AI in Agriculture Market Size, Share and Trends 2026 to 2035

According to MarketnReports, the global AI in Agriculture market size was estimated at USD 2.57 billion in 2025 and is expected to reach USD 20.12 billion by 2035, growing at a CAGR of 22.85% from 2026 to 2035. Increasing demand for precision farming and sustainable agricultural practices.

Key Insights

  • The global AI in agriculture market size was valued at USD 2.57 billion in 2025 and is projected to reach USD 20.12 billion by 2035.
  • The market is anticipated to grow at a CAGR of 22.85% during the forecast period from 2026 to 2035.
  • The market is driven by rising food demand, labor shortages, and the adoption of precision farming technologies.
  • Machine Learning dominates the type segment with a 45% share due to its versatility in analyzing data for predictions and optimizations across farming processes.
  • Precision Farming dominates the application segment with a 45% share because it enables resource-efficient practices that boost yields and reduce costs in large-scale operations.
  • Agricultural Enterprises dominate the end-use segment with a 50% share owing to their scale and investment capacity in AI for integrated farm management.
  • North America dominates the regional segment with a 36% share attributable to advanced technological infrastructure, high R&D investments, and supportive government policies.

What is the AI in Agriculture Market?

The AI in agriculture market refers to the integration of artificial intelligence technologies into farming practices to enhance efficiency, productivity, and sustainability through data-driven insights and automation. This includes applications like predictive analytics for crop yields, machine learning for pest detection, and computer vision for monitoring livestock health. The market definition encompasses software, hardware, and services that leverage AI to optimize resource use, reduce waste, and improve decision-making in agricultural operations, excluding general IT tools, and focuses on innovations that address challenges like labor shortages and climate variability in global food production.

Market Dynamics

Growth Drivers

The growth drivers in the AI in agriculture market are fueled by the escalating global population and the consequent need for higher food production, where AI enables precision techniques to maximize yields with minimal resources. Technological advancements in sensors, drones, and data analytics lower barriers to adoption, allowing farmers to make informed decisions on planting, irrigation, and harvesting. Government initiatives promoting sustainable farming and subsidies for digital tools further accelerate market expansion, as they align with environmental goals to reduce chemical usage and water waste.

Restraints

Restraints in the AI in agriculture market include high initial implementation costs for hardware and software, which limit accessibility for smallholder farmers in developing regions. Data privacy concerns and the lack of standardized interoperability between systems hinder seamless integration and trust in AI solutions. Additionally, inadequate rural internet connectivity and skilled labor shortages impede real-time data processing and effective utilization of advanced technologies.

Opportunities

Opportunities in the AI in agriculture market emerge from the integration of AI with IoT and blockchain for traceable supply chains, enhancing transparency and efficiency in global trade. Expansion into emerging economies with growing agricultural sectors offers potential through affordable, mobile-based AI tools tailored for small farms. Collaborations between tech firms and agribusinesses can drive innovations in climate-resilient crops and automated systems, capitalizing on sustainability trends.

Challenges

Challenges in the AI in agriculture market involve addressing data quality issues, as inaccurate inputs from varying field conditions can lead to flawed predictions and decisions. Regulatory hurdles related to AI ethics and environmental impact assessments delay deployments in sensitive areas. Moreover, resistance to technology adoption among traditional farmers requires education and demonstration of ROI to overcome cultural barriers.

AI in Agriculture Market: Report Scope

Report Attributes Report Details
Report Name AI in Agriculture Market
Market Size 2025 USD 2.57 Billion
Market Forecast 2035 USD 20.12 Billion
Growth Rate CAGR of 22.85%
Report Pages 220
Key Companies Covered

Deere & Company, IBM Corporation, Microsoft Corporation, The Climate Corporation, Farmers Edge Inc., and Others
Segments Covered By Type, By Application, By End-Use, and By Region
Regions Covered North America, Europe, Asia Pacific (APAC), Latin America, and The Middle East and Africa (MEA)
Base Year 2025
Historical Year 2020 - 2024
Forecast Year 2026 - 2035
Customization Scope Avail customized purchase options to meet your exact research needs.

Market Segmentation

The AI in Agriculture market is segmented by type, application, end-use, and region.

Based on Type Segment, Machine Learning is the most dominant subsegment, holding 45% market share, followed by Computer Vision at around 25%. Machine Learning leads due to its core role in processing vast datasets for predictive modeling and optimization, which drives market growth by enabling scalable solutions that improve farm efficiency and decision-making across diverse agricultural operations.

