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Smart Agriculture Market Size & Share 2026-2035

Report ID: GMI7104
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Published Date: July 2026
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Smart Agriculture Market Size

The smart agriculture market was valued at USD 23.2 billion in 2025. The market is expected to grow from USD 25.9 billion in 2026 to USD 59.6 billion in 2035, at a CAGR of 9.7%, according to the latest report published by Global Market Insights Inc.

Smart Agriculture Market Key Takeaways

2025 Market Size
$ 23.2 Billion
2026 Market Size
$ 25.9 Billion
2035 Forecast Market Size
$ 59.6 Billion
CAGR (2026–2035)
9.7%
Regional Dominance
Largest Market
North America
Fastest Growing Region
Asia Pacific
Key Players
  • Market Leader: John Deere led with over 11.2% market share in 2025.

  • Leading Players: Top 5 players in this market include John Deere, CNH Industrial, AGCO Corporation, Valmont Industries, Lindsay Corporation, which collectively held a market share of 26.6% in 2025.

Key Market Drivers
  • AI/ML & precision agriculture technology proliferation
  • Rising agricultural labor costs & structural workforce shortages
  • Government subsidies & digital agriculture policy programs
Opportunity
  • Carbon credit & environmental service markets
  • Autonomous farming systems development
Challenges
  • High upfront capital expenditure & extended ROI horizon
  • Digital literacy gap & skilled workforce deficit in agriculture

The regulatory environment is allowing smart farming to be adopted more widely in major agricultural economies, and thus a consistent structural tailwind exists for the adoption of smart farming. The European Union's “Farm to Fork Strategy” and Common Agricultural Policy reform package outline mandatory requirements around sustainability, precision application, and compliance with environmental regulations that farm operators cannot comply with without connected systems for monitoring and controlling their operations.[1]

At the same time, USDA precision agriculture investment programs are providing ongoing support from the federal government for on-farm technology infrastructure, so that a greater number of farm operations across the U.S. can afford to use digital tools to support their operations.[2]

Food security imperatives are strengthening the commercial case for smart agriculture on a global basis. The growing global population and the long-term decline of the amount of arable land available per capita are both putting increased pressure on farmers to get more productive output from their existing land base without putting in place proportionately as much chemical fertilizers or water as they have historically done.[3]

Precision application technologies, which allow farm operators to precisely apply fertilizers, pesticides, and irrigation, provide a way to achieve increased productivity through the use of technology, making higher productivity operationally necessary rather than just a way to differentiate yourself from your competitors.

The availability of farm labor is independently driving the adoption of technology in high-income agricultural markets. Structural labor shortages exist in North America, Europe, and parts of the world, for both seasonal farm labor and permanent farm labor. Therefore, smart farming provides farmers with an opportunity to meet labor needs through the use of technology, rather than having to rely solely on laborers to operate their farms.

Smart Agriculture Market Research Report

Smart Agriculture Market Trends

Changing innovation and technology transformation are important for the growth of the smart agriculture industry.

  • Across the agricultural sector, artificial intelligence (AI) and machine learning (ML) technologies are increasingly being integrated into modern decision-support tools, such as those used in crop monitoring, yield forecasting, and precision input management. This next generation of informed decision-making is allowing agricultural producers to utilize real-time agronomic insights derived from sensor networks, satellite imagery, and on-farm historical performance data- moving towards predictive management instead of reactive field management.[4]
  •  Additionally, equipment manufacturers and independent technology developers are integrating AI-based guidance layers into their products, thus narrowing the time between when data is generated and when farm managers utilize this data to make management decisions.
  • Across the irrigation-intensive agricultural production system, there is rapid progression toward the use of dense Internet of Things (IoT) sensor networks, which include soil moisture probes, microclimate weather stations, and evapotranspiration sensors, as baseline infrastructure for monitoring and managing water use. These dense IoT sensor networks are providing for variable-rate irrigation schedules based on real-time crop water demands, compared to traditional calendar or fixed-rate applied irrigation schedules.[5]
  • This results in significant reduction of water consumption and input costs in the field, as the costs of hardware used for in-field sensor networks decrease, and as the data management systems that process the output from in-field sensor networks mature, the business case for in-field sensors continues to strengthen.
  • Satellite-based precision guidance systems and field mapping systems are emerging as critical operational tools across row crops, specialty crops, and pasture management. High-accuracy GPS positioning integrated into farm equipment is enabling machine-level navigation precision that supports variable-rate application, controlled traffic farming, and seamless machine-to-machine coordination at the fleet level.

