・管理します。これらのテクノロジーは、農家がより多くの情報に基づいた意思決定を行い、作物の収量を向上させ、資源の浪費を減らし、持続可能性を高めることを可能にします。

世界銀行によると、テクノロジーに基づく農業システム（スマート農業技術を含む）は、零細農家の収入を大幅に増加させることができます。サハラ以南のアフリカや南アジアなどの地域では、デジタル農業が5億人以上の貧困削減に役立つと世界銀行は見積もっています。

食糧安全保障に対する需要の高まり

食料安全保障に対する世界の需要の高まりが、インテリジェント農業の急成長を促しています。インテリジェント農業は、テクノロジーを活用して農業の生産性と持続可能性を高める革新的なアプローチです。世界の人口は2050年までに100億人近くに達すると予測されており、安定的かつ効率的な食糧供給を確保することが重要な課題となっています。インテリジェント農業は、人工知能（AI）、モノのインターネット（IoT）、ロボット工学、データ分析などの先進技術を駆使して農作業を最適化します。これらのテクノロジーは、土壌の健康状態、作物の状態、天候パターンをリアルタイムで監視することを可能にし、農家が灌漑、施肥、害虫駆除について十分な情報に基づいた判断を下すのに役立ちます。インテリジェント農業は、資源効率を改善し無駄を省くことで、環境への影響を最小限に抑えながら収穫量を増やすことができます。

高い初期投資コスト

初期投資コストの高さは、インテリジェント農業技術の普及にとって大きな障壁となっています。自動化機械、ドローン、センサー、人工知能（AI）システムなどを含むこれらの高度農業ソリューションには、機器とインフラの両方に多額の初期投資が必要です。多くの中小規模の農家にとって、この高い資金負担は法外であり、特に融資や補助金へのアクセスが制限されている地域ではなおさらです。技術そのもの購入に加え、農家はしばしば、研修、メンテナンス、既存システムとの統合のための追加コストに直面します。その結果、十分な財源を持たない農家にとって、より効率的でデータ主導の農法への転換はより困難なものとなります。

アグリテックと金融サービスの統合

アグリテックと金融サービスの統合は、生産性と持続可能性を向上させる高度なツールや金融商品へのアクセスを農家に提供することで、インテリジェント農業に革命をもたらしています。IoTセンサー、AI主導の分析、精密農業ツールといったアグリテックのイノベーションは、作物の健康状態、土壌状態、天候パターンに関するデータをリアルタイムで収集します。このデータは、農家が情報に基づいた意思決定を行う上で貴重なものです。デジタル決済プラットフォーム、農作物保険、信用システムなどの金融サービスと組み合わせることで、農家はテクノロジーへの投資、リスク削減、効率化に必要な資金を利用できるようになります。

熟練労働者の不足

熟練労働者の不足は、農業慣行を改善するためにテクノロジーと自動化に大きく依存するインテリジェント農業の進展における重要な課題です。業界がAI、IoT、ドローン、データ分析などのより高度なシステムを採用するにつれ、これらのテクノロジーを操作、維持、最適化できる熟練労働者の必要性が高まっています。しかし、農業従事者の多くは、こうしたハイテク分野で必要な専門知識を持ち合わせていないです。このギャップは非効率を招き、農家は最新のツールの可能性を十分に活用できずに苦しんでいます。労働力不足は、労働力の高齢化と、若い世代における農業キャリアの魅力の限界によって、さらに深刻化しています。

COVID-19の影響：

COVID-19の大流行は、世界・サプライ・チェーン、労働力の確保、市場アクセスを混乱させることにより、インテリジェント農業に大きな影響を与えました。農業部門は必要不可欠であるが、制限や閉鎖により、特に季節労働者や出稼ぎ労働者に頼ることの多い、植え付け、収穫、包装などの作業において労働力不足が生じた。この労働力不足は、農作物のタイムリーな生産と流通を妨げ、食糧供給に影響を与えました。パンデミックは、労働力不足を補い効率を向上させるため、精密農業、ドローン、IoTベースのモニタリングシステムなど、農業におけるテクノロジーへの依存を促しました。

予測期間中、中規模農場セグメントが最大となる見込み

中規模農場セグメントは、生産性、持続可能性、資源管理を最適化するために先進技術を採用することで、予測期間中最大のシェアを占めると予想されます。これらの農場は、家族経営の小規模農場よりは規模が大きいが、大規模な工業農場よりは規模が小さく、モノのインターネット（IoT）デバイス、センサー、ドローン、人工知能（AI）を農作業に統合する傾向が強まっています。これらの技術は、作物の健康状態、土壌水分、気象条件のリアルタイムモニタリングに役立ち、農家は無駄を最小限に抑えながら収量を向上させるデータ主導の意思決定を行うことができます。