Based on Application Segment, Precision Farming is the most dominant subsegment with 45% share, followed by Crop Monitoring at 20%. Precision Farming dominates because it integrates multiple AI tools for targeted resource application, thereby propelling overall market expansion through significant cost savings and yield improvements in response to global food security needs.

Based on the End-Use Segment, Agricultural Enterprises is the most dominant subsegment at 50%, followed by Farmers at 30%. Agricultural Enterprises lead owing to their ability to invest in comprehensive AI systems for large-scale management, which fuels market growth by demonstrating high ROI and encouraging broader adoption.

Recent Developments

  • In February 2025, AGCO Corporation acquired 85% of Trimble’s agriculture business for USD 2 billion, forming PTx Trimble to advance AI-driven precision farming and autonomous technologies.
  • In April 2025, Aigen launched its Generation-2 Element robots for weeding, featuring enhanced AI compute and stereo vision for improved accuracy in crops like cotton and beets.
  • In March 2025, Bindwell raised USD 500K in pre-seed funding to accelerate AI-powered pesticide discovery, achieving results 4x faster than traditional methods.

North America to Dominate the Global Market

  • North America is poised to dominate the global AI in agriculture market

North America as the dominant country, driven by major players like John Deere and substantial USDA investments in AI for precision farming, addressing large-scale crop production in regions like the Midwest.

Canada contributes through government programs promoting digital agriculture, focusing on AI for sustainable practices in prairie provinces amid climate challenges.

Europe holds a strong position with EU funding for green tech, led by Germany and the Netherlands in AI for greenhouse optimization and livestock monitoring.

Asia Pacific shows rapid growth, with China dominating via state-backed initiatives integrating AI in rice and vegetable farming across vast rural areas.

Latin America and the Middle East & Africa emerge, led by Brazil and Israel, where AI addresses water scarcity and boosts export-oriented agriculture.

Key Market Players and Strategies

  • Deere & Company focuses on acquisitions like Blue River Technology and investments in autonomous machinery to enhance precision farming solutions.
  • IBM Corporation leverages Watson AI for predictive analytics, partnering with agribusinesses to provide cloud-based crop management tools.
  • Microsoft Corporation advances FarmBeats platform, emphasizing IoT and AI integration for affordable, data-driven farming in emerging markets.
  • The Climate Corporation (Bayer) develops FieldView for digital agronomy, using AI to optimize seed selection and climate risk management.
  • Farmers Edge Inc. pursues satellite imagery and AI analytics, offering customized insights to improve yield and sustainability for global farmers.

Market Trends

  • Increasing adoption of generative AI for decision support and predictive modeling.
  • Growth in drone analytics and robotics for real-time monitoring and automation.
  • Focus on sustainable practices through AI-driven resource optimization.
  • Integration of AI with IoT for enhanced data connectivity in remote areas.
  • Rise in agentic AI for autonomous farm operations and risk mitigation.

Market Segments and their Subsegments Covered in the Report

By Type

  • Machine Learning
  • Computer Vision
  • Predictive Analytics
  • Robotics
  • IoT Integration
  • Natural Language Processing
  • Deep Learning
  • Image Recognition
  • Speech Recognition
  • Sensor Data Analysis
  • Others

By Application

  • Precision Farming
  • Crop Monitoring
  • Livestock Monitoring
  • Drone Analytics
  • Agricultural Robots
  • Soil Management
  • Irrigation Management
  • Weather Forecasting
  • Yield Prediction
  • Pest Detection
  • Others

By End-Use

  • Farmers
  • Agricultural Enterprises
  • Government Agencies
  • Research Institutions
  • Agribusiness Companies
  • Cooperatives
  • Others
  • Others

By Region

  • North America
    • U.S.
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Rest of Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • Rest of Asia Pacific
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Middle East & Africa
    • UAE
    • South Africa
    • Rest of Middle East & Africa

Frequently Asked Questions

AI in agriculture refers to technologies using machine learning, computer vision, and analytics to optimize farming practices and enhance productivity.

Key factors include population growth, labor shortages, precision farming adoption, and sustainability initiatives.

The market is projected to grow from approximately USD 3.17 billion in 2026 to USD 20.12 billion by 2035.

The CAGR is expected to be 22.85% during the forecast period.

North America will contribute the most, driven by technological advancements and investments.

Major players include Deere & Company, IBM Corporation, Microsoft Corporation, The Climate Corporation, and Farmers Edge Inc.

The report provides insights on size, trends, segments, regions, players, and forecasts.

Stages include data collection, algorithm development, hardware integration, deployment, and maintenance.

Trends focus on automation and sustainability, with preferences for cost-effective, eco-friendly solutions.

Government subsidies for digital farming and regulations on sustainable practices drive adoption.