Smart Agriculture Market Analysis

Smart Agriculture Market Size, By Product Type, 2022 – 2035 (USD Billion)

Based on product type, the industry is segmented into hardware & equipment, software platforms, and connectivity & services. The hardware & equipment segment accounts for revenue of around USD 13.5 billion in the year 2025 and is expected to reach USD 30.6 billion by 2035.

  • Hardware and equipment form the core physical foundation of every smart agriculture market. Precision GPS receivers, field sensor networks, drone platforms, and automated farm machinery need to be in place before software platforms and connectivity services can deliver real value to farmers.
  • This architectural dependence means that, overall, exemplary procurement must take place prior to any farm using a digital platform- allowing for it to establish both a lead in terms of timeframe, and therefore volume, in relation to digital agricultural technologies.
  • From a commercial operator perspective, precision agriculture hardware is treated similarly to durable capital infrastructure and complies with capital replacement cycles, rather than as an additional source of technology spending. For example, GPS-based guidance terminals, variable rate application controllers and machine telemetry systems all require multi-year capital investment and typically upgrade their value over the course of several years as performance standards change, and regulatory compliance requirements increase.
  • This cadence of replacement provides an ongoing, multi-event cycle of demand for the entire segment of precision agricultural hardware that will not be individually replicated with software license and service revenues.
  • The range of hardware categories available to farmers such as  drone platforms, soil-based sensors, in-cab guidance systems, and perimeter weather hubs, provides producers with the ability to efficiently and effectively address a variety of operational needs associated with all crop types, sizes of farms, and geographic conditions within one product segment.

Smart Agriculture Market Revenue Share (%), By Farm Size (2025)

Based on the farm size, the smart agriculture market is bifurcated into large (>50 Ha), medium (5–50 Ha) and small (5 Ha). The large (>50 Ha) segments held the largest share, accounting for 53.3% of the market in 2025.

  • Large commercial farm operations can utilize a larger overall investment in capital, and capital investments are significantly less risky for large-scale operations than for small-scale operations.
  • The economics of GPS navigation systems, variable-rate application equipment, aerial imaging systems, and integrated farm management software all benefit directly from the number of acres an agricultural producer has in operation. The more acres operated, the higher the expected return on investment for smart agriculture technology.
  • The availability of business financing from land-based institutions or government grants in the North American, European, and major Asia-Pacific markets is tilted heavily toward large-scale operators. These large operators possess the financial documentation, collateral, and credentials necessary to access business loans and investment opportunities within precision agriculture.
  • Large-scale operators also have access to incentives and grants within precision agriculture, while smaller operators do not have the equity to finance precision agriculture technology. This inherent imbalance creates a significant availability gap in technology adoption rates between large agricultural producers and smaller agricultural producers when looking at high-value markets across the world.
  • Agricultural operations at the farm level create an inherently complex need for information management systems that large farms have in greater number than farming operations at a smaller scale such as managing various crop species/varieties, multiple soil types, layered irrigation systems, multiple machine fleets/end-user equipment and any required transportation.

North America Smart Agriculture Market

U.S. Smart Agriculture Market Size, 2022 – 2035 (USD Billion)

In 2025, the U.S. dominated the market growth in North America, accounting for 73.8% of the share in the region.

  • Growth in the North America smart agriculture industry is anchored by a commercially mature farm sector with well-established precision agriculture infrastructure and demonstrated willingness to invest in capital-intensive digital tools. Federal programs administered through USDA agencies have consistently directed sustained investment toward on-farm GPS guidance, remote sensing, and farm management software infrastructure across major crop production systems- reinforcing broad-based technology adoption at scale.
  • The region benefits from exceptional ecosystem density in smart agriculture, with major equipment manufacturers, agri-tech platform developers, and venture-backed agricultural technology startups all headquartered in or commercially active across the United States.

Asia Pacific Smart Agriculture Market

Asia Pacific smart agriculture industry is expected to grow at 11.4% during the forecast period.

  • Rapid urbanization across Asia Pacific is simultaneously reducing the supply of agricultural labor and increasing domestic food demand- a structural imbalance that is generating powerful, policy-supported incentives for farm mechanization and digital monitoring adoption at scale.
  • Government initiatives in China and India are actively subsidizing precision equipment acquisition and digital agriculture platform deployment as components of national food security and rural economic development programs, driving adoption at a pace that is positioning Asia Pacific as the market's most dynamic regional growth environment [6].

