Artificial Intelligence in Agriculture Market Research Report – Segmentation By Application (Crop and Soil Monitoring, Predictive Agricultural Analytics, Livestock Monitoring, Agriculture Robots, Drone Analytics, Precision Farming, Weather Tracking, Disease and Pest Detection, Other Applications); By Deployment (Cloud, On-premise, Hybrid);and Region; - Size, Share, Growth Analysis | Forecast (2024– 2030)
Published: 2024 - January
Report Code: IM-885
Format:
Region: Global
What is Artificial Intelligence (AI) in Agriculture?
Artificial Intelligence in Agriculture refers to the integration of AI-powered technologies such as machine learning, computer vision, and robotics into agricultural practices to enhance productivity, sustainability, and profitability. Unlike traditional mechanization, AI delivers real-time, data-driven decision-making support that redefines operational efficiency from field to fork.
AI in agriculture is reshaping conventional agronomy with disruptive technologies that offer New intelligent tools, make operations Easy with automation, ensure Safe crop monitoring, and open Big opportunities in food security and climate-resilient farming.
Market Size:
Artificial Intelligence (AI) in Agriculture Market was valued at USD 2.9 billion in 2024 and is projected to reach a market size of USD 10.04 billion by 2030 at a CAGR of 23%.
Key Market Players
• Prospera Technologies, Ltd.
• ec2ce
• Valmont Industries
• Microsoft Corporation
• PrecisionHawk
• Corteva
• Gamaya
• IBM Corporation
• Climate LLC
• Taranis
Case Study:
Prospera Technologies enabled a large tomato grower in Mexico to increase yields by 30% using AI-driven visual insights and predictive analytics—highlighting AI's USP in yield optimization without expanding acreage.
Key Statistics and Trends:
• Over 65% of large farms in North America are exploring AI-based solutions.
• AI-based drone analytics see a 40% rise in adoption YoY.
• AI in greenhouse automation is among top-funded AgriTech areas globally.
Market Segmentation:
By Type:
• Machine Learning
• Computer Vision
• Predictive Analytics
• Robotics & Automation
• Internet of Things (IoT) Integration
• Natural Language Processing (NLP)
• Remote Sensing and Satellite Imaging
• Intelligent Monitoring Systems
• Others
By End User:
• Precision Farming
• Livestock Monitoring
• Drone Analytics
• Agricultural Robotics
• Smart Greenhouses
• Soil and Crop Monitoring
• Irrigation Management
• Supply Chain Optimization
• Weather Forecasting
• Others
What’s in It for You?
• Pinpoint high-growth application areas for strategic investments
• Benchmark with innovation leaders and acquisition targets
• Understand AI’s value chain integration in agribusiness
• Identify solution white-spaces and automation gaps
• Align with regulatory and sustainability-driven tech needs
Chapter 1. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – Scope & Methodology
1.1. Market Segmentation
1.2. Scope, Assumptions & Limitations
1.3. Research Methodology
1.4. Primary Sources
1.5. Secondary Sources
Chapter 2. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – Executive Summary
2.1. Market Size & Forecast – (2024 – 2030) ($M/$Bn)
2.2. Key Trends & Insights
2.2.1. Demand Side
2.2.2. Supply Side
2.4. Attractive Investment Propositions
2.5. COVID-19 Impact Analysis
Chapter 3. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – Competition Scenario
3.1. Market Share Analysis & Company Benchmarking
3.2. Competitive Strategy & Development Scenario
3.3. Competitive Pricing Analysis
3.4. Supplier-Distributor Analysis
Chapter 4. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET - Entry Scenario
4.1. Regulatory Scenario
4.2. Case Studies – Key Start-ups
4.3. Customer Analysis
4.5. PESTLE Analysis
4.4. Porters Five Force Model
4.4.1. Bargaining Power of Suppliers
4.4.2. Bargaining Powers of Customers
4.4.3. Threat of New Entrants
4.4.4. Rivalry among Existing Players
4.4.5. Threat of Substitutes
Chapter 5. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET - Landscape
5.1. Value Chain Analysis – Key Stakeholders Impact Analysis
5.2. Market Drivers
5.3. Market Restraints/Challenges
5.4. Market Opportunities
Chapter 6. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – By Deployment 6.1. Introduction/Key Findings
6.2. Cloud
6.3. On-premise
6.4. Hybrid
6.5. Y-O-Y Growth trend Analysis By Deployment
6.6. Absolute $ Opportunity Analysis By Deployment , 2024-2030
Chapter 7. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – By Application
7.1. Introduction/Key Findings
7.2. Crop and Soil Monitoring
7.3. Predictive Agricultural Analytics
7.4. Livestock Monitoring
7.5. Agriculture Robots
7.6. Drone Analytics
7.7. Precision Farming
7.8. Weather Tracking
7.9. Disease and Pest Detection
7.10. Other Applications
7.11. Y-O-Y Growth trend Analysis By Application
7.12. Absolute $ Opportunity Analysis By Application , 2024-2030
Chapter 8. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET - By Geography – Market Size, Forecast, Trends & Insights
