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現代農業中的人工智慧、物聯網和區塊鏈市場——全球和區域分析：按應用、產品和國家分類——分析和預測（2025-2035 年）
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現代農業中的人工智慧、物聯網和區塊鏈市場——全球和區域分析：按應用、產品和國家分類——分析和預測（2025-2035 年）

AI, IoT, and Blockchain Market in Modern Agriculture - A Global and Regional Analysis: Focus on Application, Product, and Country Analysis - Analysis and Forecast, 2025-2035
出版日期: | 出版商: BIS Research | 英文 160 Pages | 商品交期: 1-5個工作天內

價格

現代農業中人工智慧、物聯網和區塊鏈的市場規模預計將從 2025 年的 243.13 億美元成長到 2035 年的 1,545.465 億美元，複合年成長率為 20.32%。

這一成長得益於整個農業價值鏈的快速數位轉型，包括智慧感測器、物聯網連接設備、人工智慧分析和基於區塊鏈的溯源平台的普及。提高產量、降低營運成本、實現氣候友善農業以及增強供應鏈透明度的壓力日益增大，正在加速全球農場採用先進的數位化工具。

關鍵市場統計數據
預測期 2025-2035
2025年市場規模 243億美元
2035 年預測 1545.4億美元
複合年成長率 20.32%

人工智慧驅動的農業模型、自主農機、無人機和連網農業設備正在重塑營運效率，而物聯網感測器、農場管理系統和衛星監測則助力即時決策。隨著食品公司和監管機構將可追溯性和永續性檢驗置於優先地位，區塊鏈的應用正在加速。儘管整體發展勢頭強勁，但市場仍面臨諸多挑戰，例如數據互通性、農民的數位素養、高昂的初始成本以及農村地區通訊基礎設施的限制。隨著設備製造商、農業科技公司和政府加大投資，預計到2035年，該產業將保持強勁成長。

現代農業中的人工智慧、物聯網和區塊鏈市場簡介

根據BIS Research的研究，人工智慧、物聯網和區塊鏈在現代農業領域的應用是下一代糧食生產系統的核心驅動力，引領農業從傳統模式轉型為數據驅動、自動化和氣候友善農業。數位技術正發展成為功能強大的工具，支援即時作物資訊、自主田間作業、精準投入管理和透明供應鏈。

人工智慧模型和機器視覺系統能夠更早檢測病蟲害和營養缺乏，而物聯網感測器則持續監測土壤、天氣和設備性能。衛星影像、無人機和雲分析的整合進一步提高了決策的準確性。區塊鏈平台支援端到端的可追溯性，確保符合食品安全、品質保證和永續性標準。

隨著全球農業面臨日益嚴峻的壓力，包括氣候變遷、勞動力短缺、糧食安全問題以及永續性義務，數位化解決方案為農民和農業相關企業提供了戰略優勢。在對智慧農業技術投資增加、政府推動數位農業發展以及全球透過技術主導提高農業生產力的努力的共同推動下，預計未來十年該市場將顯著成長。

市場概覽

在對即時田間資訊、自動化作業和資料最佳化決策日益成長的需求驅動下，人工智慧、物聯網和區塊鏈市場正在現代農業領域迅速崛起，成為該領域的基石。隨著糧食系統日益複雜化和氣候風險加劇，從智慧感測器和機器人到先進分析平台等一系列數位農業技術，將使農民能夠以前所未有的精準度管理作物、牲畜和資源。

人工智慧增強了產量、天氣和投入需求的預測模型，而物聯網設備則將農業機械、環境感測器和牲畜監測系統連接成一個整合的資料生態系統。區塊鏈透過檢驗生產實踐、認證永續性和預防欺詐，提高了整個供應鏈的可靠性和透明度。

隨著人們對氣候友善農業、資源效率和可追溯食品體系的關注度日益提高，世界各國政府、農業技術公司和農業相關企業正加速對數位農業的投資。隨著這些技術的不斷發展和整合，人工智慧、物聯網和區塊鏈有望在塑造全球農業的未來中發揮關鍵作用。

對產業的影響

人工智慧、物聯網和區塊鏈正在將現代農業轉型為一個更數據驅動、高效和工業化的系統。人工智慧能夠提供預測性洞察，例如產量預測、病蟲害檢測和投入最佳化，幫助農場提高生產力，同時降低成本和減少廢棄物。物聯網將田間、畜舍和倉儲設施中的感測器、機械和設備連接起來，提供土壤狀況、天氣、灌溉和資產性能的即時可見性。區塊鏈透過提高從農業投入到最終消費者的整個價值鏈的可追溯性、透明度和課責，構建了一個值得信賴的數位基礎，從而支持食品安全、永續性聲明和更快捷的支付。這些技術共同推動農業從人工、被動的實踐轉向符合現代工業標準的擴充性、自動化和績效驅動型運作。

市場區隔:

細分 1：按應用

  • 作物生產最佳化
  • 水和養分管理
  • 智慧農業的監測與自動化
  • 畜牧管理

在現代農業的人工智慧、物聯網和區塊鏈市場中，作物生產最佳化預計將成為（按應用領域分類的）主導關注點。

在現代農業的人工智慧、物聯網和區塊鏈市場中，作物生產最佳化預計將在 2025 年至 2035 年間繼續成為主要應用領域。該領域預計將從 2025 年的 87.955 億美元成長到 2035 年的 517.336 億美元，複合年成長率高達 19.39%。

這一成長得益於人工智慧驅動的作物建模、精準施肥、智慧成像和感測器整合式田間監測等技術的日益普及。所有這些都有助於提高產量、減少廢棄物並最佳化資源利用。農民和企業正在迅速採用人工智慧驅動的決策工具、衛星分析和物聯網感測器網路來監測作物脅迫、實現養分自動供給並提高整個生長季的生產力。

水和營養管理預計將成為成長最快的領域，從 2025 年的 45.751 億美元成長到 2035 年的 328.581 億美元，複合年成長率高達 21.79%。

這種快速成長是由水資源壓力日益增大、肥料最佳化需求增加以及土壤濕度感測器、電化學養分監測器、自動化灌溉系統和基於人工智慧的施肥灌溉模型等技術的融合應用所驅動的。智慧灌溉物聯網平台和預測分析技術正被廣泛採用，以降低營運成本、節約用水並保障作物健康。

預計到2035年，智慧農業監測與自動化市場規模將從2025年的57.775億美元成長至382.398億美元，複合年成長率（CAGR）為20.80%。主要促進因素包括以下應用：

  • 自主農業機械
  • 配備電腦視覺的機器人平台
  • 利用無人機進行實地分析
  • 氣候觀測站
  • 互聯農場管理系統

這些技術使農場能夠自主運營，提高即時監控能力，並減少對人力的依賴。

細分2：按產品

  • 人工智慧（AI）
  • 物聯網
  • 區塊鏈平台

在現代農業的人工智慧、物聯網和區塊鏈市場中，物聯網 (IoT) 預計將繼續保持主導地位（按產品分類）。

根據最新的市場估算和預測，物聯網 (IoT) 領域預計將在 2035 年之前繼續保持其在現代農業人工智慧、物聯網和區塊鏈市場中的領先產品類型。物聯網領域在 2025 年的價值將達到 216.595 億美元，預計到 2035 年將達到 1,205.556 億美元，複合年成長率 (CAGR) 為 18.73%，實現了強勁成長。

物聯網憑藉其在實現互聯互通和自動化農業營運中的關鍵作用，持續保持主導地位。感測器網路、連接模組和閘道器設備透過產生土壤狀況、作物生長、氣候參數、農業機械運作和牲畜行為等即時數據，構成了智慧農業的基礎。隨著農場向數據驅動決策和自動化轉型，物聯網平台在提高產量、減少投入和最佳化資源管理方面仍發揮核心作用。

