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 agriculture industry is experiencing a major revolution due to widespread AI adoption along its entire value chain. AI has shifted from a futurist concept to a crucial strategic tool, impacting areas such as weather forecasting, crop monitoring, pest detection, drone pest control, food sorting and livestock monitoring. Beyond R&D, AI improves farming efficiency through predictive analytics and quality checks, revolutionizes crop management, boosts yield with precision farming, supports data-driven decisions, cuts costs for pest and disease control and labor, and promotes more sustainable farming methods. Although challenges like data integration, regulations and skilled workforce shortages persist, clear benefits and a growing number of applications highlight a trend where AI is becoming essential for innovation and gaining a competitive edge in agriculture.
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.
The agriculture industry is experiencing a major revolution due to widespread AI adoption along its entire value chain. AI has shifted from a futurist concept to a crucial strategic tool, impacting areas such as weather forecasting, crop monitoring, pest detection, drone pest control, food sorting and livestock monitoring. Beyond R&D, AI improves farming efficiency through predictive analytics and quality checks, revolutionizes crop management, boosts yield with precision farming, supports data-driven decisions, cuts costs for pest and disease control and labor, and promotes more sustainable farming methods. Although challenges like data integration, regulations and skilled workforce shortages persist, clear benefits and a growing number of applications highlight a trend where AI is becoming essential for innovation and gaining a competitive edge in agriculture.
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.
The 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
Chapter 2 Market Overview
Chapter 3 Market Dynamics
Chapter 4 Regulatory Landscape
Chapter 5 Emerging Trends and Patent Analysis
Chapter 6 Market Segmentation Analysis
Chapter 7 Competitive Intelligence
Chapter 8 Sustainability in AI in the Agriculture Industry: ESG Perspective
Chapter 9 Appendix
List of Tables
List of Figures
Companies Mentioned
- 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.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 124 |
| Published | November 2025 |
| Forecast Period | 2025 - 2030 |
| Estimated Market Value ( USD | $ 2.8 Billion |
| Forecasted Market Value ( USD | $ 8.5 Billion |
| Compound Annual Growth Rate | 25.1% |
| Regions Covered | Global |
| No. of Companies Mentioned | 15 |
