AI in Precision Farming Market Size, Share, Opportunities, and Trends By Technology (Machine Learning, Computer Vision, Predictive Analytics, AI-powered Robotics, Others), By Application (Crop Health Monitoring, Soil Health Monitoring, Disease and Pest Detection, Irrigation Optimization, Climate and Weather Forecast, Others), And By Geography – Forecasts From 2025 To 2030

AI in Precision Farming Market Size:

The AI in Precision Farming Market is expected to grow at a CAGR of 16.64%, reaching a market size of US$3.748 billion in 2030 from US$1.736 billion in 2025.

Precision farming is a farming technique that uses technologies including IoT, remote sensing, Geographic Information Systems and artificial intelligence to monitor and manage variability within the agricultural field. It leverages data insights from technologies such as soil health analysis, water usage optimization for irrigation, pest and disease control, and crop management among others. It refers to a method of farming that is about more efficient utilization of agricultural resources that is data-driven and environmentally sustainable.

Artificial Intelligence is increasingly being adopted in precision farming, driving a paradigm shift in managing and utilizing agricultural resources more effectively and efficiently. It is used for finding out anomalies and patterns in crop growth, and soil health, offering more accurate decision-making capabilities. For example, AI-powered drones and image recognition software and tools are used for crop health monitoring, detecting the early signs of diseases and pests. Also, it is used for predictive analytics by analyzing the historical data and weather patterns for estimating the yield and thus, helping in the efficient management afterwards such as harvesting, storage and marketing strategies. Various artificial intelligence technologies such as machine learning, computer vision, natural language processing and predictive analytics are used to enhance the efficiency and accuracy of data for making precision farming more cost-effective and more productive.

Several factors are driving the market growth of precision farming such as increasing demand for food production with the rising global population, ultimately driving the market growth of AI in precision farming. Alongside, the increasing technological advancement in artificial intelligence and other technologies such as IoT is driving the growth of precision farming as it is offering more enhanced benefits to precision farming. The rising environmental concerns amidst the rising climate change is driving the demand for more judicious and sustainable use of resources including agricultural resources, driving the market growth of the AI in the precision farming market.

What are the AI in Precision Farming Market Drivers?

• Rising AI adoption across the agricultural sector to meet the growing demand for food production

The demand for food production is growing globally due to the rise in population. To meet the growing demand for food production, there is an increasing trend in the adoption of artificial intelligence technologies for optimizing crop yield by analyzing vast amounts of historical data, understanding weather patterns, analyzing soil health, and optimizing irrigation that helps ensure higher yield. For instance, a smart sprayer, developed by Blue River Technology utilizes a vision-based system and artificial intelligence to detect weeds and plants and spray the herbicide on weeds only. It is said by the company that it reduces the required quantity of herbicide by more than 90% compared to traditional broadcast sprayers. This highlights the effectiveness of artificial intelligence in precision farming. Also, artificial intelligence helps in reducing wastage during precision farming. Thus, the growing AI adoption for the benefits is driving the market of AI in precision Farming.

• Increasing technological development is driving the market

There is increasing technological development in artificial intelligence such as advanced predictive analytics which is driving its usage in precision farming. Apart from artificial intelligence, there is development in other technologies also such as the Internet of Things and remote sensors that is also boosting the use of AI in precision farming due to the integration of IoT with artificial intelligence.

Segment Analysis of the AI in Precision Farming Market:

• By technology, machine learning has a significant market share

Machine learning technology is widely used to offer insights. Its algorithms analyse the vast amount of data collected from various sources including IoT devices, sensors, drones etc. And offer valuable actionable insights. It is used for various applications such as soil health analysis, crop health analysis and others. It is also integrated with other technologies offering key insights. Thus, the segment of machine learning based on technology is anticipated to continue holding a major share in the AI in the precision farming market. 

What key geographical trends are shaping AI in the Precision Farming Market?

• The market is anticipated to be dominated by North America

Based on Geography, In the AI precision farming market, North America is anticipated to dominate the market. The United States of America and Canada will be driving the growth due to the presence of large-scale farms in these regions. This region also has greater adoption of technology by farmers. The increasing investment in research and development of artificial intelligence is making this region a leader in the adoption of advanced technologies.

The European market will also witness significant growth in the AI in the precision farming. The growing demand for sustainable farming along with rising initiatives by the government for digital farming is driving the market.

