커넥티드 농업 시장 : 컴포넌트, 모듈, 제공, 용도, 최종사용자별 - 세계 예측(2025-2032년)

The Connected Agriculture Market is projected to grow by USD 18.76 billion at a CAGR of 16.64% by 2032.

Concise foundational framing of connected agriculture technologies, institutional drivers, and commercialization pathways shaping farm-level decision-making

Connected agriculture is emerging as a foundational pillar of modern food systems, enabling precision, traceability, and resilience across the farm-to-fork continuum. This introduction synthesizes the core technologies, operational shifts, and stakeholder motivations that define the sector, establishing a context for deeper strategic analysis.

The narrative begins with the technological building blocks that underpin connected agriculture, including networks of sensors, edge and cloud computing, analytics, and integrated farm management platforms. These elements combine to deliver incremental and systemic value: improved input efficiency, reduced waste, and enhanced decision-making at the field level. Equally important are the institutional drivers - regulatory pressures for sustainability, evolving consumer expectations for provenance and quality, and the operational imperative to manage risk in a more variable climate environment.

Transitioning from concept to adoption, the introduction emphasizes how commercial models are evolving to link hardware, software, and services into bundled offerings that lower adoption barriers for growers. The section frames the remainder of the executive summary by highlighting where strategic value is created, which stakeholders capture that value, and how interoperability, standards, and data governance will influence long-term success. By offering this orientation, the content prepares readers to evaluate subsequent discussions on market dynamics, competitive positioning, and actionable recommendations.

How rapid sensor innovation, data governance, and outcome-based commercial models are reshaping adoption patterns and value capture across the agrifood value chain

The landscape of connected agriculture is undergoing transformative shifts that are redefining operational norms, technology adoption patterns, and value capture across the agrifood ecosystem. Rapid advancements in sensor miniaturization and low-power connectivity are enabling more granular monitoring of soil, weather, and crop status, while improvements in machine learning and edge analytics are moving meaningful intelligence closer to the point of action.

Simultaneously, business models are shifting from one-time technology sales toward subscription and outcome-based agreements that align vendor incentives with farm productivity and sustainability outcomes. This transition is encouraging long-term partnerships between technology providers and growers and is prompting investment in integration capabilities and service delivery. Governance and interoperability are also in focus; increasing attention to data standards and secure data exchange is creating new expectations around data ownership, privacy, and the ethical use of farm-level information.

As these developments converge, stakeholders must reassess strategic priorities: technology selection criteria, supply chain partnerships, talent and capability development, and regulatory engagement. The result is a more interconnected, data-driven agricultural paradigm where differentiated value will accrue to organizations that can combine robust sensing, practical analytics, and scalable service models while demonstrating measurable agricultural and environmental benefits.

Assessing the strategic supply chain and commercial responses to tariff-driven cost pressures on precision agriculture components and integrated systems

The cumulative impact of tariff policy adjustments through 2025 has materially influenced supplier strategies, procurement choices, and the design of connected agriculture solutions. Tariffs on imported components such as sensors, precision-actuation hardware, and communications modules have increased unit costs for many integrated systems, thereby accelerating evaluation of alternative sourcing strategies and local assembly options.

In response, manufacturers and solution providers have pursued a range of mitigations. Some organizations have accelerated supplier diversification to include regional vendors with reduced tariff exposure, while others have altered bill-of-materials designs to rely more heavily on domestically sourced components. Additionally, there has been a discernible shift toward modular architectures that allow incremental upgrades without full-system replacements, helping to manage capital intensity for end users.

These dynamics have also affected go-to-market approaches. Providers are emphasizing financing, managed services, and software-centric revenue streams to offset higher hardware costs and to preserve adoption momentum. From a policy engagement perspective, stakeholders are increasing advocacy efforts centered on harmonized standards and tariff exemptions for critical agricultural technologies. Collectively, these responses demonstrate an adaptive ecosystem that is rebalancing supply chains and business models to preserve innovation diffusion despite the headwinds created by tariff measures.

