Artificial Intelligence in Agriculture Market : Trends, Analysis, and Competitive Landscape 2025

This Artificial Intelligence in Agriculture market report has been prepared by considering several fragments of the present Artificial Intelligence in Agriculture market and upcoming market scenario. The market insights gained through this market research analysis report facilitates more clear understanding of the market landscape, issues that may interrupt in the future, and ways to position definite brand excellently. It consists of most-detailed market segmentation, thorough analysis of major market players, trends in consumer and supply chain dynamics, and insights about new geographical markets. The market insights covered in the Artificial Intelligence in Agriculture report simplifies managing marketing of goods and services effectively.

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Market Overview:

Artificial Intelligence in Agriculture encompasses the use of advanced technologies—such as machine learning, computer vision, and robotics—to optimize farming workflows, elevate crop monitoring, bolster yield prediction, enhance decision-making, and improve supply chain efficiency.

The global AI in Agriculture Market is projected to grow from USD 1.75 billion in 2023 to USD 8.57 billion by 2031, registering a CAGR of 22.4% during the forecast period of 2024–2031.

Some of the major players operating in the Artificial Intelligence in Agriculture market include:

Deere & Company, IBM, Microsoft, OpenAI, Open Text Corporation, ClimateAi, AgEagle Aerial Systems Inc., CNH Industrial N.V., AGCO Corporation, KUBOTA Corporation, YANMAR HOLDINGS CO., LTD., DeLaval, Lely, Raven Industries, Inc., Gamaya, Bayer AG, VALMONT INDUSTRIES, INC., Cisco Systems, Inc., Oracle, Harvest CROO Robotics LLC, ADM, SYNGENTA GLOBAL, Corteva, and Bowery Farming Inc.

Global Artificial Intelligence in Agriculture Market Scope

The AI in Agriculture market is comprehensively segmented by offering, technology, application, deployment mode, end user, and geography—offering clarity across dimensions to help you identify target priorities:

Offering

Hardware
Software
Services

Technology

Machine Learning (ML)
Computer Vision
Natural Language Processing (NLP)
Robotics & Automation
Others

Application

Precision Farming
Livestock Monitoring
Weather Forecasting
Soil Management
Crop Health Monitoring
Supply Chain Optimization
Others

Deployment Mode

Cloud
On-Premise

End User

Farms
Agro-Tech Companies
Agrochemical Companies
Research Institutes
Others

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Table of Content:

Part 01: Executive Summary
Part 02: Scope of the Report
Part 03: Global Artificial Intelligence in Agriculture Market Landscape
Part 04: Global Artificial Intelligence in Agriculture Market Sizing
Part 05: Global Artificial Intelligence in Agriculture Market Segmentation By Offering
Part 06: Five Forces Analysis
Part 07: Customer Landscape
Part 08: Geographic Landscape
Part 09: Decision Framework
Part 10: Drivers and Challenges
Part 11: Market Trends
Part 12: Vendor Landscape
Part 13: Vendor Analysis