Europe Smart Agriculture Market

Europe smart agriculture industry is expected to grow at 9.3% during the forecast period.

  • The European Commission's Farm to Fork Strategy, alongside Common Agricultural Policy sustainability conditionality reforms, is establishing mandatory precision application, environmental monitoring, and farm data transparency requirements that targeted smart agriculture technologies directly address.
  • Adoption of precision input management systems, in-field sensor infrastructure, and digital farm management platforms is being accelerated by compliance requirements rather than purely commercial incentives- generating durable, regulation-backed demand across commercial, mid-sized, and family farm segments throughout Western and Central Europe.

Middle East and Africa Smart Agriculture Market

Middle East and Africa smart agriculture industry is expected to grow at 10.1% during the forecast period.

  • Countries including the UAE are channeling strategic capital toward controlled environment agriculture, precision drip irrigation, and remote sensing infrastructure as direct responses to water scarcity and the fundamental constraints of limited arable land availability.
  • These investments are creating specific demand for sensor networks, automated irrigation controls, and satellite crop monitoring systems that enable productive agricultural output in environments where conventional farming approaches face irreducible resource limitations.

Smart Agriculture Market Share

The top companies in the smart agriculture industry John Deere, CNH Industrial, AGCO Corporation, Valmont Industries and Lindsay Corporation collectively hold a share of 26.6% of the market in 2025. These prominent players are proactively involved in strategic endeavors, such as mergers & acquisitions, facility expansions & collaborations, to expand their product portfolios, extend their reach to a broad customer base, and strengthen their market position.

  • John Deere is a global leader in smart agriculture, offering precision farming solutions that integrate GPS guidance, autonomous machinery, AI-powered analytics, and connected farm management platforms. Through technologies such as precision spraying, autonomous tractors, and the John Deere Operations Center, the company helps farmers optimize productivity, reduce input costs, and improve decision-making using real-time field data.
  • CNH Industrial, through its Case IH and New Holland brands, provides advanced precision agriculture solutions including guidance systems, telematics, autonomous equipment, and digital farm management tools. The company focuses on connected farming by integrating machinery, sensors, and data analytics to improve operational efficiency, crop yields, and resource utilization across large-scale agricultural operations.
  • AGCO Corporation delivers smart farming technologies through brands such as Fendt, Massey Ferguson, and Valtra. Its precision agriculture portfolio includes variable-rate application systems, GPS-guided equipment, telemetry solutions, and the Fuse smart farming platform. The company emphasizes interoperable and data-driven technologies that help farmers increase productivity while promoting sustainable agricultural practices.

Smart Agriculture Market Companies

Major players operating in the smart agriculture industry are:

  • Ag Leader Technology
  • AGCO Corporation
  • AgEagle Aerial Systems
  • Carbon Robotics
  • CLAAS KGaA mbH
  • CNH Industrial  
  • Delair
  • DeLaval
  • FarmDroid
  • GEA Group
  • Hemisphere GNSS
  • John Deere  
  • Kubota Corporation
  • Lely Industries
  • Lindsay Corporation
  • METER Group
  • Netafim  
  • Pessl Instruments
  • Saga Robotics
  • Sentek Technologies
  • Topcon Agriculture
  • Trimble Agriculture
  • Valmont Industries
  • Yanmar Holdings  

Valmont Industries is a major provider of precision irrigation and agricultural technology solutions through its Valley Irrigation business. The company offers connected irrigation systems, remote monitoring platforms, and data-driven water management technologies that enable farmers to optimize water usage, improve crop performance, and enhance farm sustainability in water-scarce regions.

Lindsay Corporation participates in the smart agriculture market through its Zimmatic irrigation systems and FieldNET remote management platform. The company combines precision irrigation, IoT-enabled monitoring, and automated control technologies to help growers manage water resources efficiently. Its solutions support higher crop yields, reduced operating costs, and improved farm productivity through real-time field insights.