The Asia Pacific region will witness growth in the market during the forecast period due to the increasing adoption of AI for precision farming by countries like China, Japan, South Korea, India and others, due to increasing population and growing economy. Also, there are increased investments by the governments for modernizing agriculture.

Recent Developments in the AI in Precision Farming Market:

• In September 2024, Garuda Aerospace partnered with Agrowing, a global sensor and imagery company, to enhance their aerial precision agriculture with advanced deep learning technology in India.  Garuda’s Aerospace’s Kisan Drones will be offered to farmers through this partnership.
• In April 2024, AGCO Corporation launched a new brand for precision agriculture portfolio that is PTx. This new brand combines the precision agricultural technologies of AGCO’s tech stack i.e., Precision Planting and PTx Trimble.

AI in Precision Farming Market Scope:

Report Metric	Details
AI in Precision Farming Market Size in 2025	US$1.736 billion
AI in Precision Farming Market Size in 2030	US$3.748 billion
Growth Rate	CAGR of 16.64%
Study Period	2020 to 2030
Historical Data	2020 to 2023
Base Year	2024
Forecast Period	2025 – 2030
Forecast Unit (Value)	USD Billion
Segmentation	Technology Application Geography
Geographical Segmentation	North America, South America, Europe, Middle East and Africa, Asia Pacific
List of Major Companies in the AI in Precision Farming Market	Deere & Company CNH Industrial N.V. Trimble Inc. AGCO Corporation IBM Corporation
Customization Scope	Free report customization with purchase

 

The AI in Precision Farming Market is analysed into the following segments:

• By Technology
  • Machine Learning
  • Computer Vision
  • Predictive Analytics
  • AI-powered Robotics
  • Others
• By Application
  • Crop Health Monitoring
  • Soil Health Monitoring
  • Disease and Pest Detection
  • Irrigation optimization
  • Climate and Weather Forecast
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • China
    • Japan
    • South Korea
    • Australia
    • India
    • Indonesia
    • Thailand
    • Others

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1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View 

5. AI IN PRECISION FARMING MARKET BY TECHNOLOGY 

5.1. Introduction

5.2. Machine Learning

5.3. Computer Vision

5.4. Predictive Analytics

5.5. AI-powered Robotics 

5.6. Others

6. AI IN PRECISION FARMING MARKET BY APPLICATION

6.1. Introduction

6.2. Crop Health Monitoring

6.3. Soil Health Monitoring

6.4. Disease and Pest Detection

6.5. Irrigation optimization 

6.6. Climate and Weather Forecast 

6.7. Others 

7. AI IN PRECISION FARMING MARKET BY GEOGRAPHY

7.1. Introduction

7.2. North America

7.2.1. By Technology

7.2.2. By Application

7.2.3. By Country

7.2.3.1. USA

7.2.3.2. Canada

7.2.3.3. Mexico

7.3. South America

7.3.1. By Technology

7.3.2. By Application

7.3.3. By Country

7.3.3.1. Brazil

7.3.3.2. Argentina

7.3.3.3. Others

7.4. Europe

7.4.1. By Technology

7.4.2. By Application

7.4.3. By Country

7.4.3.1. United Kingdom

7.4.3.2. Germany

7.4.3.3. France

7.4.3.4. Spain

7.4.3.5. Others

7.5. Middle East and Africa

7.5.1. By Technology

7.5.2. By Application

7.5.3. By Country

7.5.3.1. Saudi Arabia

7.5.3.2. UAE

7.5.3.3. Others

7.6. Asia Pacific

7.6.1. By Technology

7.6.2. By Application

7.6.3. By Country

7.6.3.1. China

7.6.3.2. Japan

7.6.3.3. South Korea

7.6.3.4. Australia

7.6.3.5. India

7.6.3.6. Indonesia

7.6.3.7. Thailand

7.6.3.8. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisitions, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. Deere & Company 

9.2. CNH Industrial N.V. 

9.3. Trimble Inc.

9.4. AGCO Corporation

9.5. IBM Corporation

9.6. BASF

9.7. Raven Industries Inc.

9.8. Corteva Agriscience

9.9. AgEagle Aerial Systems Inc.

9.10. The Climate Corporation (Bayer AG)

Deere & Company 

CNH Industrial N.V. 

Trimble Inc.

AGCO Corporation

IBM Corporation

BASF

Raven Industries Inc.

Corteva Agriscience

AgEagle Aerial Systems Inc.

The Climate Corporation (Bayer AG)