Integrated segmentation perspectives highlighting how components, modules, deployment choices, applications, and end users create distinct adoption pathways and value propositions

Key segmentation insights reveal where adoption accelerates, which offerings resonate with different customer cohorts, and how product and service architectures must evolve to meet diverse needs. Analysis by component shows a differentiated landscape between Services and Solutions: Services encompass consulting services, managed services, professional services, support and maintenance, and training and education, while Solutions cover crop monitoring, farming machinery management, greenhouse automation, irrigation management, livestock monitoring, and weather and soil monitoring. This duality underscores that providers must balance deep domain expertise with scalable, productized capabilities to serve both implementation and ongoing operational needs.

When examining the technology stack through module segmentation, the market divides across application enablement, connectivity management, and device management, each demanding distinct engineering priorities and go-to-market narratives. Deployment preferences further segment the landscape into cloud and on-premises options, reflecting variability in connectivity, security posture, and customer willingness to trust off-site data stewardship. Application-based segmentation isolates pre-production planning and management, in-production planning and management, and post-production planning and management, indicating that end-to-end workflows require integrated solutions that span the crop lifecycle.

Finally, end user segmentation identifies farmers, government agencies, and research institutions as primary adopter groups, each with unique procurement drivers, performance metrics, and support expectations. Together, these segmentation lenses suggest that successful strategies will be those that tailor bundles of technology, services, and deployment models to clearly defined user journeys while maintaining interoperability to enable cross-segment scalability.

Comparative regional dynamics and strategic go-to-market considerations across the Americas, Europe Middle East & Africa, and Asia-Pacific that influence technology adoption

Regional dynamics are central to shaping adoption trajectories, investment priorities, and partnership models within connected agriculture. In the Americas, adoption is being driven by large-scale commercial farms and strong private-sector investment into precision farming tools, creating a fertile environment for vertically integrated solutions and finance-backed deployment models. Transitioning eastward, Europe, Middle East & Africa present a mosaic of regulatory drivers and sustainability mandates that are encouraging sensor deployment, traceability initiatives, and collaborative research partnerships between public institutions and private innovators.

Asia-Pacific exhibits a mix of high-technology adoption in industrialized markets and leapfrogging opportunities in emerging economies where mobile-first solutions and low-cost sensor networks can scale rapidly. These regional differences imply varying priorities for solution architecture, pricing, and local partnerships. For example, regions with fragmented smallholder landscapes will prioritize lightweight, low-cost solutions and strong extension services, whereas regions with large commercial farms will value integrated machinery management, high-bandwidth connectivity, and advanced analytics.

Consequently, vendors must adopt differentiated regional go-to-market playbooks that account for regulatory environments, infrastructure constraints, and customer sophistication. Cross-regional learners can export proven service models while adapting technology to local agronomic and economic contexts, thereby accelerating adoption while managing implementation risk.

How integrated product-service strategies, strategic partnerships, and talent orchestration are defining competitive advantage among connected agriculture providers

Companies operating in connected agriculture are consolidating capabilities across hardware, software, and services to capture recurring revenue and to deepen customer relationships. Leading organizations tend to focus on integrated platform development while simultaneously building out professional services and managed service offerings to ensure successful deployment and long-term value realization. Strategic partnerships with telecom operators, sensor manufacturers, and agricultural cooperatives are common, enabling solutions that leverage existing distribution networks and local agronomic expertise.

Product roadmaps emphasize modularity and open APIs to facilitate interoperability with third-party tools and to reduce integration friction for large enterprise customers. In parallel, service portfolios are expanding to include advisory services, agronomic analytics, and outcome-based contracts that align vendor compensation with measured agronomic improvements. Talent strategies reflect growing demand for interdisciplinary teams that combine agronomy, data science, and systems engineering, along with customer success functions focused on farmer adoption and retention.

From a competitive standpoint, market leaders differentiate through validated field performance, robust assurance programs, and transparent data governance. Emerging challengers commonly focus on niche segments - for example, specialized sensors or localized advisory platforms - and can rapidly gain footholds by addressing specific pain points. Overall, the firm-level insight is that sustained advantage will accrue to organizations that execute integrated product-service strategies while maintaining flexibility to adapt to regional requirements and evolving regulatory expectations.