Smart Agriculture Industry News

  • In February 2026, John Deere officially announced its roster for the 2026 Startup Collaborators cohort. The initiative focuses on scaling early-stage companies specializing in cutting-edge agricultural robotics, computer vision, and machine learning to deepen Deere’s pipeline of autonomous field equipment and farm software solutions.
  • In February 2026, Carbon Robotics introduced the world's first Large Plant Model (LPM), which is a major artificial intelligence breakthrough trained on over 150 million labeled plants. This advanced AI platform enables their autonomous LaserWeeder machinery to instantly identify and eliminate weeds in real-time, adapting instantly to unique microclimates and field conditions without requiring custom programming.
  • In November 2025, CNH Industrial debuted its high-tech product fleet for the upcoming 2026 production year, focusing on customer-centric field robotics and automation. A key innovation featured was the Case IH SenseApply system, an AI-powered smart spraying framework that uses computer vision for green-on-brown weed detection and targeted chemical application
  • In August 2025, AGCO Corporation announced an expansion of its North American distribution network through dealer mergers in Eastern Canada to establish larger contiguous territories. The strategy aims to improve regional accessibility for its precision agriculture tech suites, including Fendt equipment lines and the smart connectivity platform known as FarmerCore.
  • In March 2025, CNH Industrial partnered with digital platform xFarm to deploy autonomous xSense Pro microclimate weather stations in global water-scarce test regions. This precision irrigation initiative uses cellular networks to feed localized field data directly into connected farm management software, allowing automated water tracking.

The smart agriculture market research report includes in-depth coverage of the industry, with estimates & forecasts in terms of revenue (USD Billion) (from 2022 to 2035), for the following segments:

Market, By Product Type

  • Hardware & Equipment
    • Drones & Unmanned Aerial Vehicles (UAVs)
      • Agricultural Spraying Drones
      • Crop Monitoring & Imaging Drones
      • Multispectral & Hyperspectral Sensing UAVs
    • Precision Irrigation Systems
      • Drip Irrigation with Smart Controls
      • Variable Rate Irrigation (VRI) Systems
      • Soil Moisture Sensor-Integrated Systems
    • GPS/GNSS Guidance & Auto-Steering Systems
      • RTK-GPS Precision Guidance Systems
      • Auto-Steer Retrofit Kits for Existing Machinery
      • Field Mapping & Variable Rate Application Controllers
    • IoT Sensors & Connected Field Devices
      • Soil Health Sensors (Nutrient, Moisture, pH)
      • Weather Stations & Microclimate Monitoring Devices
      • Crop Growth & Canopy Sensors
    • Automated & Robotic Farm Machinery
      • Autonomous Tractors & Self-Driving Platforms
      • Harvesting Robots- Fruit, Vegetable & Grain Picking
      • Seeding & Planting Automation Systems
      • Weeding Robots & Mechanical Pest Control Devices
    • AI-Integrated Intelligent Farm Equipment
      • Machine Vision-Enabled Sprayers & Spreaders
      • AI-Powered Combine Harvesters
      • Intelligent Fertigation & Crop Management Systems
  • Software & Farm Management Platforms
    • Farm Management Information Systems (FMIS)
    • Precision Agriculture Analytics Platforms
    • AI-Driven Crop Advisory & Decision Support Software
  • Connectivity & Services
    • Remote Monitoring & Telematics Services
    • Maintenance & After-Sales Service Platforms
  • Data-as-a-Service (DaaS) & Subscription Models

Market, By Technology Type

  • Precision Farming Technology
    • Variable Rate Technology (VRT)
    • GPS/GNSS-Based Precision Guidance Systems
    • Remote Sensing & Satellite Imagery for Field Analytics
  • Artificial Intelligence & Machine Learning
    •  AI-Powered Crop Yield Prediction Models
    • Computer Vision for Crop Disease & Pest Detection
    • Machine Learning in Autonomous Farm Equipment Navigation
    • Generative AI in Agricultural Advisory Platforms
  • Internet of Things (IoT) & Connectivity
    • Agricultural IoT Sensor Networks
    • 5G & LPWAN Connectivity for Smart Farm Devices
    • Edge Computing in On-Farm IoT Data Processing
  • Robotics & Automation
    • Field Robotics
    • Greenhouse Automation Systems
    •  Swarm Robotics in Large-Scale Crop Production
  • Remote Sensing & Aerial Technology
    • UAV/Drone-Based Remote Sensing
    • Satellite-Based Crop Monitoring Platforms
    •  LiDAR Applications in Agricultural Terrain Mapping
  • Blockchain & Data Management Technology
    • Blockchain for Agricultural Supply Chain Transparency
  •  Farm Data Ownership & Interoperability Standards

