Dublin, May 21, 2026 (GLOBE NEWSWIRE) — The “AI in Crop Monitoring Global Market Report 2026” has been added to ResearchAndMarkets.com’s offering.
The AI in crop monitoring market is on an exponential growth trajectory, expected to soar from $2.64 billion in 2025 to $8.29 billion by 2030, with a CAGR nearing 25.8% between 2025 and 2026. This robust growth is driven by the increasing adoption of precision agriculture technologies, the need for higher crop yields, and the demand for food security. Factors such as the use of drones and IoT devices for real-time monitoring, automated data collection, and analysis are propelling the market forward.
Looking to the future, key factors fuelling growth include governmental support for smart farming, efforts to cut labor costs in agriculture, and a shift towards data-driven decision-making. The integration of cloud-based farm management platforms and investments in AI-driven crop tools are transforming the sector. Innovations in AI and machine learning algorithms ensure enhanced monitoring accuracy, while novel drone and satellite technologies offer unprecedented real-time farm insights.
The adoption of robotics and autonomous machinery, exemplified by robotic harvesters and smart irrigation systems, is another major driver. These technologies mitigate labor shortages and enhance precision in farming operations. AI utilizes data from these systems to offer insights on crop health, soil conditions, and pest management.
Key industry players like Syngenta Group are advancing the field with generative AI-powered agronomic intelligence, providing dynamic recommendations and predictive analytics for improved crop management. Acquisitions, such as CropX Technologies Ltd.’s purchase of EngeniousAg Technologies Pvt. Ltd., demonstrate industry consolidation aimed at integrating AI with precision agriculture tools.
Leading companies in this market include International Business Machines Corporation, CNH Industrial N.V., and John Deere Company. These firms, alongside regional competitors, are pivotal in driving technological advancements and market expansion.
Regionally, North America led the market in 2025, with Asia-Pacific poised for rapid growth. Strategic regional developments reflect a broader geographical scope, with countries like China, India, and Brazil playing significant roles.
The AI in crop monitoring sector encompasses services such as real-time health monitoring, soil analysis, and yield prediction, all facilitated by cutting-edge AI technologies. This market is characterized by its reliance on factory gate values, with revenues generated from both direct sales and complementary services.
Despite this growth, challenges such as tariffs have raised the costs of hardware imports, slowing adoption rates among smaller farms in certain regions. However, this has spurred local manufacturing and a pivot towards software-based solutions. Overall, the AI in crop monitoring market stands at the forefront of agricultural innovation, offering enhanced efficiency and sustainability in food production amid global challenges.
Scope:
- Markets Covered: Offerings include hardware, software, and services; deployment via cloud-based or on-premises solutions.
- Technologies: Covering AI, machine learning, IoT, big data analytics, and more.
- Applications: From disease management to precision irrigation and soil health monitoring.
- End Users: Extend from agricultural cooperatives to Agri-Tech companies.
- Key Companies Mentioned: Industry leaders such as International Business Machines Corporation, John Deere, and EOS Data Analytics Inc., among others, are profiled for their contributions to the sector.