在物聯網領域，光學感測器、電化學感測器和定位感測器等感測器設備佔據了最大的市場佔有率，這得益於它們在田間監測、自動灌溉和精準養分管理等領域的廣泛應用。隨著感測器系統與雲端控制面板和行動應用程式的整合度不斷提高，其在小規模、中型和大型農業生產中的應用正在加速。

總體而言，物聯網技術將繼續成為數位農業生態系統的基礎，支援從即時監控到預測分析的一切，並鞏固其作為市場主要產品類型的地位。

細分3：按地區

  • 北美洲：美國、加拿大、墨西哥
  • 歐洲：德國、法國、英國、荷蘭、西班牙等
  • 亞太地區：中國、日本、印度、澳洲及其他地區
  • 其他地區：南美洲、中東和非洲

北美在全球現代農業人工智慧、物聯網和區塊鏈市場中保持主導地位，預計在預測期內將保持最高的區域市場規模。市場規模預計將從2025年的85.152億美元成長到2035年的470.849億美元，複合年成長率高達18.65%。這一成長主要得益於精密農業技術的快速普及、物聯網感測器和農業自動化系統的廣泛應用，以及支撐數據驅動型農業的強大數位基礎設施。美國在人工智慧作物分析、自主農機、智慧灌溉和數位化農場管理平台等領域投入大量資金，引領該地區的發展。

亞太地區預計將成為成長最快的市場，從2025年的58.29億美元成長到2035年的450.679億美元，複合年成長率高達22.70%。這一快速成長主要得益於不斷成長的糧食需求、中國、印度、日本、韓國和澳洲等國大規模推進的數位化農業舉措，以及物聯網感測器、人工智慧驅動的作物智慧平台和智慧灌溉系統的廣泛應用。亞太各國正優先發展農業自動化、氣候智慧型農業和數位化諮詢工具，以提高生產力和永續性。

歐洲仍然是一個技術先進且成熟的市場，預計將從2025年的66.26億美元成長到2035年的426.78億美元，複合年成長率達20.52%。該地區受益於對永續農業的強大監管支持，以及農場管理軟體、溫室自動化、機器人技術和基於區塊鏈的溯源平台的高普及率。德國、法國、英國和荷蘭等國在智慧農業研究、可控環境農業和精準畜牧管理方面持續發揮主導作用。

該區域其他地區，包括南美洲、中東和非洲，預計將從2025年的33.545億美元成長到2035年的197.156億美元，複合年成長率高達19.38%。這一成長主要得益於自動化灌溉、作物監測工具和數位諮詢平台的日益普及，尤其是在缺水地區。

需求：促進因素、限制因素與機遇

市場需求：對精密農業、永續性和數據驅動型農業的需求不斷成長。

隨著全球農業領域快速推動數位轉型，現代農業中的人工智慧、物聯網和區塊鏈市場正經歷強勁的需求成長。推動市場擴張的關鍵因素包括對精密農業、資源最佳化和氣候適應耕作方式日益成長的需求。

推動農業發展的關鍵因素之一是物聯網感測器的日益普及，這些感測器能夠提供土壤濕度、養分含量、作物健康狀況和天氣狀況的即時數據。這些資訊使農民能夠最佳化水、肥料和農藥等投入的使用，從而提高產量並減少對環境的影響。人工智慧驅動的分析技術能夠實現預測建模、產量預測和作物病害的早期檢測，進一步增強決策能力，減少經濟損失，並提高農場盈利。

氣候變遷和日益嚴重的水資源短缺也加速了對先進數位工具的需求。智慧灌溉系統、人工智慧驅動的水資源管理和溫室自動化控制等技術，能夠幫助農民在不斷變化的環境條件下維持生產穩定。同時，不斷成長的全球糧食需求也迫使生產商採用自動化和機器人技術，以應對勞動力短缺並提高田間作業效率。

農業供應鏈也是需求的主要驅動力。在日益嚴格的監管要求和消費者對檢驗食品品質的期望的推動下，區塊鏈平台正被擴大用於確保從農場到餐桌的可追溯性、食品安全和透明物流。

這些技術的進步，結合起來，使人工智慧、物聯網和區塊鏈成為現代農業中必不可少的工具，使農民和農業相關企業能夠以更高的精準度、永續性和韌性進行運作。

市場限制因素：缺乏數據、高成本、基礎設施有限。

儘管人工智慧、物聯網和區塊鏈在現代農業領域的應用十分廣泛，但這些市場仍面臨一些挑戰，可能會阻礙大規模部署。

限制因素之一是農村地區，特別是開發中國家，缺乏數位基礎設施。寬頻連線有限、智慧型裝置普及率低以及電力供應不穩定，都降低了物聯網感測器、連網裝置和雲端資料平台的效能。

成本仍然是一大障礙。人工智慧驅動的機械、無人機、物聯網感測器網路和資料管理平台所需的初始投資對於中小農戶來說可能負擔過重。即使硬體成本下降，訂閱平台、資料儲存和設備維護等相關的持續成本也會阻礙技術的普及。

資料碎片化也是一大挑戰。農業數據通常使用不相容的系統、多種設備和專有平台進行收集，導致互通性問題和資訊孤島。許多生產者缺乏數據素養，限制了他們充分利用分析和決策支援工具的能力。

網路安全風險也令人擔憂。隨著農場網路化程度的提高，資料外洩、設備未授權存取以及供應鏈記錄被篡改的風險也在增加。因此，需要更強力的安全措施和標準來保護農業資料。

最後，技術技能和熟練人員的缺乏正在減緩數位解決方案的採用和管理速度，尤其是在新興市場。

市場機會：自主農業、氣候變遷因應解決方案與基於區塊鏈的可追溯性

新興技術正在為現代農業中的人工智慧、物聯網和區塊鏈市場創造巨大的成長機會。

最具發展前景的機會之一在於自主和機器人農業系統，包括自動駕駛曳引機、無人機噴灑器、自動收割機和除草機器人。這些技術有助於解決勞動力短缺問題，提高效率，並支持大規模農業生產。

氣候智慧型農業也蘊藏著巨大的機會。先進的分析技術、機器學習模型和基於物聯網的氣象監測能夠幫助農民更好地應對極端天氣事件，最佳化資源利用，並增強抵禦能力。人工智慧驅動的作物病害預測、即時自動灌溉和基於感測器的溫室環境最佳化等解決方案尤其受到青睞。

區塊鏈具有變革農業供應鏈的潛力。它能夠實現從種子到商店的全程透明化，從而提升食品安全、預防詐欺並增強消費者信任。隨著各國政府和全球食品公司日益重視數位化溯源，區塊鏈平台供應商正迎來龐大的商機。

此外，衛星影像、無人機影像和地面感測器的整合正在為人工智慧驅動的作物智慧平台開闢新的市場。這些平台可以為生產者、農產品供應商、金融機構、保險公司、食品加工商等提供服務。

