농업용 AI 시장 : 전망(2024-2029년)

The AI for agriculture market is expected to grow at a CAGR of 24.57%, reaching a market size of US$6,062.706 million in 2029 from US$2,021.502 million in 2024.

Variables on temperature, soil, water use, weather, etc., are generated daily by farms. Artificial intelligence (AI) and machine learning models use this data in real-time to derive insightful conclusions, including determining the optimal time for planting seeds, selecting crops, choosing hybrid seeds for higher yields, and other agricultural decisions. Precision farming, also called intelligent systems, helps improve the general value and precision of yields. AI helps to identify infestations, plant diseases, and malnourishment in farms. AI sensors can detect and target weeds before choosing which herbicide to apply in a region.

Many technical firms created robots that accurately monitor weeds with spray guns using image processing techniques and artificial intelligence. These robots can lower the price of herbicides by eliminating large amounts of the chemicals that are often sprayed on crops. By dramatically reducing the number of pesticides required in the fields, these sophisticated AI sprayers can raise the standard of agricultural output.

AI for Agriculture Market Drivers:

• Increased globalization and adoption of new technology is anticipated to propel the market growth

Rising customer demand for agricultural products is expected to drive market value growth. Contemporary agricultural technologies, government initiatives, and regulations are also promoting industrialization. The shifting costs of research and development, as well as the increasing use of drones and changes in form, have contributed to the product implications, thus expanding the market. To boost agricultural output, the government is encouraging research and development (R&D) in the field through the State Agricultural Universities (SAUs) and the Indian Council of Agricultural Research (ICAR). In 2023-24, the Department of Agricultural Research & Education (DARE) will have a budget of Rs. 9504 crores, up from Rs. 7846.17 crores in 2019-20. This budget is aimed at developing new techniques demonstrating these in farmers' fields and equipping them with the knowledge to adopt modern methods.

AI for Agriculture Market Geographical Outlook

• North America is witnessing exponential growth during the forecast period

The North American economy is characterized by rising disposable income, continuous investments in automation, large bets on the Internet of Things, and an increasing focus from governments on developing domestic AI equipment. Several agricultural technology vendors' research into artificial intelligence solutions benefits the market as well. In farming, there is a technological revolution coming, as predicted by AI. As drones, robots, and intelligent monitoring systems are used in research and field experiments, it is expected that this will increase significantly in years to come. Regional markets also expect rapid growth with increased use of AI-powered technologies within the agricultural sector.

Reasons for buying this report:-

• Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
• Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
• Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
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Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

• Historical data & forecasts from 2022 to 2029
• Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
• Competitive Positioning, Strategies, and Market Share Analysis
• Revenue Growth and Forecast Assessment of segments and regions including countries
• Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The AI for agriculture market is segmented and analyzed as follows:

By Technology

• Machine Learning
• Computer Vision
• Predictive Analytics

By Application

• Agricultural Robots
• Precision Farming
• Drone Analytics
• Livestock Monitoring
• Weather Tracking
• Others

By Geography

• North America
• USA
• Canada
• Mexico
• South America
• Brazil
• Argentina
• Others
• Europe
• Germany
• France
• United Kingdom
• Spain
• Others
• Middle East and Africa
• Saudi Arabia
• Israel
• UAE
• Other
• Asia Pacific
• China
• Japan
• India
• South Korea
• Indonesia
• Vietnam
• Thailand
• Others

TABLE OF CONTENTS

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 FOR AGRICULTURE MARKET BY TECHNOLOGY

• 5.1. Introduction
• 5.2. Machine Learning
• 5.3. Computer Vision
• 5.4. Predictive Analytics

6. AI FOR AGRICULTURE MARKET BY APPLICATION

• 6.1. Introduction
• 6.2. Agricultural Robots
• 6.3. Precision Farming
• 6.4. Drone Analytics
• 6.5. Livestock Monitoring
• 6.6. Weather Tracking
• 6.7. Others

7. AI FOR AGRICULTURE 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. Germany
    • 7.4.3.2. France
    • 7.4.3.3. United Kingdom
    • 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. Israel
    • 7.5.3.3. UAE
    • 7.5.3.4. 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. India
    • 7.6.3.4. South Korea
    • 7.6.3.5. Indonesia
    • 7.6.3.6. Vietnam
    • 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. Gamaya SA
• 9.2. IBM Corporation
• 9.3. Trimble Inc.
• 9.4. Bayer AG
• 9.5. Prospera Technologies Ltd.
• 9.6. PrecisionHawk Inc.
• 9.7. Cainthus Corp.
• 9.8. AGCO Corporation
• 9.9. Deere & Company
• 9.10. Farmers Edge Inc.