Practical strategic actions that industry leaders should implement to accelerate adoption, de-risk supply chains, and align commercial models with measurable farm outcomes

Leaders in the industry should prioritize actions that accelerate meaningful adoption while protecting long-term optionality and resilience. First, invest in modular product architectures and open integration capabilities to reduce customer friction and to enable flexible financing and upgrade paths. Second, expand service-led offerings-including training and managed services-to increase adoption velocity and to transform one-time hardware sales into recurring revenue relationships.

Third, diversify supply chains to mitigate tariff exposure and to shorten lead times for critical components; this should include regional assembly capabilities and strategic supplier partnerships. Fourth, engage proactively with policymakers, standards bodies, and industry consortia to shape favorable regulatory outcomes and to advocate for standards that enable secure data exchange. Fifth, build interdisciplinary teams that combine agronomy, data science, and field engineering, and invest in on-farm demonstrations and proof-of-value pilots to establish credibility and measurable outcomes.

Finally, adopt customer-centric pricing and contracting models that align incentives, such as outcome-based contracts or usage-based subscriptions, and ensure robust data governance practices that address privacy, security, and ownership concerns. Implementing these actions will increase adoption resilience, accelerate time-to-value for end users, and position organizations to capture more of the long-term value created by connected agriculture.

Transparent mixed-methods research approach combining stakeholder interviews, targeted literature review, and segmentation-based triangulation to produce actionable findings

The research methodology underpinning this executive summary is designed to combine primary qualitative insight with rigorous secondary synthesis to ensure balanced, actionable findings. Qualitative inputs were gathered through structured interviews with a cross-section of stakeholders, including technology providers, agricultural practitioners, policy advisors, and research institutions, to capture diverse perspectives on adoption barriers, operational priorities, and future trajectories.

Secondary research comprised a targeted review of technical literature, regulatory announcements, and industry reports to contextualize primary insights and to trace technology and policy trends. The analysis applied a segmentation framework to map capabilities across components, modules, deployment models, applications, and end-user types, enabling granular interpretation of where value is created and where strategic focus should be concentrated. Triangulation techniques were used to validate divergent viewpoints, and scenario-based reasoning helped explore how policy shifts and supply-chain disruptions could influence strategic choices.

Throughout the methodology, attention was paid to transparency of assumptions and to documenting sources of uncertainty. Sensitivity analysis and corroborative interviews were employed to reduce bias and to highlight areas where additional field validation would be valuable. This methodological approach supports robust, practitioner-oriented conclusions and recommendations.

Consolidated strategic perspective emphasizing the necessary alignment of technology integration, policy engagement, and field-level validation to realize long-term value

The conclusion synthesizes the executive summary's principal insights and offers a concise perspective on strategic priorities for stakeholders across the connected agriculture ecosystem. Technology and business-model innovation are converging to make precision agriculture more accessible and operationally impactful, yet adoption will depend on the ability of providers to integrate hardware, software, and services in ways that are affordable, interoperable, and demonstrably beneficial under real-world conditions.

Policy and supply-chain dynamics are significant modifiers of the adoption curve; proactive strategies that address tariff exposure, local sourcing, and regulatory engagement are essential to sustain momentum. Equally, regional variation in farm structure and infrastructure will require tailored approaches rather than a one-size-fits-all playbook. Providers that combine modular product design, flexible commercial models, and a strong emphasis on field-level validation will be best positioned to capture long-term value.

In closing, connected agriculture represents a pragmatic path to improve productivity, sustainability, and resilience, but realizing that potential will require disciplined execution, collaborative partnerships, and continued emphasis on measurable outcomes. Stakeholders should prioritize interventions that reduce adoption friction, protect economic viability for growers, and ensure that data and technology deployments deliver verifiable agronomic and environmental benefits.