總體而言，隨著數位生態系統的成熟，人工智慧、物聯網和區塊鏈的整合將繼續為整個農業領域創造新的價值，從農場最佳化到全球價值鏈的數位化。

這份報告將為組織帶來什麼價值？

產品與創新策略：本報告深入剖析了人工智慧、物聯網和區塊鏈技術如何改變現代農業，為企業提供詳盡的洞察。報告重點在於人工智慧驅動的作物智慧、物聯網賦能的感測網路、自主農業機械、數位雙胞胎以及基於區塊鏈的溯源系統等新興創新技術。這些技術能夠實現農場即時監測、預測分析和資源高效利用。報告涵蓋了從用於了解作物健康狀況的機器視覺到用於提升供應鏈透明度的分散式帳本系統等一系列技術進步，為產品開發團隊、研發部門和創新領導者提供切實可行的洞察。企業可以利用這些洞察來設計下一代精密農業工具，增強設備和平台之間的互通性，並建立可擴展的數位化農業解決方案，以滿足不斷變化的市場需求。

成長與行銷策略：人工智慧、物聯網和區塊鏈在現代農業領域擁有強勁的成長潛力，遍及所有主要農業區。本報告概述了領先主要企業採取的關鍵策略，包括併購（例如，凱斯紐荷蘭工業集團收購Raven）、策略聯盟（例如，迪爾公司在自動化領域的合作）以及雲端農場管理平台的擴展。報告還指出了智慧灌溉、畜牧自動化、自動駕駛曳引機、溫室數位化和區塊鏈驅動的價值鏈系統等關鍵成長領域。隨著農民、合作社、供應商和食品公司日益採用數據驅動的實踐，企業可以利用本報告來最佳化市場定位、改善打入市場策略，並透過有針對性的產品和附加價值服務進入高潛力細分市場。

競爭策略：本報告全面分析了數位農業生態系統的競爭格局，重點關注設備製造商、農業科技Start-Ups、物聯網感測器供應商、人工智慧分析公司和區塊鏈平台等關鍵參與者。報告深入檢驗了影響競爭動態的策略性舉措，例如夥伴關係、技術合作、合資企業、平台整合和產品發布。透過競爭標竿分析，企業可以辨識尚未開發的機遇，評估競爭對手的能力，並分析新興威脅。隨著農業快速向自動化、遙感探測、雲端分析和分散式資料系統轉型，創新速度、互通性、資料所有權和生態系統整合等方面的競爭將日益激烈。本報告的洞見將有助於企業增強其長期競爭優勢，並在不斷發展的數位農業市場中獲得更大的市場佔有率。

調查方法

數據預測和建模中的因素

  • 在對現代農業中的人工智慧、物聯網和區塊鏈市場進行分析時，我們以美元為基準貨幣。為便於統計計算，除美元以外的其他貨幣均採用當年的平均外匯轉換為美元。
  • 外匯以Oanda網站上的歷史外匯為準。
  • 本研究考慮了 2021 年 1 月至 2024 年 3 月期間幾乎所有最新發展。
  • 本報告中呈現的資訊是基於詳細的一手訪談、調查和二手分析的結果。
  • 如果相關資訊不可用，則使用替代指標或推斷方法。
  • 市場估計和預測並未考慮未來的景氣衰退。
  • 除非出現重大技術突破，否則目前使用的技術預計將在整個預測期內繼續沿用。

市場估計和預測

本研究利用了廣泛的二級資訊來源，包括權威出版物、著名作者的報導、白皮書、公司年報、名錄和主要資料庫，以收集有用且有效的資訊，對現代農業中的人工智慧、物聯網和區塊鏈市場進行全面、技術性、市場導向性和商業性調查。

市場分析流程包括計算市場統計數據、估算市場規模、預測市場趨勢、深入分析市場以及數據三角驗證（這些定量數據處理技術的具體調查方法將在後續章節中詳細介紹）。我們進行了初步調查，以收集有關市場細分類型和主要企業行業趨勢的資訊，並檢驗市場數據的有效性。

主要市場參與企業及競爭格局概述

本報告中介紹的現代農業人工智慧、物聯網和區塊鏈市場公司，是根據專家對其技術能力、解決方案廣度、全球覆蓋範圍以及在整個數位農業價值鏈中的市場滲透率的意見而選定的。

現代農業領域人工智慧、物聯網和區塊鏈市場的主要企業

  • Deere & Company
  • Robert Bosch GmbH
  • CNH Industrial NV
  • Trimble Inc.
  • Signify Holding
  • Taranis
  • CropIn Technology Solutions
  • Plantix (PEAT GmbH)
  • Ceres Imaging
  • Climate LLC (The Climate Corporation)
  • AGRIVI
  • Regen Network Development
  • SZ DJI Technology Co., Ltd. (DJI)
  • OSRAM GmbH (ams OSRAM)
  • Granular Inc.

現代農業的人工智慧、物聯網和區塊鏈市場部分也全面涵蓋了不屬於上述群體的公司（如適用）。

目錄

執行摘要

第1章 市場：產業展望

  • 趨勢：對當前和未來影響的評估
    • 人工智慧驅動的作物分析和決策支持
    • 利用物聯網進行精準灌溉和養分管理。
    • 利用機器人和無人機的智慧農業自動化
  • 監理情勢
  • 研究與發展評論
    • 專利申請趨勢（按國家和公司分類）
  • Start-Ups產業的現狀
  • 相關人員分析
    • 用例
    • 最終用戶和採購標準
  • 重大全球事件的影響分析
  • 市場動態概述
  • 市場動態
    • 市場促進因素
    • 市場挑戰
    • 市場機遇

第2章：現代農業中的人工智慧、物聯網和區塊鏈市場（按應用領域分類）

  • 用途概述
  • 現代農業中的人工智慧、物聯網和區塊鏈市場（按應用領域分類）
    • 作物生產最佳化
    • 水和養分管理
    • 智慧農場監測和自動化
    • 畜牧管理

第3章：現代農業中的人工智慧、物聯網和區塊鏈市場（按產品分類）

  • 產品概述
  • 現代農業中的人工智慧、物聯網和區塊鏈市場（按產品分類）
    • 人工智慧（AI）
    • 物聯網
    • 區塊鏈平台

第4章：現代農業中的人工智慧、物聯網和區塊鏈市場（按地區分類）

  • 現代農業中的人工智慧、物聯網和區塊鏈市場（按地區分類）
  • 北美洲
    • 區域概覽
    • 市場促進因素
    • 市場限制因素
    • 應用
    • 產品
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 區域概覽
    • 市場促進因素
    • 市場限制因素
    • 應用
    • 產品
    • 德國
    • 法國
    • 英國
    • 荷蘭
    • 西班牙
    • 其他
  • 亞太地區
    • 區域概覽
    • 市場促進因素
    • 市場限制因素
    • 應用
    • 產品
    • 中國
    • 日本
    • 印度
    • 澳洲
    • 其他
  • 其他地區
    • 區域概覽
    • 市場促進因素
    • 市場限制因素
    • 應用
    • 產品
    • 中東和非洲
    • 南美洲

第5章：公司簡介

第6章：調查方法

Product Code: AGA3621SA

This report can be delivered within 1 working day.

AI, IoT, and Blockchain Market in Modern Agriculture Overview

The AI, IoT, and blockchain market in modern agriculture is projected to grow from $24,301.3 million in 2025 to $154,546.5 million by 2035, registering a CAGR of 20.32%. Growth is being driven by rapid digital transformation across the agricultural value chain, including the widespread adoption of smart sensors, IoT-connected devices, AI-driven analytics, and blockchain-based traceability platforms. Increasing pressure to improve yield, reduce operational costs, enable climate-smart farming, and strengthen supply-chain transparency is accelerating the deployment of advanced digital tools in farms globally.

