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现代农业中的人工智慧、物联网和区块链市场——全球和区域分析：按应用、产品和国家划分——分析和预测（2025-2035 年）
市场调查报告书
商品编码
1982255

现代农业中的人工智慧、物联网和区块链市场——全球和区域分析：按应用、产品和国家划分——分析和预测（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个工作天内

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现代农业中人工智慧、物联网和区块链的市场规模预计将从 2025 年的 243.13 亿美元成长到 2035 年的 1,545.465 亿美元，复合年增长率为 20.32%。

这一增长得益于整个农业价值链的快速数位转型，包括智慧感测器、物联网连接设备、人工智慧分析和基于区块链的溯源平台的普及。提高产量、降低营运成本、实现气候友善农业以及增强供应链透明度的压力日益增大，正在加速全球农场采用先进的数位化工具。

关键市场统计数据
预测期 2025-2035
2025年市场规模 243亿美元
2035 年预测 1545.4亿美元
复合年增长率 20.32%

人工智慧驱动的农业模型、自主农机、无人机和连网农业设备正在重塑营运效率，而物联网感测器、农场管理系统和卫星监测则助力即时决策。随着食品公司和监管机构将可追溯性和永续性检验置于优先地位，区块链的应用正在加速。儘管整体发展势头强劲，但市场仍面临诸多挑战，例如数据互通性、农民的数位素养、高昂的初始成本以及农村地区通讯基础设施的限制。随着设备製造商、农业科技公司和政府加大投资，预计到2035年，该产业将保持强劲成长。

现代农业中的人工智慧、物联网和区块链市场简介

根据BIS Research的研究，人工智慧、物联网和区块链在现代农业领域的应用是下一代粮食生产系统的核心驱动力，引领农业从传统模式转型为数据驱动、自动化和气候友善农业。数位技术正发展成为功能强大的工具，支援即时作物资讯、自主田间作业、精准投入管理和透明供应链。

人工智慧模型和机器视觉系统能够更早检测病虫害和营养缺乏，而物联网感测器则持续监测土壤、天气和设备性能。卫星影像、无人机和云分析的整合进一步提高了决策的准确性。区块链平台支援端到端的可追溯性，确保符合食品安全、品质保证和永续性标准。

随着全球农业面临日益严峻的压力，包括气候变迁、劳动力短缺、粮食安全问题以及永续性义务，数位化解决方案为农民和农业相关企业提供了战略优势。在对智慧农业技术投资增加、政府推动数位农业发展以及全球透过技术主导提高农业生产力的努力的共同推动下，预计未来十年该市场将显着增长。

市场概览

在对即时田间资讯、自动化作业和资料优化决策日益增长的需求驱动下，人工智慧、物联网和区块链市场正在现代农业领域迅速崛起，成为该领域的基石。随着粮食系统日益复杂化和气候风险加剧，从智慧感测器和机器人到先进分析平台等一系列数位农业技术，将使农民能够以前所未有的精准度管理作物、牲畜和资源。

人工智慧增强了产量、天气和投入需求的预测模型，而物联网设备则将农业机械、环境感测器和牲畜监测系统连接成一个整合的资料生态系统。区块链透过检验生产实践、认证永续性和预防欺诈，提高了整个供应链的可靠性和透明度。

随着人们对气候友善农业、资源效率和可追溯食品体系的关注度日益提高，世界各国政府、农业技术公司和农业相关企业正加速对数位农业的投资。随着这些技术的不断发展和整合，人工智慧、物联网和区块链有望在塑造全球农业的未来中发挥关键作用。

对产业的影响

人工智慧、物联网和区块链正在将现代农业转型为一个更数据驱动、高效和工业化的系统。人工智慧能够提供预测性洞察，例如产量预测、病虫害检测和投入优化，帮助农场提高生产力，同时降低成本和减少废弃物。物联网将田间、畜舍和仓储设施中的感测器、机械和设备连接起来，提供土壤状况、天气、灌溉和资产性能的即时可见性。区块链透过提高从农业投入到最终消费者的整个价值链的可追溯性、透明度和课责，构建了一个值得信赖的数位基础，从而支持食品安全、永续性声明和更快捷的支付。这些技术共同推动农业从人工、被动的实践转向符合现代工业标准的扩充性、自动化和绩效驱动型运作。