作物モニタリング分野は予測期間中に最も高いCAGRが見込まれます。

作物モニタリング分野は予測期間中に急成長すると予測されます。作物モニタリングはインテリジェント農業の重要な側面であり、現代農業の効率と生産性を大幅に向上させる。衛星画像、ドローン、IoTセンサーなどの先進技術の利用により、農家は作物の健康状態、土壌水分、温度、その他の重要な要素をリアルタイムで継続的に監視することができます。このデータ主導のアプローチにより、農家は的確な意思決定を行うことができ、灌漑の最適化、肥料や農薬の効率的な散布、病気や害虫の蔓延の兆候の早期発見が可能になります。さらに、作物モニタリング・システムは、多くの場合、大量のデータを分析するためにAIや機械学習アルゴリズムを組み込んでおり、作物管理を改善するための予測的洞察や推奨事項を提供します。

最大のシェアを持つ地域

アジア太平洋地域は、推定期間を通じて市場の最大シェアを維持する見通しです。農業セクターの急成長と、気候変動、人口増加、資源不足といった課題の増加に伴い、各国政府はスマート農業ソリューションを優先しています。モノのインターネット（IoT）、人工知能（AI）、ドローン、ロボット工学などの技術の採用を促進するための政策や投資が行われています。これらのイノベーションは、資源利用の最適化、作物収量の向上、サプライチェーン管理の改善、環境への影響の低減に役立ちます。政府はまた、官民パートナーシップを促進し、補助金、助成金、税制優遇措置を提供し、農家の技術採用を奨励しています。

CAGRが最も高い地域：

予測期間中、CAGRが最も高いのは欧州地域と推定されます。テクノロジーが農業セクターを再構築し続ける中、欧州の農家や新興企業は、作物生産の最適化、資源消費の削減、効率化のために、精密農業、AI主導の分析、IoT対応デバイスなどのイノベーションを採用する傾向を強めています。投資の急増は、持続可能性を高め、サプライチェーン管理を改善し、食料安全保障を強化する最先端のソリューションの出現を促進しています。このような資本流入は、既存のAgTech企業と新興新興企業の双方を支援し、事業規模の拡大と市場範囲の拡大を可能にしています。資金調達へのアクセスが増加したことで、欧州の農業はデータ主導型かつ技術的に高度化し、よりスマートで弾力性のある農法が可能になりつつあります。

無料カスタマイズサービス：

本レポートをご購読のお客様には、以下の無料カスタマイズオプションのいずれかをご利用いただけます：

• 企業プロファイル
  • 追加市場プレーヤーの包括的プロファイリング（3社まで）
  • 主要企業のSWOT分析（3社まで）
• 地域セグメンテーション
  • 顧客の関心に応じた主要国の市場推計・予測・CAGR（注：フィージビリティチェックによる）
• 競合ベンチマーキング
  • 製品ポートフォリオ、地理的プレゼンス、戦略的提携に基づく主要企業のベンチマーキング

目次

第1章 エグゼクティブサマリー

第2章 序文

• 概要
• ステークホルダー
• 調査範囲
• 調査手法
  • データマイニング
  • データ分析
  • データ検証
  • 調査アプローチ
• 調査情報源
  • 1次調査情報源
  • 2次調査情報源
  • 前提条件

第3章 市場動向分析

• ドライバー
• 抑制要因
• 機会
• 脅威
• 技術分析
• 用途分析
• 新興市場
• COVID-19の影響

第4章 ポーターのファイブフォース分析

• 供給企業の交渉力
• 買い手の交渉力
• 代替品の脅威
• 新規参入業者の脅威
• 競争企業間の敵対関係

第5章 世界のインテリジェント農業市場：農場規模別

• 小規模農場
• 中規模農場
• 大規模農場

第6章 世界のインテリジェント農業市場：技術別

• モノのインターネット（IoT）
• 人工知能（AI）
• ロボット工学と自動化
• クラウドコンピューティング
• その他の規模

第7章 世界のインテリジェント農業市場：用途別

• 精密農業
• 家畜監視
• 作物モニタリング
• スマート温室
• 農業用ドローン

第8章 世界のインテリジェント農業市場：地域別

• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • イタリア
  • フランス
  • スペイン
  • その他欧州
• アジア太平洋
  • 日本
  • 中国
  • インド
  • オーストラリア
  • ニュージーランド
  • 韓国
  • その他アジア太平洋
• 南米
  • アルゼンチン
  • ブラジル
  • チリ
  • その他南米
• 中東・アフリカ
  • サウジアラビア
  • アラブ首長国連邦
  • カタール
  • 南アフリカ
  • その他中東とアフリカ