KEY MARKET STATISTICS
Forecast Period2025 - 2035
2025 Evaluation$24.30 Billion
2035 Forecast$154.54 Billion
CAGR20.32%

AI-powered agronomic models, autonomous machinery, drones, and connected farm equipment are reshaping operational efficiency, while IoT sensors, farm management systems, and satellite-based monitoring enable real-time decision-making. Blockchain adoption is growing as food companies and regulators prioritize traceability and sustainability verification. Despite strong overall momentum, the market faces challenges related to data interoperability, digital literacy among farmers, high upfront costs, and connectivity limitations in rural areas. With rising investment from equipment OEMs, agtech companies, and governments, the sector is set for robust expansion through 2035.

Introduction of the AI, IoT, and Blockchain Market in Modern Agriculture

The study conducted by BIS Research identifies the AI, IoT, and blockchain market in modern agriculture as a core enabler of next-generation food production systems, driving the transition from traditional farming to data-driven, automated, and climate-smart agriculture. Digital technologies are evolving into multifunctional tools that support real-time crop intelligence, autonomous field operations, precise input management, and transparent supply chains.

AI models and machine vision systems strengthen early detection of pests, diseases, and nutrient deficiencies, while IoT sensors provide continuous monitoring of soil, weather, and equipment performance. The integration of satellite imagery, drones, and cloud analytics further enhances decision accuracy. Blockchain platforms support end-to-end traceability, ensuring food safety, quality assurance, and compliance with sustainability standards.

As global agriculture faces rising pressures, climate variability, labor shortages, food security concerns, and sustainability mandates, digital solutions offer farmers and agribusinesses a strategic advantage. The market is expected to grow significantly in the coming decade, supported by rising investment in smart farming technologies, government digital agriculture missions, and global efforts to increase farm productivity through technology-driven innovation.

Market Introduction

The AI, IoT, and blockchain market in modern agriculture is rapidly emerging as a foundational pillar of modern farming, driven by growing demand for real-time field intelligence, automated operations, and data-optimized decision-making. As food systems become more complex and climate risks intensify, digital agriculture technologies, ranging from smart sensors and robotics to advanced analytics platforms, enable farmers to manage crops, livestock, and resources with unprecedented precision.

AI enhances predictive modeling for yield, weather, and input requirements, while IoT devices connect farm machinery, environmental sensors, and livestock monitoring systems into a unified data ecosystem. Blockchain strengthens trust and transparency across the supply chain by verifying production practices, certifying sustainability, and preventing fraud.

With rising emphasis on climate-smart agriculture, resource efficiency, and traceable food systems, governments, agritech providers, and global agribusinesses are accelerating investment in digital agriculture. As these technologies continue to advance and become more integrated, AI, IoT, and blockchain are expected to play a pivotal role in shaping the future of global agriculture.

Industrial Impact

AI, IoT, and blockchain are reshaping modern agriculture by turning it into a more data-driven, efficient, and industrialized system. AI enables predictive insights such as yield forecasting, pest detection, and optimized input use, helping farms improve productivity while reducing costs and waste. IoT connects sensors, machinery, and equipment across fields, livestock operations, and storage facilities, providing real-time visibility into soil health, weather conditions, irrigation, and asset performance. Blockchain adds a trusted digital layer by improving traceability, transparency, and accountability across the agricultural value chain, from farm inputs to end consumers, supporting food safety, sustainability claims, and faster settlements. Together, these technologies shift agriculture from manual, reactive practices to scalable, automated, and performance-driven operations aligned with modern industrial standards.

Market Segmentation:

Segmentation 1: by Application

  • Crop Production Optimization
  • Water and Nutrient Management
  • Smart Farm Monitoring and Automation
  • Livestock Management

Crop Production Optimization to Dominate the AI, IoT, and Blockchain Market in Modern Agriculture (by Application)

In the AI, IoT, and blockchain market in modern agriculture, crop production optimization is projected to remain the dominant application segment throughout 2025-2035. The segment is expected to grow from $8,795.5 million in 2025 to $51,733.6 million by 2035, registering a strong CAGR of 19.39%.

This growth is attributed to the increasing adoption of AI-driven crop modeling, precision input application, smart imaging, and sensor-integrated field monitoring, all of which enhance yield, reduce waste, and optimize resource use. Farmers and enterprises are rapidly integrating AI-powered decision tools, satellite analytics, and IoT sensor grids to monitor crop stress, automate input delivery, and achieve season-long productivity improvements.

Water and nutrient management is expected to be the fastest-growing segment, expanding from $4,575.1 million in 2025 to $32,858.1 million by 2035, with an impressive CAGR of 21.79%.

The surge is driven by rising pressure on water resources, the need for fertilizer optimization, and the integration of soil moisture sensors, electrochemical nutrient monitors, automated irrigation systems, and AI-based fertigation models. Smart irrigation IoT platforms and predictive analytics are being deployed widely to reduce operational costs, conserve water, and increase crop health consistency.

Smart farm monitoring and automation is projected to grow from $5,777.5 million in 2025 to $38,239.8 million by 2035, at a CAGR of 20.80%. Key drivers include the adoption of:

  • autonomous farm machinery
  • computer-vision-enabled robot platforms
  • drone-based field analytics
  • climate monitoring stations
  • connected farm management systems

These technologies allow farms to move toward "hands-off" operations, improve real-time monitoring, and reduce labor dependency.

Segmentation 2: by Product

  • Artificial Intelligence (AI)
  • Internet of Things
  • Blockchain Platform

Internet of Things (IoT) to Maintain Dominance in the AI, IoT, and Blockchain Market in Modern Agriculture (by Product)

According to the latest market estimates, the Internet of Things (IoT) segment is projected to remain the dominant product category in the AI, IoT, and blockchain market in modern agriculture through 2035. Valued at $21,659.5 million in 2025, the IoT segment is expected to reach $120,555.6 million by 2035, growing at a robust CAGR of 18.73%.

IoT's continued dominance is driven by its critical role in enabling connected and automated farming operations. Sensor networks, connectivity modules, and gateway devices form the backbone of smart agriculture by generating real-time data on soil conditions, crop health, climate parameters, machinery operations, and livestock behavior. As farms transition toward data-driven decision-making and automation, IoT platforms remain central to improving yield, reducing input usage, and optimizing resource management.

Within IoT, sensor devices, including optical sensors, electrochemical sensors, and location sensors, account for the largest share due to their widespread deployment in field monitoring, irrigation automation, and precision nutrient management. Increasing integration of sensor systems with cloud dashboards and mobile applications is further accelerating adoption across small, medium, and large farm operations.

Overall, IoT technologies will continue to anchor the digital farm ecosystem, supporting everything from real-time monitoring to predictive analytics, and ensuring its position as the leading product category in the market.

Segmentation 3: by Region

  • North America: U.S., Canada, and Mexico
  • Europe: Germany, France, U.K., Netherlands, Spain, and Rest-of-Europe
  • Asia-Pacific: China, Japan, India, Australia, and Rest-of-Asia-Pacific
  • Rest-of-the-World: South America and the Middle East and Africa

North America is expected to maintain its dominant position in the global AI, IoT, and blockchain market in modern agriculture, achieving the highest regional market value throughout the forecast period. The market is projected to grow from $8,515.2 million in 2025 to $47,084.9 million by 2035, registering a strong CAGR of 18.65%. This growth is driven by the rapid adoption of precision farming technologies, widespread use of IoT-enabled sensors and farm automation systems, and strong digital infrastructure supporting data-driven agriculture. The U.S. leads the region due to heavy investments in AI-driven crop analytics, autonomous machinery, smart irrigation, and digital farm management platforms.