市场区隔:

细分 1：按应用

  • 作物生产优化
  • 水和养分管理
  • 智慧农业的监测与自动化
  • 畜牧管理

在现代农业的人工智慧、物联网和区块链市场中，作物生产优化预计将成为（按应用领域分類的）主导关注点。

在现代农业的人工智慧、物联网和区块链市场中，作物生产优化预计将在 2025 年至 2035 年间继续成为主要应用领域。该领域预计将从 2025 年的 87.955 亿美元成长到 2035 年的 517.336 亿美元，复合年增长率高达 19.39%。

这一增长得益于人工智慧驱动的作物建模、精准施肥、智慧成像和感测器整合式田间监测等技术的日益普及。所有这些都有助于提高产量、减少废弃物并优化资源利用。农民和企业正在迅速采用人工智慧驱动的决策工具、卫星分析和物联网感测器网路来监测作物胁迫、实现养分自动供给并提高整个生长季的生产力。

水和营养管理预计将成为成长最快的领域，从 2025 年的 45.751 亿美元成长到 2035 年的 328.581 亿美元，复合年增长率高达 21.79%。

这种快速增长是由水资源压力日益增大、肥料优化需求增加以及土壤湿度感测器、电化学养分监测器、自动化灌溉系统和基于人工智慧的施肥灌溉模型等技术的融合应用所驱动的。智慧灌溉物联网平台和预测分析技术正被广泛采用，以降低营运成本、节约用水并保障作物健康。

预计到2035年，智慧农业监测与自动化市场规模将从2025年的57.775亿美元成长至382.398亿美元，复合年增长率（CAGR）为20.80%。主要驱动因素包括以下应用：

  • 自主农业机械
  • 配备电脑视觉的机器人平台
  • 利用无人机进行实地分析
  • 气候观测站
  • 互联农场管理系统

这些技术使农场能够自主运营，提高即时监控能力，并减少对人力的依赖。

细分2：按产品

  • 人工智慧（AI）
  • 物联网
  • 区块链平台

在现代农业的人工智慧、物联网和区块链市场中，物联网 (IoT) 预计将继续保持主导地位（按产品划分）。

根据最新的市场估算和预测，物联网 (IoT) 领域预计将在 2035 年之前继续保持其在现代农业人工智慧、物联网和区块链市场中的领先产品类型。物联网领域在 2025 年的价值将达到 216.595 亿美元，预计到 2035 年将达到 1,205.556 亿美元，复合年增长率 (CAGR) 为 18.73%，实现了强劲增长。

物联网凭藉其在实现互联互通和自动化农业营运中的关键作用，持续保持主导地位。感测器网路、连接模组和网关设备透过产生土壤状况、作物生长、气候参数、农业机械运作和牲畜行为等即时数据，构成了智慧农业的基础。随着农场向数据驱动决策和自动化转型，物联网平台在提高产量、减少投入和优化资源管理方面仍发挥核心作用。

在物联网领域，光学感测器、电化学感测器和定位感测器等感测器设备占据了最大的市场份额，这得益于它们在田间监测、自动灌溉和精准养分管理等领域的广泛应用。随着感测器系统与云端控制面板和行动应用程式的整合度不断提高，其在小规模、中型和大型农业生产中的应用正在加速。

总体而言，物联网技术将继续成为数位农业生态系统的基础，支援从即时监控到预测分析的一切，并巩固其作为市场主要产品类型的地位。

细分3：按地区

  • 北美洲：美国、加拿大、墨西哥
  • 欧洲：德国、法国、英国、荷兰、西班牙等
  • 亚太地区：中国、日本、印度、澳洲及其他地区
  • 其他地区：南美洲、中东和非洲