Market, By Farm Size

  • Large Farms (>50 Hectares)
  • Medium Farms (5–50 Hectares)
  • Small Farms (5 Hectares)

Market, By Application

  • Crop Production
    • Cereal & Grain Crops
    • Fruits & Vegetables
    • Oilseeds & Pulses
    •  Specialty & High-Value Crops
  •  Livestock Monitoring
    • Precision Livestock Farming
    • Dairy Farm Automation
  •  Aquaculture
  • Forestry & Land Management

The above information is provided for the following regions and countries:

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Spain
    • Netherlands
  • Asia Pacific
    • China
    • Japan
    • India
    • Australia
    • South Korea
    • Indonesia
    • Philippines
  • Latin America
    • Brazil
    • Mexico
    • Argentina
  • MEA
    • Turkey
    • Israel
    • South Africa

 

Authors:  Avinash Singh, Sunita Singh

Table of Contents

Chapter 1   Methodology & Scope

Chapter 2   Executive Summary

Chapter 3   Industry Insights

Chapter 4   Competitive landscape, 2025

Chapter 5   Market Estimates and Forecast, By Product, 2022 – 2035 (USD Billion)

Chapter 6   Market Estimates and Forecast, By Technology, 2022 – 2035 (USD Billion)

Chapter 7   Market Estimates and Forecast, By Farm Size, 2022 – 2035 (USD Billion)

Chapter 8   Market Estimates and Forecast, By Application, 2022 – 2035 (USD Billion)

Chapter 9   Market Estimates and Forecast, By Region, 2022 – 2035 (USD Billion)

Chapter 10   Company Profiles

Frequently Asked Question(FAQ) :
How big is the smart agriculture market?
The smart agriculture market size was estimated at USD 23.2 billion in 2025 and is expected to reach USD 25.9 billion in 2026.
What is the 2035 forecast for the smart agriculture market?
The market is projected to reach USD 59.6 billion by 2035, growing at a CAGR of 9.7% from 2026 to 2035.
Which region dominates the smart agriculture market?
North America currently holds the largest share of the smart agriculture market in 2025.
Which region is expected to grow the fastest in the smart agriculture market?
Asia Pacific is projected to be the fastest-growing region during the forecast period.
Who are the major players in smart agriculture market?
Some of the major players in smart agriculture market include John Deere, CNH Industrial, AGCO Corporation, Valmont Industries, Lindsay Corporation.

Research methodology, data sources & validation process

This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.

Our 6-step research process

  1. 1. Research design & analyst oversight

    At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.

    Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.

  2. 2. Primary research

    Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.

  3. 3. Data mining & market analysis

    Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.

  4. 4. Market sizing

    Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.

  5. 5. Forecast model & key assumptions

    Every forecast includes explicit documentation of:

    • ✓ Key growth drivers and their assumed impact

    • ✓ Restraining factors and mitigation scenarios

    • ✓ Regulatory assumptions and policy change risk

    • ✓ Technology adoption curve parameter

    • ✓ Macroeconomic assumptions (GDP growth, inflation, currency)

    • ✓ Competitive dynamics and market entry/exit expectations

  6. 6. Validation & quality assurance

    The final stages involve human validation, where domain experts manually review filtered data to identify nuances and contextual errors that automated systems might miss. This expert review adds a critical layer of quality assurance, ensuring data aligns with research objectives and domain-specific standards.

    Our triple-layer validation process ensures maximum data reliability:

    • ✓ Statistical Validation

    • ✓ Expert Validation

    • ✓ Market Reality Check

Trust & credibility

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Professional standards & satisfaction
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150+
Research Analysts
Across 10+ industry verticals
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5-year relationship value

Verified data sources

  • Trade publications

    Security & defense sector journals and trade press

  • Industry databases

    Proprietary and third-party market databases

  • Regulatory filings

    Government procurement records and policy documents

  • Academic research

    University studies and specialist institution reports

  • Company reports

    Annual reports, investor presentations, and filings

  • Expert interviews

    C-suite, procurement leads, and technical specialists

  • GMI archive

    13,000+ published studies across 30+ industry verticals

  • Trade data

    Import/export volumes, HS codes, and customs records

Parameters studied & evaluated

Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →

Authors:  Avinash Singh, Sunita Singh
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