第9章 主な発展

• 契約、パートナーシップ、コラボレーション、合弁事業
• 買収と合併
• 新製品発売
• 事業拡大
• その他の主要戦略

第10章 企業プロファイリング

• AG Leader Technology
• AGCO Corporation
• BASF Agricultural Solutions
• Bayer AG
• John Deere
• Kubota Corporation
• Raven Industries
• Syngenta AG
• Trimble Inc
• Topcon Positioning Systems
• KUKA AG
• JH Robotics, Inc
• Kawasaki Heavy Industries

List of Tables

• Table 1 Global Intelligent Agriculture Market Outlook, By Region (2022-2030) ($MN)
• Table 2 Global Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 3 Global Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 4 Global Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 5 Global Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 6 Global Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 7 Global Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 8 Global Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 9 Global Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 10 Global Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 11 Global Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 12 Global Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 13 Global Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 14 Global Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 15 Global Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 16 Global Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 17 Global Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
• Table 18 North America Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
• Table 19 North America Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 20 North America Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 21 North America Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 22 North America Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 23 North America Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 24 North America Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 25 North America Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 26 North America Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 27 North America Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 28 North America Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 29 North America Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 30 North America Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 31 North America Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 32 North America Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 33 North America Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 34 North America Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
• Table 35 Europe Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
• Table 36 Europe Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 37 Europe Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 38 Europe Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 39 Europe Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 40 Europe Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 41 Europe Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 42 Europe Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 43 Europe Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 44 Europe Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 45 Europe Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 46 Europe Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 47 Europe Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 48 Europe Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 49 Europe Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 50 Europe Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 51 Europe Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
• Table 52 Asia Pacific Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
• Table 53 Asia Pacific Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 54 Asia Pacific Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 55 Asia Pacific Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 56 Asia Pacific Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 57 Asia Pacific Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 58 Asia Pacific Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 59 Asia Pacific Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 60 Asia Pacific Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 61 Asia Pacific Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 62 Asia Pacific Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 63 Asia Pacific Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 64 Asia Pacific Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 65 Asia Pacific Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 66 Asia Pacific Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 67 Asia Pacific Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 68 Asia Pacific Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
• Table 69 South America Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
• Table 70 South America Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 71 South America Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 72 South America Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 73 South America Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 74 South America Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 75 South America Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 76 South America Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 77 South America Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 78 South America Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 79 South America Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 80 South America Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 81 South America Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 82 South America Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 83 South America Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 84 South America Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 85 South America Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
• Table 86 Middle East & Africa Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
• Table 87 Middle East & Africa Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
• Table 88 Middle East & Africa Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
• Table 89 Middle East & Africa Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
• Table 90 Middle East & Africa Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
• Table 91 Middle East & Africa Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
• Table 92 Middle East & Africa Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
• Table 93 Middle East & Africa Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
• Table 94 Middle East & Africa Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
• Table 95 Middle East & Africa Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
• Table 96 Middle East & Africa Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
• Table 97 Middle East & Africa Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
• Table 98 Middle East & Africa Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
• Table 99 Middle East & Africa Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
• Table 100 Middle East & Africa Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
• Table 101 Middle East & Africa Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
• Table 102 Middle East & Africa Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)

According to Stratistics MRC, the Global Intelligent Agriculture Market is accounted for $18.08 billion in 2024 and is expected to reach $34.93 billion by 2030 growing at a CAGR of 11.6% during the forecast period. Intelligent agriculture, also known as smart farming, refers to the use of advanced technologies, data analytics, and automation to optimize agricultural practices. It incorporates tools such as Internet of Things (IoT) devices, drones, sensors, artificial intelligence (AI), and machine learning to monitor and manage various aspects of farming, from crop growth to livestock management. These technologies enable farmers to make more informed decisions, improve crop yields, reduce resource wastage and enhance sustainability.

According to the World Bank, technology-based agriculture systems (including smart farming techniques) can significantly increase smallholder farmers' income. In regions such as Sub-Saharan Africa and South Asia, the World Bank estimates that digital agriculture could help reduce poverty for over 500 million people.