北美在全球现代农业人工智慧、物联网和区块链市场中保持主导地位，预计在预测期内将保持最高的区域市场规模。市场规模预计将从2025年的85.152亿美元成长到2035年的470.849亿美元，复合年增长率高达18.65%。这一成长主要得益于精密农业技术的快速普及、物联网感测器和农业自动化系统的广泛应用，以及支撑数据驱动型农业的强大数位基础设施。美国在人工智慧作物分析、自主农机、智慧灌溉和数位化农场管理平台等领域投入大量资金，引领该地区的发展。

亚太地区预计将成为成长最快的市场，从2025年的58.29亿美元成长到2035年的450.679亿美元，复合年增长率高达22.70%。这一快速成长主要得益于不断增长的粮食需求、中国、印度、日本、韩国和澳洲等国大规模推进的数位化农业倡议，以及物联网感测器、人工智慧驱动的作物智慧平台和智慧灌溉系统的广泛应用。亚太各国正优先发展农业自动化、气候智慧型农业和数位化咨询工具，以提高生产力和永续性。

欧洲仍然是一个技术先进且成熟的市场，预计将从2025年的66.26亿美元增长到2035年的426.78亿美元，复合年增长率达20.52%。该地区受益于对永续农业的强大监管支持，以及农场管理软体、温室自动化、机器人技术和基于区块链的溯源平台的高普及率。德国、法国、英国和荷兰等国在智慧农业研究、可控环境农业和精准畜牧管理方面持续发挥主导作用。

该区域其他地区，包括南美洲、中东和非洲，预计将从2025年的33.545亿美元增长到2035年的197.156亿美元，复合年增长率高达19.38%。这一增长主要得益于自动化灌溉、作物监测工具和数位咨询平台的日益普及，尤其是在缺水地区。

需求：驱动因素、限制因素与机会

市场需求：对精密农业、永续性和数据驱动型农业的需求不断增长。

随着全球农业领域快速推动数位转型，现代农业中的人工智慧、物联网和区块链市场正经历强劲的需求成长。推动市场扩张的关键因素包括对精密农业、资源优化和气候适应耕作方式日益增长的需求。

推动农业发展的关键因素之一是物联网感测器的日益普及，这些感测器能够提供土壤湿度、养分含量、作物健康状况和天气状况的即时数据。这些资讯使农民能够优化水、肥料和农药等投入的使用，从而提高产量并减少对环境的影响。人工智慧驱动的分析技术能够实现预测建模、产量预测和作物病害的早期检测，进一步增强决策能力，减少经济损失，并提高农场盈利。

气候变迁和日益严重的水资源短缺也加速了对先进数位工具的需求。智慧灌溉系统、人工智慧驱动的水资源管理和温室自动化控制等技术，能够帮助农民在不断变化的环境条件下维持生产稳定。同时，不断增长的全球粮食需求也迫使生产商采用自动化和机器人技术，以应对劳动力短缺并提高田间作业效率。

农业供应链也是需求的主要驱动力。在日益严格的监管要求和消费者对检验食品品质的期望的推动下，区块链平台正被越来越多地用于确保从农场到餐桌的可追溯性、食品安全和透明物流。

这些技术的进步，结合起来，使人工智慧、物联网和区块链成为现代农业中必不可少的工具，使农民和农业相关企业能够以更高的精准度、永续性和韧性进行运作。

市场限制因素：缺乏数据、高成本、基础设施有限。

儘管人工智慧、物联网和区块链在现代农业领域的应用十分广泛，但这些市场仍面临一些挑战，可能会阻碍大规模部署。

限制因素之一是农村地区，特别是开发中国家，缺乏数位基础设施。宽频连线有限、智慧型装置普及率低以及电力供应不稳定，都降低了物联网感测器、连网装置和云端资料平台的效能。

成本仍然是一大障碍。人工智慧驱动的机械、无人机、物联网感测器网路和资料管理平台所需的初始投资对于中小农户来说可能负担过重。即使硬体成本下降，订阅平台、资料储存和设备维护等相关的持续成本也会阻碍技术的普及。

