세계의 농업용 AI 시장

The global market for AI in agriculture is estimated to grow from $2.8 billion in 2025 to reach $8.5 billion by the end of 2030, at a compound annual growth rate (CAGR) of 25.1% from 2025 through 2030.

The North American market for AI in agriculture is estimated to grow from $999.7 million in 2025 to reach $3.1 billion by the end of 2030, at a CAGR of 25.6% from 2025 through 2030.

The Asia-Pacific market for AI in agriculture is estimated to grow from $662 million in 2025 to reach $2.5 billion by the end of 2030, at a CAGR of 30.3% from 2025 through 2030.

Report Scope

This report presents qualitative and quantitative data on the current market dynamics and trends in the global market for AI in agriculture. The report also assesses recent technological developments and software performance. Analyses of the most popular software, new product approvals and emerging technologies are also included. The market prospects for four regions-North America, Europe, Asia-Pacific, the Middle East and Africa, and South America-are discussed. The report also includes profiles of leading companies and their strategies.

This in-depth analysis of the global AI in agriculture market, emphasizing the major driving forces and emerging technologies shaping this rapidly evolving field, explores how AI transforms agriculture through enhanced technologies, such as drone-based and predictive analytics and crop monitoring. It also examines AI disruption across industry verticals and value chain stages, while presenting market spending patterns, investment forecasts, expenditures of major companies and venture capital funding in AI-driven technologies. The market is divided based on components, applications, technology and region. Based on components, the market is segmented into software, hardware and services. Based on technology, the market is segmented into natural language processing, machine learning, computer vision and predictive analysis. Based on applications, the market is segmented into precision farming, drone analytics, agricultural robots, livestock monitoring and others. For market estimates, data has been provided for 2024 as the base year, with estimates for 2025 and forecasts for 2025 through 2030.

Report Includes

• 42 data tables and 54 additional tables
• Overview and an analysis of the global market for AI in the agriculture sector
• Analyses of the global market trends, with revenue data for 2024, estimates for 2025, and projections of compound annual growth rates (CAGRs) through 2030
• Estimates of the market's size and revenue growth prospects, accompanied by a market share analysis by components, technology, application and region
• Facts and figures pertaining to market dynamics, opportunities and deterrents, technological advances, regulations, innovations and standards and the impacts of macroeconomic variables
• Impact analysis of U.S. tariff laws on the industry
• Insights derived from Porter's Five Forces model, as well as a global supply chain analysis
• Case studies on AI implementation to improve processes and business operations in the sector
• Overview of sustainability trends and ESG developments, with emphasis on consumer attitudes, as well as the ESG risk ratings and practices of leading companies
• Analysis of the industry structure, including companies' market shares and rankings, strategic initiatives, M&A activity and a venture funding outlook
• Profiles of the leading companies, including Microsoft, IBM Corp., Deere & Co., Syngenta AG and Bayer CropScience

Table of Contents

Chapter 1 Executive Summary

• Market Outlook
• Scope of Report
• Market Summary
• Market Dynamics and Growth Factors
• Emerging Technologies
• Segmental Analysis
• Regional Analysis
• Conclusion

Chapter 2 Market Overview

• Overview
• Macroeconomic Factors Analysis
• Government Policy and Regulation
• Technological Infrastructure and Digital Readiness
• Global Trade and Supply Chain Dynamics
• Impact of U.S. Tariffs
• Porter's Five Forces Analysis
• Potential for New Entrants (Moderate)
• Bargaining Power of Suppliers (High)
• Bargaining Power of Buyers (High)
• Threat of Substitute Products or Services (Moderate)
• Level of Industry Competitiveness (High)
• AI Impact on the Agricultural Value Chain
• Development of New Seed Varieties, Herbicides or Fertilizers -- Accelerated Innovation
• Automated Growing and Production Practices
• Processing, Packaging and Storage
• Distribution to End Users and Retailers
• Use Cases
• Use Case 1: Optimizing Automated Irrigation Systems
• Use Case 2: Automated Weed Control Systems
• Use Case 3: Livestock Health Monitoring
• Use Case 4: Automated Pest Control Systems
• Use Case 5: Crop Yield Visualization and Forecasting

Chapter 3 Market Dynamics

• Overview
• Market Drivers
• Adoption Is Driven by Labor Shortages and Escalating Labor Costs
• Adoption of Drone-based Weed and Pest Management
• Market Restraints
• Infrastructure Gaps in Developing Regions Hinder the Widespread Use of AI in Agriculture
• Data-Related Challenges Impact the Scaling of AI in Agriculture
• Market Opportunities
• Start-Ups and AgTech Investments Drive AI Adoption in Agriculture
• Greenhouse Farming Offers Opportunity for AI in Agriculture
• Market Challenges
• High Implementation Costs

Chapter 4 Regulatory Landscape

• Overview
• Regulatory Scenario of AI in Agriculture

Chapter 5 Emerging Trends and Patent Analysis

• Emerging Technology
• Internet of Things and Edge AI
• Natural Language Processing
• Generative AI in Agriculture
• Patent Analysis
• Key Findings
• Overview

Chapter 6 Market Segmentation Analysis

• Segmentation Breakdown
• Market Analysis by Components
• Key Takeaways
• Software
• Services
• Hardware
• Market Analysis by Technology
• Key Takeaways
• Machine Learning
• Computer Vision
• Natural Language Processing
• Predictive Analytics
• Market Analysis by Application
• Key Takeaways
• Precision Farming
• Drone Analytics
• Agricultural Robots
• Livestock Monitoring
• Other Applications
• Geographic Breakdown
• Market Analysis by Region
• Key Takeaways
• North America
• Europe
• Asia-Pacific
• Middle East and Africa
• South America

Chapter 7 Competitive Intelligence

• Key Takeaways
• Competitive Analysis
• Strategic Analysis
• Investment Landscape

Chapter 8 Sustainability in AI in the Agriculture Industry: ESG Perspective

• Introduction to ESG
• Sustainability Trends and Initiatives in AI in the Agriculture Industry
• ESG Risk Ratings
• Concluding Remarks from BCC Research

Chapter 9 Appendix

• Research Methodology
• Sources
• Abbreviations
• Company Profiles
• AEROBOTICS PTY. LTD.
• BAYER AG
• CROPIN TECHNOLOGY SOLUTIONS PVT. LTD.
• CROPX INC.
• DEERE & CO.
• EAGLENXT
• ECOROBOTIX
• GAMAYA
• IBM CORP.
• INTELLIAS
• MICROSOFT
• N-IX LLC.
• SYNGENTA AG
• TARANIS
• TRIMBLE INC.
• Emerging Start-ups/Market Disruptors