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AI In Precision Farming Market On Course To Reach $2.08 Billion By 2030: Size And Growth Overview
The market for ai in precision farming has seen rapid expansion in recent years. It is anticipated to expand from $0.94 billion in 2025 to $1.12 billion in 2026, achieving a compound annual growth rate (CAGR) of 19.8%. The increase observed in previous periods is linked to factors such as increasing inefficiencies in traditional farming methods, heightened pressures from pests and diseases, the rising adoption of early digital instruments, increasing expenditures on agricultural inputs, and the broadened scope of commercial farming operations.
The ai in precision farming market size is projected to experience significant expansion in the coming years. It is forecast to reach $2.08 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 16.7%. This growth over the forecast period is driven by the increasing need for sustainable farming practices, the rising adoption of AI-based analytics, the expanding deployment of precision agriculture tools, the growth of connected farm ecosystems, and the heightened demand for optimized crop yields. Prominent trends for this period include a growing demand for data-driven crop optimization, the increasing use of automated field monitoring tools, wider adoption of precision soil and input management, the expansion of smart irrigation and resource efficiency practices, and an enhanced focus on minimizing crop loss through early detection technologies.
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AI In Precision Farming Market Growth Factors: What Is Strengthening Demand Worldwide?
The restricted supply of cultivable land is anticipated to drive the expansion of the AI in precision farming market in the future. Cultivable land denotes areas suitable for agricultural purposes, particularly for crop production. The scarcity of cultivable land stems from various elements such as urbanization, the deterioration of soil quality, and the impacts of climate change. Within precision farming, AI tackles the issue of scarce cultivable land by optimizing resource utilization and boosting crop yield via data-driven strategies and focused actions. As an illustration, data from August 2023, provided by The U.S. Department of Agriculture (USDA), a US-based government entity, indicates that in 2023, the mean value of U.S. farm real estate, encompassing all agricultural land and structures, reached $4,080 per acre. This represented a rise of $280 per acre, or 7.4%, when contrasted with values from 2022. Consequently, the scarcity of cultivable land is fostering the expansion of the AI in precision farming market.
AI In Precision Farming Market By Segment: Complete Category And Subcategory Breakdown
The AI in precision farming market covered in this report is segmented –
1) By Type: Machine Learning, Computer Vision, Other Types
2) By Offering: Hardware, Software, AI-as-a-Service, Service
3) By Application: Experimental Study, Farm Management, Private Planting, Other Applications
Subsegments:
1) By Machine Learning: Predictive Analytics For Crop Yields, Soil Quality Monitoring, Pest And Disease Detection, Crop Growth Prediction
2) By Computer Vision: Crop And Weed Identification, Field Monitoring Through Drones, Crop Damage Detection, Automated Harvesting Systems
3) By Other Types: Robotics In Farming, Natural Language Processing (NLP) For Farm Data Analysis, AI-Powered Irrigation Systems
AI In Precision Farming Market Trend Outlook: Developments Defining The Forecast Period
Leading companies in the artificial intelligence (AI) in the precision farming market are focusing on developing technological advancements, such as digital agronomy platforms, to enhance data-driven crop management, optimize resource utilization, and improve overall farm productivity. A digital agronomy platform refers to an integrated software system that combines data analytics, remote sensing, and AI technologies to provide real-time insights and decision support for optimizing crop production and farm management practices. For instance, in January 2023, Precision Planting, a US-based agricultural technology company, launched a new data app for farmers called Panorama. It provides farmers with easy access to detailed agronomic data from the Gen 3 20|20 monitor, allowing them to view row-by-row maps, field reports, and yield comparisons on their phone or computer. This simplifies data management by automatically syncing data and enabling remote support from dealers, helping farmers make better-informed decisions for planting and crop management. The app’s purpose is to give an unobstructed, portable view of farm data to optimize efficiency and improve overall crop performance.
Who Is Competing For Share In The AI In Precision Farming Market?
Major companies operating in the ai in precision farming market are Microsoft Corporation, Robert Bosch GmbH, Intel Corporation, International Business Machines Corporation, Bayer AG, Deere & Company, SAP SE, Yara International ASA, DTN LLC, FarmWise Labs Inc., Taranis Visual Ltd., Blue River Technology Inc., Agworld Inc., Ceres Imaging Inc., PrecisionHawk Inc., FarmLogs Inc., Prospera Technologies Ltd., Arable Labs Inc., Agribotix LLC, Resson Aerospace Corporation
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AI In Precision Farming Market Regional Snapshot: Leading Geography In 2025
North America was the largest region in the AI in precision farming market in 2025. Europe is expected to be the fastest-growing region in the forecast period. The regions covered in the ai in precision farming market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