8.1. North America
8.1.1. By Country
8.1.1.1. U.S.A.
8.1.1.2. Canada
8.1.1.3. Mexico
8.1.2. By Application
8.1.3. By Deployment
8.1.5. Countries & Segments - Market Attractiveness Analysis
8.2. Europe
8.2.1. By Country
8.2.1.1. U.K.
8.2.1.2. Germany
8.2.1.3. France
8.2.1.4. Italy
8.2.1.5. Spain
8.2.1.6. Rest of Europe
8.2.2. By Application
8.2.3. By Deployment
8.2.4. Countries & Segments - Market Attractiveness Analysis
8.3. Asia Pacific
8.3.1. By Country
8.3.1.1. China
8.3.1.2. Japan
8.3.1.3. South Korea
8.3.1.4. India
8.3.1.5. Australia & New Zealand
8.3.1.6. Rest of Asia-Pacific
8.3.2. By Application
8.3.3. By Deployment
8.3.4. Countries & Segments - Market Attractiveness Analysis
8.4. South America
8.4.1. By Country
8.4.1.1. Brazil
8.4.1.2. Argentina
8.4.1.3. Colombia
8.4.1.4. Chile
8.4.1.5. Rest of South America
8.4.2. By Application
8.4.3. By Deployment
8.4.4. Countries & Segments - Market Attractiveness Analysis
8.5. Middle East & Africa
8.5.1. By Country
8.5.1.1. United Arab Emirates (UAE)
8.5.1.2. Saudi Arabia
8.5.1.3. Qatar
8.5.1.4. Israel
8.5.1.5. South Africa
8.5.1.6. Nigeria
8.5.1.7. Kenya
8.5.1.8. Egypt
8.5.1.8. Rest of MEA
8.5.2. By Application
8.5.3. By Deployment
8.5.4. Countries & Segments - Market Attractiveness Analysis
Chapter 9. GLOBAL ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET – Company Profiles – (Overview, Product Portfolio, Financials, Strategies & Developments)
9.1 Microsoft
9.2. IBM
9.3. John Deere
9.4. The Climate Corporation
9.5. Bayer Crop Science
9.6. BASF
9.7. Syngenta Crop Protection
9.8. Trimble Inc.
9.9. Raven Industries
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Frequently Asked Questions
The Global Artificial Intelligence in Agriculture Market was valued at USD 2.05 Billion and is projected to reach a market size of USD 9.09 Billion by the end of 2030. Over the forecast period of 2024-2030, the market is projected to grow at a CAGR of 23.7%.
Microsoft, IBM, John Deere, The Climate Corporation, Bayer Crop Science, BASF, Syngenta Crop Protection, Trimble Inc., Raven Industries.
The fastest-growing region in the Global AI In Agriculture Market is Middle East and Africa.
North America accounts for the largest market share in the Global Artificial Intelligence in Agriculture Market
Growing demand for high-quality agricultural production, supportive government policies, and widespread industrialization fuel the global AI in agriculture market.