The Asia-Pacific (APAC) region is projected to be the fastest-growing market, expanding from $5,829.0 million in 2025 to $45,067.9 million by 2035, at an impressive CAGR of 22.70%. This rapid acceleration is fueled by rising food demand, large-scale digital agriculture initiatives in China, India, Japan, South Korea, and Australia, and increasing adoption of IoT sensors, AI-powered crop intelligence platforms, and smart irrigation systems. APAC countries are prioritizing farm automation, climate-smart agriculture, and digital advisory tools to increase productivity and sustainability.

Europe remains a technologically advanced and mature market, rising from $6,602.6 million in 2025 to $42,678.0 million in 2035, with a CAGR of 20.52%. The region benefits from strong regulatory support for sustainable farming, high adoption of farm management software, greenhouse automation, robotics, and blockchain-based traceability platforms. Countries such as Germany, France, the U.K., and the Netherlands continue to lead in smart farming research, controlled-environment agriculture, and precision livestock management.

The Rest-of-the-World (RoW), comprising South America and the Middle East and Africa, is projected to grow from $3,354.5 million in 2025 to $19,715.6 million by 2035, at a solid CAGR of 19.38%. Growth is supported by increasing adoption of irrigation automation, crop monitoring tools, and digital advisory platforms, especially in water-scarce regions.

Demand: Drivers, Limitations, and Opportunities

Market Demand Drivers: Rising Need for Precision, Sustainability, and Data-Driven Farming

The AI, IoT, and blockchain market in modern agriculture has been experiencing robust demand growth as the global farming sector undergoes rapid digital transformation. Key factors driving market expansion include the rising need for precision agriculture, resource optimization, and climate-resilient farming practices.

One of the primary drivers is the growing adoption of IoT-enabled sensors, which provide real-time data on soil moisture, nutrient levels, crop health, and weather conditions. These insights allow farmers to optimize input usage, such as water, fertilizer, and pesticides, resulting in higher productivity and lower environmental impact. AI-powered analytics further enhance decision-making by enabling predictive modeling, yield forecasting, and early detection of crop diseases, thereby reducing economic losses and improving farm profitability.

Climate change and increasing water scarcity are also accelerating demand for advanced digital tools. Technologies such as smart irrigation systems, AI-guided water management, and automated greenhouse controls help farmers maintain production stability despite shifting environmental conditions. Simultaneously, rising global food demand is pushing growers to adopt automation and robotics to address labor shortages and improve field efficiency.

The supply chain side of agriculture is also a major contributor to demand. Blockchain platforms are increasingly being deployed to ensure traceability, food safety, and transparent farm-to-fork logistics, driven by tighter regulatory requirements and consumer expectations for verifiable food quality.

Together, these developments are making AI, IoT, and blockchain essential tools in modern agriculture, enabling farmers and agribusinesses to operate with greater precision, sustainability, and resilience.

Market Limitations: Data Gaps, High Costs, and Infrastructure Constraints

Despite strong adoption momentum, the AI, IoT, and blockchain market in modern agriculture faces several challenges that could hinder large-scale deployment.

A major limitation is the lack of digital infrastructure in rural regions, particularly in developing countries. Limited broadband connectivity, low smart-device penetration, and inconsistent power supply reduce the effectiveness of IoT sensors, connected equipment, and cloud-based data platforms.

Cost remains a key barrier. The upfront investment required for AI-enabled machinery, drones, IoT sensor networks, and data management platforms can be prohibitive for small and medium-sized farmers. Even when hardware costs decrease, ongoing expenses related to subscription platforms, data storage, and equipment maintenance can slow adoption.

Data fragmentation also poses challenges. Farm data is often collected using incompatible systems, multiple devices, and proprietary platforms, leading to interoperability issues and information silos. Many growers struggle with data literacy, limiting their ability to fully utilize analytics and decision-support tools.

Cybersecurity risks are another concern. As farms become more connected, the risk of data breaches, unauthorized access to equipment, and manipulation of supply chain records increases. This necessitates stronger safeguards and standards for agricultural data protection.

Finally, limited technical skills and a shortage of trained personnel reduce the pace at which digital solutions can be implemented and managed, especially in emerging markets.

Market Opportunities: Autonomous Farming, Climate-Smart Solutions, and Blockchain Traceability

Emerging technologies are creating significant opportunities for growth within the AI, IoT, and blockchain market in modern agriculture.

One of the strongest opportunities lies in autonomous and robotic farming systems, including self-driving tractors, drone spraying, automated harvesting equipment, and robotic weeders. These technologies help address labor shortages, improve efficiency, and support large-scale operations.

Climate-smart agriculture presents another major opportunity. Advanced analytics, machine learning models, and IoT-based weather monitoring can help farmers better manage extreme climate events, optimize resource use, and improve resilience. Solutions such as AI-driven crop disease prediction, real-time irrigation automation, and sensor-based greenhouse optimization are especially in demand.

Blockchain offers transformative potential for the agricultural supply chain. By enabling end-to-end transparency, from seed to shelf, it enhances food safety, prevents fraud, and strengthens consumer trust. Governments and global food companies are increasingly mandating digital traceability, creating substantial opportunities for blockchain platform providers.

Additionally, the integration of satellite imagery, drone imaging, and ground-based sensors is opening new markets for AI-powered crop intelligence platforms, which can serve growers, input companies, financial institutions, insurers, and food processors.

Overall, as digital ecosystems mature, the integration of AI, IoT, and blockchain will continue to create new value pools across the agricultural sector, from on-farm optimization to global supply chain digitization.

How can this report add value to an organization?

Product/Innovation Strategy: This report offers organizations a detailed understanding of how AI, IoT, and blockchain technologies are transforming modern agriculture. It highlights emerging innovations such as AI-driven crop intelligence, IoT-enabled sensing networks, autonomous farm machinery, digital twins, and blockchain-based traceability systems. These technologies are enabling real-time farm monitoring, predictive analytics, and resource-efficient operations. By mapping technological advancements, ranging from machine vision for crop health to distributed ledger systems for supply chain transparency, the report provides actionable insights for product development teams, R&D departments, and innovation leaders. Companies can use these insights to design next-generation precision farming tools, enhance interoperability across devices and platforms, and build scalable digital agriculture solutions aligned with evolving market needs.

Growth/Marketing Strategy: The AI, IoT, and blockchain market in modern agriculture offers robust growth potential across all major agricultural regions. This report outlines key strategies adopted by leading players, including mergers and acquisitions (e.g., CNH Industrial's acquisition of Raven), strategic partnerships (such as Deere & Company's automation collaborations), and the expansion of cloud-based farm management platforms. It also identifies growth hotspots such as smart irrigation, livestock automation, autonomous tractors, greenhouse digitalization, and blockchain-enabled supply chain systems. With farmers, cooperatives, input suppliers, and food companies increasingly adopting data-driven practices, organizations can leverage the report to refine their market positioning, tailor their go-to-market strategies, and enter high-potential segments using targeted product offerings and value-added services.

Competitive Strategy: The report provides a comprehensive competitive landscape of the digital agriculture ecosystem, profiling major players across equipment manufacturers, agtech startups, IoT sensor providers, AI analytics companies, and blockchain-based platforms. It examines strategic moves such as partnerships, technology collaborations, joint ventures, platform integrations, and product launches that shape competitive dynamics. Through competitive benchmarking, organizations can identify white-space opportunities, assess competitor capabilities, and evaluate emerging threats. As agriculture rapidly shifts toward automation, remote sensing, cloud analytics, and decentralized data systems, competition will intensify around innovation speed, interoperability, data ownership, and ecosystem integration. The insights in this report help organizations strengthen their long-term competitive positioning and capture a larger share of the evolving digital agriculture market.