Market Dynamics:

Driver:

Rising demand for food security

Rising global demand for food security is driving the rapid growth of Intelligent Agriculture, an innovative approach that leverages technology to enhance agricultural productivity and sustainability. With the world's population projected to reach nearly 10 billion by 2050, ensuring a stable and efficient food supply has become a critical concern. Intelligent Agriculture uses advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), robotics, and data analytics to optimize farming practices. These technologies enable real-time monitoring of soil health, crop conditions, and weather patterns, helping farmers make informed decisions on irrigation, fertilization, and pest control. By improving resource efficiency and reducing waste, Intelligent Agriculture can increase yields while minimizing environmental impact.

Restraint:

High initial investment costs

High initial investment costs are a significant barrier to the widespread adoption of intelligent agriculture technologies. These advanced farming solutions, which include automated machinery, drones, sensors, and artificial intelligence (AI) systems, require substantial upfront capital for both the equipment and infrastructure. For many small and medium-sized farmers, this high financial burden is prohibitive, especially in regions where access to financing or subsidies is limited. In addition to the purchase of the technologies themselves, farmers often face additional costs for training, maintenance, and integration with existing systems. As a result, the shift towards more efficient, data-driven farming practices becomes more challenging for those without sufficient financial resources.

Opportunity:

Integration of Agri-tech with financial services

The integration of agri-tech with financial services is revolutionizing intelligent agriculture by providing farmers with access to advanced tools and financial products that improve productivity and sustainability. Agri-tech innovations, such as IoT sensors, AI-driven analytics, and precision farming tools, collect real-time data on crop health, soil conditions, and weather patterns. This data is valuable for farmers to make informed decisions. When coupled with financial services like digital payment platforms, crop insurance, and credit systems, farmers can access the necessary capital to invest in technology, reduce risks, and increase efficiency.

Threat:

Shortage of skilled labor

The shortage of skilled labor is a significant challenge in the advancement of intelligent agriculture, which relies heavily on technology and automation to improve farming practices. As the industry adopts more advanced systems such as AI, IoT, drones, and data analytics, there is a growing need for skilled workers who can operate, maintain, and optimize these technologies. However, many agricultural workers lack the necessary expertise in these high-tech fields. This gap results in inefficiencies, as farmers struggle to fully harness the potential of modern tools. The labor shortage is further compounded by an aging workforce and the limited appeal of agricultural careers among younger generations.

Covid-19 Impact:

The COVID-19 pandemic significantly impacted intelligent agriculture by disrupting global supply chains, labor availability, and market access. While the agriculture sector is essential, the restrictions and lockdowns led to labor shortages, especially in tasks like planting, harvesting, and packaging, which were often reliant on seasonal or migrant workers. This labor deficit hindered the timely production and distribution of crops, affecting food supply. The pandemic prompted a greater reliance on technology in agriculture, such as precision farming, drones, and IoT-based monitoring systems, to compensate for the workforce shortage and improve efficiency.

The Medium Scale Farms segment is expected to be the largest during the forecast period

Medium Scale Farms segment is expected to dominate the largest share over the estimated period, by adopting advanced technologies to optimize productivity, sustainability, and resource management. These farms, which are larger than small family-run operations but smaller than large industrial farms, are increasingly integrating Internet of Things (IoT) devices, sensors, drones, and artificial intelligence (AI) into their farming practices. These technologies help in real-time monitoring of crop health, soil moisture, and weather conditions, allowing farmers to make data-driven decisions that improve yields while minimizing waste.

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

Crop Monitoring segment is estimated to grow at a rapid pace during the forecast period. Crop monitoring is a key aspect of intelligent agriculture, significantly enhancing the efficiency and productivity of modern farming. Through the use of advanced technologies such as satellite imagery, drones, and IoT sensors, farmers can continuously monitor crop health, soil moisture, temperature, and other vital factors in real-time. This data-driven approach allows for precise decision-making, enabling farmers to optimize irrigation, apply fertilizers and pesticides more efficiently, and detect early signs of diseases or pest infestations. Furthermore, crop monitoring systems often incorporate AI and machine learning algorithms to analyze large volumes of data, providing predictive insights and recommendations for improved crop management.

Region with largest share:

Asia Pacific region is poised to hold the largest share of the market throughout the extrapolated period. With the rapid growth of the agricultural sector and increasing challenges like climate change, population growth, and resource scarcity, governments are prioritizing smart farming solutions. Policies and investments are being made to promote the adoption of technologies such as Internet of Things (IoT), Artificial Intelligence (AI), drones, and robotics. These innovations help optimize resource use, enhance crop yields, improve supply chain management, and reduce environmental impacts. Governments are also fostering public-private partnerships, providing subsidies, grants, and tax incentives to encourage technological adoption among farmers.