资料碎片化也是一大挑战。农业数据通常使用不相容的系统、多种设备和专有平台进行收集，导致互通性问题和资讯孤岛。许多生产者缺乏数据素养，限制了他们充分利用分析和决策支援工具的能力。

网路安全风险也令人担忧。随着农场网路化程度的提高，资料外洩、设备未授权存取以及供应链记录被篡改的风险也在增加。因此，需要更强有力的安全措施和标准来保护农业资料。

最后，技术技能和熟练人员的缺乏正在减缓数位解决方案的采用和管理速度，尤其是在新兴市场。

市场机会：自主农业、气候变迁因应解决方案与基于区块链的可追溯性

新兴技术正在为现代农业中的人工智慧、物联网和区块链市场创造巨大的成长机会。

最具发展前景的机会之一在于自主和机器人农业系统，包括自动驾驶拖拉机、无人机喷洒器、自动收割机和除草机器人。这些技术有助于解决劳动力短缺问题，提高效率，并支持大规模农业生产。

气候智能型农业也蕴藏着巨大的机会。先进的分析技术、机器学习模型和基于物联网的气象监测能够帮助农民更好地应对极端天气事件，优化资源利用，并增强抵御能力。人工智慧驱动的作物病害预测、即时自动灌溉和基于感测器的温室环境优化等解决方案尤其受到青睐。

区块链具有变革农业供应链的潜力。它能够实现从种子到商店的全程透明化，从而提升食品安全、预防诈欺并增强消费者信任。随着各国政府和全球食品公司日益重视数位化溯源，区块链平台供应商正迎来庞大的商机。

此外，卫星影像、无人机影像和地面感测器的整合正在为人工智慧驱动的作物智慧平台开闢新的市场。这些平台可以为生产者、农产品供应商、金融机构、保险公司、食品加工商等提供服务。

总体而言，随着数位生态系统的成熟，人工智慧、物联网和区块链的整合将继续为整个农业领域创造新的价值，从农场优化到全球价值链的数位化。

这份报告将为组织带来什么价值？

产品与创新策略：本报告深入剖析了人工智慧、物联网和区块链技术如何改变现代农业，为企业提供详尽的洞察。报告重点在于人工智慧驱动的作物智慧、物联网赋能的感测网路、自主农业机械、数位双胞胎以及基于区块链的溯源系统等新兴创新技术。这些技术能够实现农场即时监测、预测分析和资源高效利用。报告涵盖了从用于了解作物健康状况的机器视觉到用于提升供应链透明度的分散式帐本系统等一系列技术进步，为产品开发团队、研发部门和创新领导者提供切实可行的洞察。企业可以利用这些洞察来设计下一代精密农业工具，增强设备和平台之间的互通性，并建立可扩展的数位化农业解决方案，以满足不断变化的市场需求。

成长与行销策略：人工智慧、物联网和区块链在现代农业领域拥有强劲的成长潜力，遍及所有主要农业区。本报告概述了领先主要企业采取的关键策略，包括併购（例如，凯斯纽荷兰工业集团收购Raven）、策略联盟（例如，迪尔公司在自动化领域的合作）以及云端农场管理平台的扩展。报告还指出了智慧灌溉、畜牧自动化、自动驾驶拖拉机、温室数位化和区块链驱动的价值链系统等关键成长领域。随着农民、合作社、供应商和食品公司日益采用数据驱动的实践，企业可以利用本报告来优化市场定位、改善打入市场策略，并透过有针对性的产品和附加价值服务进入高潜力细分市场。

竞争策略：本报告全面分析了数位农业生态系统的竞争格局，重点关注设备製造商、农业科技Start-Ups、物联网感测器供应商、人工智慧分析公司和区块链平台等关键参与者。报告深入检验了影响竞争动态的策略性倡议，例如伙伴关係、技术合作、合资企业、平台整合和产品发布。透过竞争标竿分析，企业可以辨识尚未开发的机会，评估竞争对手的能力，并分析新兴威胁。随着农业快速向自动化、遥感探测、云端分析和分散式资料系统转型，创新速度、互通性、资料所有权和生态系统整合等方面的竞争将日益激烈。本报告的洞见将有助于企业增强其长期竞争优势，并在不断发展的数位农业市场中获得更大的市场份额。