Research Methodology

Factors for Data Prediction and Modelling

  • The base currency considered for the AI, IoT, and blockchain market in modern agriculture analysis is the US$. Currencies other than the US$ have been converted to the US$ for all statistical calculations, considering the average conversion rate for that particular year.
  • The currency conversion rate has been taken from the historical exchange rate of the Oanda website.
  • Nearly all the recent developments from January 2021 to March 2024 have been considered in this research study.
  • The information rendered in the report is a result of in-depth primary interviews, surveys, and secondary analysis.
  • Where relevant information was not available, proxy indicators and extrapolation were employed.
  • Any economic downturn in the future has not been taken into consideration for the market estimation and forecast.
  • Technologies currently used are expected to persist through the forecast with no major technological breakthroughs.

Market Estimation and Forecast

This research study involves the usage of extensive secondary sources, such as certified publications, articles from recognized authors, white papers, annual reports of companies, directories, and major databases, to collect useful and effective information for an extensive, technical, market-oriented, and commercial study of the AI, IoT, and blockchain market in modern agriculture

The market engineering process involves the calculation of the market statistics, market size estimation, market forecast, market crackdown, and data triangulation (the methodology for such quantitative data processes has been explained in further sections). The primary research study has been undertaken to gather information and validate the market numbers for segmentation types and industry trends of the key players in the market.

Primary Research

The primary sources involve industry experts from the AI, IoT, and blockchain market in modern agriculture and various stakeholders in the ecosystem. Respondents such as CEOs, vice presidents, marketing directors, and technology and innovation directors have been interviewed to obtain and verify both qualitative and quantitative aspects of this research study.

The key data points taken from primary sources include:

  • validation and triangulation of all the numbers and graphs
  • validation of report segmentations and key qualitative findings
  • understanding the competitive landscape
  • validation of the numbers of various markets for the market type
  • percentage split of individual markets for geographical analysis

Secondary Research

This research study involves the usage of extensive secondary research, directories, company websites, and annual reports. It also makes use of databases, such as Hoovers, Bloomberg, Businessweek, and Factiva, to collect useful and effective information for an extensive, technical, market-oriented, and commercial study of the global market. In addition to the data sources, the study has been undertaken with the help of other data sources and websites, such as the Census Bureau, OICA, and ACEA.

Secondary research has been done to obtain crucial information about the industry's value chain, revenue models, the market's monetary chain, the total pool of key players, and the current and potential use cases and applications.

The key data points taken from secondary research include:

  • segmentations and percentage shares
  • data for market value
  • key industry trends of the top players in the market
  • qualitative insights into various aspects of the market, key trends, and emerging areas of innovation
  • quantitative data for mathematical and statistical calculations

Data Triangulation

This research study involves the usage of extensive secondary sources, such as certified publications, articles from recognized authors, white papers, annual reports of companies, directories, and major databases, to collect useful and effective information for an extensive, technical, market-oriented, and commercial study of the AI, IoT, and blockchain market in modern agriculture.

The process of market engineering involves the calculation of the market statistics, market size estimation, market forecast, market crackdown, and data triangulation (the methodology for such quantitative data processes has been explained in further sections). The primary research study has been undertaken to gather information and validate the market numbers for segmentation types and industry trends of the key players in the market.

Key Market Players and Competition Synopsis

The companies profiled in the AI, IoT, and blockchain market in modern agriculture have been selected based on expert inputs regarding their technological capabilities, solution breadth, global footprint, and market penetration across digital agriculture value chains.

Leading Players in the AI, IoT, and Blockchain Market in Modern Agriculture

  • Deere & Company
  • Robert Bosch GmbH
  • CNH Industrial N.V
  • Trimble Inc.
  • Signify Holding
  • Taranis
  • CropIn Technology Solutions
  • Plantix (PEAT GmbH)
  • Ceres Imaging
  • Climate LLC (The Climate Corporation)
  • AGRIVI
  • Regen Network Development
  • SZ DJI Technology Co., Ltd. (DJI)
  • OSRAM GmbH (ams OSRAM)
  • Granular Inc.

Companies that are not a part of the aforementioned pool have been well represented across different sections of the AI, IoT, and blockchain market in modern agriculture report (wherever applicable).

Table of Contents

Executive Summary

Scope and Definition

1 Markets: Industry Outlook

  • 1.1 Trends: Current and Future Impact Assessment
    • 1.1.1 AI-Driven Crop Analytics and Decision Support
    • 1.1.2 IoT-Enabled Precision Irrigation and Nutrient Management
    • 1.1.3 Smart Farm Automation with Robotics and Drones
  • 1.2 Regulatory Landscape
  • 1.3 Research and Development Review
    • 1.3.1 Patent Filing Trend (by Country and Company)
      • 1.3.1.1 Patent Filing Trend (by Country)
      • 1.3.1.2 Patent Filing Trend (by Company)
  • 1.4 Start-Up Landscape
  • 1.5 Stakeholder Analysis
    • 1.5.1 Use Case
      • 1.5.1.1 Precision Farming
        • 1.5.1.1.1 Case Study 1 : - Precision Mapping Boosts ROI in U.S. Row Crop
        • 1.5.1.1.2 Case Study 2 : - Site-Specific Management Raises Yields in India
      • 1.5.1.2 Smart Irrigation
        • 1.5.1.2.1 Case Study 1 : - IoT-Enabled Drip Irrigation Lifts Yields (India)
        • 1.5.1.2.2 Case Study 2 : - Automated Orchard Irrigation Saves Water (Europe)
      • 1.5.1.3 Livestock Tracking
        • 1.5.1.3.1 Case Study 1 : - IoT Ranch Management Reduces Losses and Costs
        • 1.5.1.3.2 Case Study 2 : - Blockchain Traceability Yields Premium Prices for Beef
      • 1.5.1.4 Carbon Trading and Sustainability
        • 1.5.1.4.1 Case Study 1 : - Carbon Farming Pioneers Boost Income (U.S.)
        • 1.5.1.4.2 Case Study 2 : - Soil Carbon Credits Reward Farmers in South Africa
    • 1.5.2 End User and Buying Criteria
  • 1.6 Impact Analysis for Key Global Events
  • 1.7 Market Dynamics Overview
  • 1.8 Market Dynamics
    • 1.8.1 Market Drivers
      • 1.8.1.1 Productivity Gains and Operational Efficiency
      • 1.8.1.2 Climate Resilience and Sustainability Requirements
      • 1.8.1.3 Food Security and Rising Global Demand
    • 1.8.2 Market Challenges
      • 1.8.2.1 High Upfront CapEx and Uncertain ROI for Smaller Producers
      • 1.8.2.2 Rural Connectivity and Data Interoperability Limitations
    • 1.8.3 Market Opportunities
      • 1.8.3.1 Carbon Markets and Climate Services
      • 1.8.3.2 Bridging Inequality in Digital Agriculture

2 AI, IoT, and Blockchain Market in Modern Agriculture (by Application)

  • 2.1 Application Summary
  • 2.2 AI, IoT, and Blockchain Market in Modern Agriculture (by Application)
    • 2.2.1 Crop Production Optimization
    • 2.2.2 Water and Nutrient Management
    • 2.2.3 Smart Farm Monitoring and Automation
    • 2.2.4 Livestock Management

3 AI, IoT, and Blockchain Market in Modern Agriculture (by Products)

  • 3.1 Product Summary
  • 3.2 AI, IoT, and Blockchain Market in Modern Agriculture (by Product)
    • 3.2.1 Artificial Intelligence (AI)
      • 3.2.1.1 AI Software Platform
      • 3.2.1.2 AI-Powered Imaging Platforms
    • 3.2.2 Internet of Things
      • 3.2.2.1 Sensor Devices
        • 3.2.2.1.1 Location Sensors
        • 3.2.2.1.2 Electrochemical Sensors
        • 3.2.2.1.3 Optical Sensors
        • 3.2.2.1.4 Others
      • 3.2.2.2 Connectivity and Gateways
      • 3.2.2.3 IOT Platforms and Dashboards
    • 3.2.3 Blockchain Platform