Region with highest CAGR:

Europe region is estimated to witness the highest CAGR during the projected time frame. As technology continues to reshape the agricultural sector, European farmers and startups are increasingly adopting innovations like precision farming, AI-driven analytics, and IoT-enabled devices to optimize crop production, reduce resource consumption, and increase efficiency. The surge in investment has facilitated the emergence of cutting-edge solutions that enhance sustainability, improve supply chain management, and boost food security. This capital influx supports both established AgTech companies and emerging startups, enabling them to scale their operations and expand their market reach. With increased access to funding, European agriculture is becoming more data-driven and technologically advanced, allowing for smarter, more resilient farming practices.

Key players in the market

Some of the key players in Intelligent Agriculture market include AG Leader Technology, AGCO Corporation, BASF Agricultural Solutions, Bayer AG, John Deere, Kubota Corporation, Raven Industries, Syngenta AG, Trimble Inc, Topcon Positioning Systems, KUKA AG, JH Robotics, Inc and Kawasaki Heavy Industries.

Key Developments:

In July 2024, AGCO to Launch Autonomous Tractor Retrofit Kits for Mixed-fleets. The retrofit kits will enable select Fendt and John Deere tractors to autonomously perform grain cart and tillage functions, with more tractor compatibility and functions coming in the future.

In March 2024, Kubota Launches RTV520 Crossroads Edition. This refresh to the 2020 model adds a handful of factory-installed features based on popular request. This new limited edition of the RTV520 comes with a package of factory-installed creature comforts.

Farm Sizes Covered:

• Small Scale Farms
• Medium Scale Farms
• Large Scale Farms

Technologies Covered:

• Internet of Things (IoT)
• Artificial Intelligence (AI)
• Robotics and Automation
• Cloud Computing
• Other Technologies

Applications Covered:

• Precision Farming
• Livestock Monitoring
• Crop Monitoring
• Smart Greenhouses
• Agricultural Drones

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 2022, 2023, 2024, 2026, and 2030
• 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 Emerging Markets
• 3.9 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 Intelligent Agriculture Market, By Farm Size

• 5.1 Introduction
• 5.2 Small Scale Farms
• 5.3 Medium Scale Farms
• 5.4 Large Scale Farms

6 Global Intelligent Agriculture Market, By Technology

• 6.1 Introduction
• 6.2 Internet of Things (IoT)
• 6.3 Artificial Intelligence (AI)
• 6.4 Robotics and Automation
• 6.5 Cloud Computing
• 6.6 Other Technologies

7 Global Intelligent Agriculture Market, By Application

• 7.1 Introduction
• 7.2 Precision Farming
• 7.3 Livestock Monitoring
• 7.4 Crop Monitoring
• 7.5 Smart Greenhouses
• 7.6 Agricultural Drones

8 Global Intelligent Agriculture Market, By Geography

• 8.1 Introduction
• 8.2 North America
  • 8.2.1 US
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 UK
  • 8.3.3 Italy
  • 8.3.4 France
  • 8.3.5 Spain
  • 8.3.6 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 Japan
  • 8.4.2 China
  • 8.4.3 India
  • 8.4.4 Australia
  • 8.4.5 New Zealand
  • 8.4.6 South Korea
  • 8.4.7 Rest of Asia Pacific
• 8.5 South America
  • 8.5.1 Argentina
  • 8.5.2 Brazil
  • 8.5.3 Chile
  • 8.5.4 Rest of South America
• 8.6 Middle East & Africa
  • 8.6.1 Saudi Arabia
  • 8.6.2 UAE
  • 8.6.3 Qatar
  • 8.6.4 South Africa
  • 8.6.5 Rest of Middle East & Africa

9 Key Developments

• 9.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 9.2 Acquisitions & Mergers
• 9.3 New Product Launch
• 9.4 Expansions
• 9.5 Other Key Strategies

10 Company Profiling

• 10.1 AG Leader Technology
• 10.2 AGCO Corporation
• 10.3 BASF Agricultural Solutions
• 10.4 Bayer AG
• 10.5 John Deere
• 10.6 Kubota Corporation
• 10.7 Raven Industries
• 10.8 Syngenta AG
• 10.9 Trimble Inc
• 10.10 Topcon Positioning Systems
• 10.11 KUKA AG
• 10.12 JH Robotics, Inc
• 10.13 Kawasaki Heavy Industries