调查方法

数据预测和建模中的因素

  • 在对现代农业中的人工智慧、物联网和区块链市场进行分析时，我们以美元为基准货币。为便于统计计算，除美元以外的其他货币均采用当年的平均外汇转换为美元。
  • 外汇以Oanda网站上的历史外汇为准。
  • 本研究考虑了 2021 年 1 月至 2024 年 3 月期间几乎所有最新发展。
  • 本报告中呈现的资讯是基于详细的一手访谈、调查和二手分析的结果。
  • 如果相关资讯不可用，则使用替代指标或推断方法。
  • 市场估计和预测并未考虑未来的景气衰退。
  • 除非出现重大技术突破，否则目前使用的技术预计将在整个预测期内继续沿用。

市场估计和预测

本研究利用了广泛的二级资讯来源，包括权威出版物、着名作者的报导、白皮书、公司年报、名录和主要资料库，以收集有用且有效的信息，对现代农业中的人工智能、物联网和区块链市场进行全面、技术性、市场导向性和商业性调查。

市场分析流程包括计算市场统计数据、估算市场规模、预测市场趋势、深入分析市场以及数据三角验证（这些定量数据处理技术的具体调查方法将在后续章节中详细介绍）。我们进行了初步调查，以收集有关市场细分类型和主要企业行业趋势的信息，并检验市场数据的有效性。

主要市场参与企业及竞争格局概述

本报告中介绍的现代农业人工智慧、物联网和区块链市场公司，是根据专家对其技术能力、解决方案广度、全球覆盖范围以及在整个数位农业价值链中的市场渗透率的意见而选定的。

现代农业领域人工智慧、物联网和区块链市场的主要企业

  • 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.

现代农业的人工智慧、物联网和区块链市场部分也全面涵盖了不属于上述群体的公司（如适用）。

目录

执行摘要

第一章 市场：产业展望

  • 趋势：对当前和未来影响的评估
    • 人工智慧驱动的作物分析和决策支持
    • 利用物联网进行精准灌溉和养分管理。
    • 利用机器人和无人机的智慧农业自动化
  • 监理情势
  • 研究与发展评论
    • 专利申请趋势（按国家和公司划分）
  • Start-Ups产业的现状
  • 相关人员分析
    • 用例
    • 最终用户和采购标准
  • 重大全球事件的影响分析
  • 市场动态概述
  • 市场动态
    • 市场驱动因素
    • 市场挑战
    • 市场机会

第二章：现代农业中的人工智慧、物联网和区块链市场（按应用领域划分）

  • 用途概述
  • 现代农业中的人工智慧、物联网和区块链市场（按应用领域划分）
    • 作物生产优化
    • 水和养分管理
    • 智慧农场监测和自动化
    • 畜牧管理

第三章：现代农业中的人工智慧、物联网和区块链市场（按产品划分）

  • 产品概述
  • 现代农业中的人工智慧、物联网和区块链市场（按产品划分）
    • 人工智慧（AI）
    • 物联网
    • 区块链平台

第四章：现代农业中的人工智慧、物联网和区块链市场（按地区划分）

  • 现代农业中的人工智慧、物联网和区块链市场（按地区划分）
  • 北美洲
    • 区域概览
    • 市场驱动因素
    • 市场限制因素
    • 应用
    • 产品
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 区域概览
    • 市场驱动因素
    • 市场限制因素
    • 应用
    • 产品
    • 德国
    • 法国
    • 英国
    • 荷兰
    • 西班牙
    • 其他的
  • 亚太地区
    • 区域概览
    • 市场驱动因素
    • 市场限制因素
    • 应用
    • 产品
    • 中国
    • 日本
    • 印度
    • 澳洲
    • 其他的
  • 其他地区
    • 区域概览
    • 市场驱动因素
    • 市场限制因素
    • 应用
    • 产品
    • 中东和非洲
    • 南美洲

第五章：公司简介

第六章：调查方法

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