4 AI, IoT, and Blockchain Market in Modern Agriculture (by Region)

  • 4.1 AI, IoT, and Blockchain Market in Modern Agriculture (by Region)
  • 4.2 North America
    • 4.2.1 Regional Overview
    • 4.2.2 Driving Factors for Market Growth
    • 4.2.3 Factors Challenging the Market
    • 4.2.4 Application
    • 4.2.5 Product
    • 4.2.6 U.S.
      • 4.2.6.1 Market (by Application)
      • 4.2.6.2 Market (by Product)
    • 4.2.7 Canada
      • 4.2.7.1 Market (by Application)
      • 4.2.7.2 Market (by Product)
    • 4.2.8 Mexico
      • 4.2.8.1 Market (by Application)
      • 4.2.8.2 Market (by Product)
  • 4.3 Europe
    • 4.3.1 Regional Overview
    • 4.3.2 Driving Factors for Market Growth
    • 4.3.3 Factors Challenging the Market
    • 4.3.4 Application
    • 4.3.5 Product
    • 4.3.6 Germany
      • 4.3.6.1 Market (by Application)
      • 4.3.6.2 Market (by Product)
    • 4.3.7 France
      • 4.3.7.1 Market (by Application)
      • 4.3.7.2 Market (by Product)
    • 4.3.8 U.K.
      • 4.3.8.1 Market (by Application)
      • 4.3.8.2 Market (by Product)
    • 4.3.9 Netherlands
      • 4.3.9.1 Market (by Application)
      • 4.3.9.2 Market (by Product)
    • 4.3.10 Spain
      • 4.3.10.1 Market (by Application)
      • 4.3.10.2 Market (by Product)
    • 4.3.11 Rest-of-Europe
      • 4.3.11.1 Market (by Application)
      • 4.3.11.2 Market (by Product)
  • 4.4 Asia-Pacific
    • 4.4.1 Regional Overview
    • 4.4.2 Driving Factors for Market Growth
    • 4.4.3 Factors Challenging the Market
    • 4.4.4 Application
    • 4.4.5 Product
    • 4.4.6 China
      • 4.4.6.1 Market (by Application)
      • 4.4.6.2 Market by Product
    • 4.4.7 Japan
      • 4.4.7.1 Market (by Application)
      • 4.4.7.2 Market (by Product)
    • 4.4.8 India
      • 4.4.8.1 Market (by Application)
      • 4.4.8.2 Market (by Product)
    • 4.4.9 Australia
      • 4.4.9.1 Market (by Application)
      • 4.4.9.2 Market (by Product)
    • 4.4.10 Rest-of-Asia-Pacific
      • 4.4.10.1 Market (by Application)
      • 4.4.10.2 Market (by Product)
  • 4.5 Rest-of-the-World
    • 4.5.1 Regional Overview
    • 4.5.2 Driving Factors for Market Growth
    • 4.5.3 Factors Challenging the Market
    • 4.5.4 Application
    • 4.5.5 Product
    • 4.5.6 Middle East and Africa
      • 4.5.6.1 Market (by Application)
      • 4.5.6.2 Market (by Product)
    • 4.5.7 South America
      • 4.5.7.1 Market (by Application)
      • 4.5.7.2 Market (by Product)

5 Company Profiles

  • 5.1 Geographic Assessment
  • 5.2 Next Frontiers
  • 5.3 Company Profile
    • 5.3.1 Deere and Company
      • 5.3.1.1 Overview
      • 5.3.1.2 Top Products/Product Portfolio
      • 5.3.1.3 Top Competitors
      • 5.3.1.4 Target Customers
      • 5.3.1.5 Key Personnel
      • 5.3.1.6 Analyst View
    • 5.3.2 Robert Bosch GmbH
      • 5.3.2.1 Overview
      • 5.3.2.2 Top Products/Product Portfolio
      • 5.3.2.3 Top Competitors
      • 5.3.2.4 Target Customers
      • 5.3.2.5 Key Personnel
      • 5.3.2.6 Analyst View
    • 5.3.3 CNH Industrial N.V.
      • 5.3.3.1 Overview
      • 5.3.3.2 Top Products/Product Portfolio
      • 5.3.3.3 Top Competitors
      • 5.3.3.4 Target Customers
      • 5.3.3.5 Key Personnel
      • 5.3.3.6 Analyst View
    • 5.3.4 Trimble Inc.
      • 5.3.4.1 Overview
      • 5.3.4.2 Top Products/Product Portfolio
      • 5.3.4.3 Top Competitors
      • 5.3.4.4 Target Customers
      • 5.3.4.5 Key Personnel
      • 5.3.4.6 Analyst View
    • 5.3.5 Signify Holding
      • 5.3.5.1 Overview
      • 5.3.5.2 Overview
      • 5.3.5.3 Top Products/Product Portfolio
      • 5.3.5.4 Top Competitors
      • 5.3.5.5 Target Customers
      • 5.3.5.6 Key Personnel
      • 5.3.5.7 Analyst View
    • 5.3.6 Taranis
      • 5.3.6.1 Overview
      • 5.3.6.2 Top Products/Product Portfolio
      • 5.3.6.3 Top Competitors
      • 5.3.6.4 Target Customers
      • 5.3.6.5 Key Personnel
      • 5.3.6.6 Analyst View
    • 5.3.7 CropIn Technology Solutions
      • 5.3.7.1 Overview
      • 5.3.7.2 Top Products/Product Portfolio
      • 5.3.7.3 Top Competitors
      • 5.3.7.4 Target Customers
      • 5.3.7.5 Key Personnel
      • 5.3.7.6 Analyst View
    • 5.3.8 Plantix
      • 5.3.8.1 Overview
      • 5.3.8.2 Top Products/Product Portfolio
      • 5.3.8.3 Top Competitors
      • 5.3.8.4 Target Customers
      • 5.3.8.5 Key Personnel
      • 5.3.8.6 Analyst View
    • 5.3.9 Ceres Imaging
      • 5.3.9.1 Overview
      • 5.3.9.2 Top Products/Product Portfolio
      • 5.3.9.3 Top Competitors
      • 5.3.9.4 Target Customers
      • 5.3.9.5 Key Personnel
      • 5.3.9.6 Analyst View
    • 5.3.10 Climate LLC
      • 5.3.10.1 Overview
      • 5.3.10.2 Top Products/Product Portfolio
      • 5.3.10.3 Top Competitors
      • 5.3.10.4 Target Customers
      • 5.3.10.5 Key Personnel
      • 5.3.10.6 Analyst View
    • 5.3.11 AGRIVI
      • 5.3.11.1 Overview
      • 5.3.11.2 Top Products/Product Portfolio
      • 5.3.11.3 Top Competitors
      • 5.3.11.4 Target Customers
      • 5.3.11.5 Key Personnel
      • 5.3.11.6 Analyst View
    • 5.3.12 Regen Network Development
      • 5.3.12.1 Overview
      • 5.3.12.2 Top Products/Product Portfolio
      • 5.3.12.3 Top Competitors
      • 5.3.12.4 Target Customers
      • 5.3.12.5 Key Personnel
      • 5.3.12.6 Analyst View
    • 5.3.13 SZ DJI Technology Co., Ltd.
      • 5.3.13.1 Overview
      • 5.3.13.2 Top Products/Product Portfolio
      • 5.3.13.3 Top Competitors
      • 5.3.13.4 Target Customers
      • 5.3.13.5 Key Personnel
      • 5.3.13.6 Analyst View
    • 5.3.14 OSRAM GmbH
      • 5.3.14.1 Overview
      • 5.3.14.2 Top Products/Product Portfolio
      • 5.3.14.3 Top Competitors
      • 5.3.14.4 Target Customers
      • 5.3.14.5 Key Personnel
      • 5.3.14.6 Analyst View
    • 5.3.15 Granular Inc.
      • 5.3.15.1 Overview
      • 5.3.15.2 Top Products/Product Portfolio
      • 5.3.15.3 Top Competitors
      • 5.3.15.4 Target Customers
      • 5.3.15.5 Key Personnel
      • 5.3.15.6 Analyst View