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Implementation of AI-driven predictive analytics with real-time soil moisture monitoring to optimize irrigation scheduling
• 5.2. Deployment of drone-based multispectral imaging integrated with machine learning models for crop health assessment
• 5.3. Adoption of blockchain-enabled supply chain traceability platforms for transparent provenance tracking of fresh produce
• 5.4. Integration of edge computing devices with IoT sensor networks for real-time pest and disease detection in fields
• 5.5. Utilization of 5G connectivity to support autonomous farm machinery and remote equipment telemetry in large-scale operations
• 5.6. Implementation of cloud-based farm management software with interoperable data standards for system-wide analytics and collaboration
• 5.7. Expansion of digital twin technology to simulate and optimize greenhouse environmental controls and crop growth strategies

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Connected Agriculture Market, by Component

• 8.1. Services
  • 8.1.1. Consulting Services
  • 8.1.2. Managed Services
  • 8.1.3. Professional Services
  • 8.1.4. Support & Maintenance
  • 8.1.5. Training & Education
• 8.2. Solutions
  • 8.2.1. Crop Monitoring
  • 8.2.2. Farming Machinery Management
  • 8.2.3. Greenhouse Automation
  • 8.2.4. Irrigation Management
  • 8.2.5. Livestock Monitoring
  • 8.2.6. Weather & Soil Monitoring

9. Connected Agriculture Market, by Module

• 9.1. Application Enablement
• 9.2. Connectivity Management
• 9.3. Device Management

10. Connected Agriculture Market, by Deployment

• 10.1. Cloud
• 10.2. On-Premises

11. Connected Agriculture Market, by Application

• 11.1. In-Production Planning & Management
• 11.2. Post-Production Planning & Management
• 11.3. Pre-Production Planning & Management

12. Connected Agriculture Market, by End User

• 12.1. Farmers
• 12.2. Government Agencies
• 12.3. Research Institutions

13. Connected Agriculture Market, by Region

• 13.1. Americas
  • 13.1.1. North America
  • 13.1.2. Latin America
• 13.2. Europe, Middle East & Africa
  • 13.2.1. Europe
  • 13.2.2. Middle East
  • 13.2.3. Africa
• 13.3. Asia-Pacific

14. Connected Agriculture Market, by Group

• 14.1. ASEAN
• 14.2. GCC
• 14.3. European Union
• 14.4. BRICS
• 14.5. G7
• 14.6. NATO

15. Connected Agriculture Market, by Country

• 15.1. United States
• 15.2. Canada
• 15.3. Mexico
• 15.4. Brazil
• 15.5. United Kingdom
• 15.6. Germany
• 15.7. France
• 15.8. Russia
• 15.9. Italy
• 15.10. Spain
• 15.11. China
• 15.12. India
• 15.13. Japan
• 15.14. Australia
• 15.15. South Korea

16. Competitive Landscape

• 16.1. Market Share Analysis, 2024
• 16.2. FPNV Positioning Matrix, 2024
• 16.3. Competitive Analysis
  • 16.3.1. Accenture PLC
  • 16.3.2. Ag Leader Technology
  • 16.3.3. AGCO Corporation
  • 16.3.4. AGRIVI Ltd.
  • 16.3.5. BASF SE
  • 16.3.6. Bayer AG
  • 16.3.7. Cisco Systems, Inc.
  • 16.3.8. CNH Industrial N.V.
  • 16.3.9. Conservis By Traction Ag Inc.
  • 16.3.10. Corteva, Inc.
  • 16.3.11. Cropin Technology Solutions Private Limited
  • 16.3.12. Croptracker, Inc.
  • 16.3.13. Deere & Company
  • 16.3.14. Farmers Edge Inc.
  • 16.3.15. Gamaya
  • 16.3.16. Granular Inc.
  • 16.3.17. Hexagon AB
  • 16.3.18. International Business Machines Corporation
  • 16.3.19. Kubota Corporation
  • 16.3.20. Lindsay Corporation
  • 16.3.21. Microsoft Corporation
  • 16.3.22. Oracle Corporation
  • 16.3.23. Robert Bosch GmbH
  • 16.3.24. SAP SE
  • 16.3.25. Shivrai Technologies Pvt. Ltd.
  • 16.3.26. SMAG by InVivo
  • 16.3.27. Syngenta AG
  • 16.3.28. Taranis
  • 16.3.29. TELUS Communications Inc.
  • 16.3.30. Tend.com
  • 16.3.31. Topcon Corporation
  • 16.3.32. Yara International ASA