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 250 |
| Forecast Period | 2026 – 2030 |
| Estimated Market Value (USD) in 2026 | $3.33 Billion |
| Forecasted Market Value (USD) by 2030 | $8.29 Billion |
| Compound Annual Growth Rate | 25.7% |
| Regions Covered | Global |
Key Topics Covered:
1. Executive Summary
1.1. Key Market Insights (2020-2035)
1.2. Visual Dashboard: Market Size, Growth Rate, Hotspots
1.3. Major Factors Driving the Market
1.4. Top Three Trends Shaping the Market
2. Artificial Intelligence (AI) in Crop Monitoring Market Characteristics
2.1. Market Definition & Scope
2.2. Market Segmentations
2.3. Overview of Key Products and Services
2.4. Global Artificial Intelligence (AI) in Crop Monitoring Market Attractiveness Scoring and Analysis
2.4.1. Overview of Market Attractiveness Framework
2.4.2. Quantitative Scoring Methodology
2.4.3. Factor-Wise Evaluation
Growth Potential Analysis, Competitive Dynamics Assessment, Strategic Fit Assessment and Risk Profile Evaluation
2.4.4. Market Attractiveness Scoring and Interpretation
2.4.5. Strategic Implications and Recommendations
3. Artificial Intelligence (AI) in Crop Monitoring Market Supply Chain Analysis
3.1. Overview of the Supply Chain and Ecosystem
3.2. List of Key Raw Materials, Resources & Suppliers
3.3. List of Major Distributors and Channel Partners
3.4. List of Major End Users
4. Global Artificial Intelligence (AI) in Crop Monitoring Market Trends and Strategies
4.1. Key Technologies & Future Trends
4.1.1 Artificial Intelligence & Autonomous Intelligence
4.1.2 Internet of Things (Iot), Smart Infrastructure & Connected Ecosystems
4.1.3 Digitalization, Cloud, Big Data & Cybersecurity
4.1.4 Sustainability, Climate Tech & Circular Economy
4.1.5 Industry 4.0 & Intelligent Manufacturing
4.2. Major Trends
4.2.1 Expansion of Real-Time Crop Health Monitoring Solutions
4.2.2 Increasing Adoption of Ai-Driven Pest and Disease Detection
4.2.3 Growing Use of Predictive Yield Forecasting Tools
4.2.4 Integration of Multi-Source Farm Data Into Unified Dashboards
4.2.5 Rising Demand for Decision-Support Systems in Precision Farming
5. Artificial Intelligence (AI) in Crop Monitoring Market Analysis of End Use Industries
5.1 Agricultural Cooperatives
5.2 Agri-Tech Companies
5.3 Government Agencies
5.4 Research Institutions
5.5 Other End Users
6. Artificial Intelligence (AI) in Crop Monitoring Market – Macro Economic Scenario Including the Impact of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, Supply Chain Impact from Tariff War & Trade Protectionism, and Covid and Recovery on the Market
7. Global Artificial Intelligence (AI) in Crop Monitoring Strategic Analysis Framework, Current Market Size, Market Comparisons and Growth Rate Analysis
7.1. Global Artificial Intelligence (AI) in Crop Monitoring PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
7.2. Global Artificial Intelligence (AI) in Crop Monitoring Market Size, Comparisons and Growth Rate Analysis
7.3. Global Artificial Intelligence (AI) in Crop Monitoring Historic Market Size and Growth, 2020 – 2025, Value ($ Billion)
7.4. Global Artificial Intelligence (AI) in Crop Monitoring Forecast Market Size and Growth, 2025 – 2030, 2035F, Value ($ Billion)
8. Global Artificial Intelligence (AI) in Crop Monitoring Total Addressable Market (TAM) Analysis for the Market
8.1. Definition and Scope of Total Addressable Market (TAM)
8.2. Methodology and Assumptions
8.3. Global Total Addressable Market (TAM) Estimation
8.4. TAM vs. Current Market Size Analysis
8.5. Strategic Insights and Growth Opportunities from TAM Analysis
Companies Featured
- International Business Machines Corporation
- CNH Industrial N.V.
- John Deere Company
- Ninjacart
- Sencrop SAS
- Raven Industries Inc.
- Prospera Technologies Inc.
- The Climate Corporation
- EOS Data Analytics Inc.
- CropIn Technology Solutions Pvt. Ltd.
- Sentera Inc.
- Farmers Edge Inc.
- Taranis Visual Ltd.
- CropX Technologies Ltd.
- Aerobotics (Pty) Ltd.
- AGRIVI Ltd.
- Farmonaut Technologies Pvt. Ltd.
- Plantix
- FlyPix AI Ltd.
- ELAI AgriTech Pvt. Ltd.
- Climate-Eyes
For more information about this report visit https://www.researchandmarkets.com/r/8bft9r
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- AI in Crop Monitoring Market