6 Research Methodology

  • 6.1 Data Sources
    • 6.1.1 Primary Data Sources
    • 6.1.2 Secondary Data Sources
    • 6.1.3 Data Triangulation
  • 6.2 Market Estimation and Forecast

List of Figures

  • Figure 1: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Scenario), $Million, 2025, 2030, and 2035
  • Figure 2: Global AI, IoT, and Blockchain Market in Modern Agriculture, 2025 and 2035
  • Figure 3: Global Market Snapshot, 2024
  • Figure 4: Global AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024 and 2035
  • Figure 5: AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024, 2030, and 2035
  • Figure 6: AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024, 2030, and 2035
  • Figure 7: AI, IoT, and Blockchain Market in Modern Agriculture Segmentation
  • Figure 8: Patent Analysis (by Country), January 2022-October 2025
  • Figure 9: Patent Analysis (by Company), January 2022-October 2025
  • Figure 10: How Data Gaps Reinforce AI Bias in Agriculture
  • Figure 11: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024, 2030, and 2035
  • Figure 12: Global AI, IoT, and Blockchain Market in Modern Agriculture (Crop Production Optimization), $Million, 2024-2035
  • Figure 13: Global AI, IoT, and Blockchain Market in Modern Agriculture (Water and Nutrient Management), $Million, 2024-2035
  • Figure 14: Global AI, IoT, and Blockchain Market in Modern Agriculture (Smart Farm Monitoring and Automation), $Million, 2024-2035
  • Figure 15: Global AI, IoT, and Blockchain Market in Modern Agriculture (Livestock Management), $Million, 2024-2035
  • Figure 16: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024, 2030, and 2035
  • Figure 17: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Artificial Intelligence (AI)), $Million, 2024-2035
  • Figure 18: Global AI, IoT, and Blockchain Market in Modern Agriculture (AI Software Platform), $Million, 2024-2035
  • Figure 19: Global AI, IoT, and Blockchain Market in Modern Agriculture (AI-Powered Imaging Platforms), $Million, 2024-2035
  • Figure 20: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Internet of Things (IoT)), $Million, 2024-2035
  • Figure 21: Global AI, IoT, and Blockchain Market in Modern Agriculture (Sensor Devices), $Million, 2024-2035
  • Figure 22: Global AI, IoT, and Blockchain Market in Modern Agriculture (Location Sensors), $Million, 2024-2035
  • Figure 23: Global AI, IoT, and Blockchain Market in Modern Agriculture (Electrochemical Sensors), $Million, 2024-2035
  • Figure 24: Global AI, IoT, and Blockchain Market in Modern Agriculture (Optical Sensors), $Million, 2024-2035
  • Figure 25: Global AI, IoT, and Blockchain Market in Modern Agriculture (Others), $Million, 2024-2035
  • Figure 26: Global AI, IoT, and Blockchain Market in Modern Agriculture (Connectivity and Gateways), $Million, 2024-2035
  • Figure 27: Global AI, IoT, and Blockchain Market in Modern Agriculture (IOT Platforms and Dashboards), $Million, 2024-2035
  • Figure 28: Global AI, IoT, and Blockchain Market in Modern Agriculture (Blockchain Platform), $Million, 2024-2035
  • Figure 29: U.S. AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 30: Canada AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 31: Mexico AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 32: Germany AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 33: France AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 34: U.K. AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 35: Netherlands AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 36: Spain AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 37: Rest-of-Europe AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 38: China AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 39: Japan AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 40: India AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 41: Australia AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 42: Rest-of-Asia-Pacific AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 43: Middle East and Africa AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 44: South America AI, IoT, and Blockchain Market in Modern Agriculture, $Million, 2024-2035
  • Figure 45: Data Triangulation
  • Figure 46: Top-Down and Bottom-Up Approach
  • Figure 47: Assumptions and Limitations

List of Tables

  • Table 1: Market Snapshot
  • Table 2: Trends: Current and Future Impact Assessment
  • Table 3: End User Segments and Buying Criteria in the Digital Farm Revolution
  • Table 4: Impact of Global Events on the Digital Farm Revolution Market
  • Table 5: Drivers, Challenges, and Opportunities, 2024-2035
  • Table 6: Barriers to Digital Agriculture Adoption for Smallholders
  • Table 7: U.S.' Farms and Ranches Segmentation
  • Table 8: Strategies Bridging Digital Divide in Agriculture
  • Table 9: Key Use Cases of AI Software Platforms in Agriculture
  • Table 10: Adoption Trends of AI Software Platforms (by Farm Type)
  • Table 11: Key Use Cases of AI-Powered Imaging Platforms in Agriculture
  • Table 12: Adoption Trends of AI-Powered Imaging Platforms (by Region and Farm Type)
  • Table 13: Key Use Cases of IoT in Agriculture
  • Table 14: Connectivity Technologies in Agriculture
  • Table 15: Recommended Connectivity Options (by Farm Type and Geography)
  • Table 16: Drivers and Challenges of IoT Connectivity Adoption in Agriculture
  • Table 17: Key Use Cases of IoT Dashboards in Agriculture
  • Table 18: Adoption Drivers and Barriers for IoT Platforms in Agriculture
  • Table 19: Core Functions of Blockchain Platform in Agriculture
  • Table 20: Blockchain Use Cases in Crop Supply Chains, Livestock, and On-Farm Operations
  • Table 21: Adoption Drivers and Barriers for Blockchain in Agriculture
  • Table 22: Global AI, IoT, and Blockchain Market in Modern Agriculture (by Region), $Million, 2024-2035
  • Table 23: North America AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 24: North America AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 25: U.S. AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 26: U.S. AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 27: Canada AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 28: Canada. AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 29: Mexico AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 30: Mexico AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 31: Europe AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 32: Europe AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 33: Germany AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 34: Germany AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 35: France AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 36: France AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 37: U.K. AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 38: U.K. AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 39: Netherlands. AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 40: Netherlands AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 41: Spain AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 42: Spain AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 43: Rest-of-Europe AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 44: Rest-of-Europe AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 45: Asia-Pacific AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 46: Asia-Pacific AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 47: China AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 48: China AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 49: Japan AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 50: Japan AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 51: India AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 52: India AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 53: Australia AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 54: Australia AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 55: Rest-of-Asia-Pacific AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 56: Rest-of-Asia-Pacific AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 57: Rest-of-the-World AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 58: Rest-of-the-World AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 59: Middle East and Africa AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 60: Middle East and Africa AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035
  • Table 61: South America AI, IoT, and Blockchain Market in Modern Agriculture (by Application), $Million, 2024-2035
  • Table 62: South America AI, IoT, and Blockchain Market in Modern Agriculture (by Product), $Million, 2024-2035