Latest News- AI In Agriculture Market: Software is expected to lead the Component segment during 2025-2029

The AI In Agriculture Market is being driven by Imperative for increased food production and yield enhancement

The AI In Agriculture Market is expected to grow at a CAGR of 20.4% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 3090.4 million. The global AI in agriculture market is experiencing a significant shift from traditional precision farming methods to fully autonomous farming operations. This transition signifies a transformative approach to farm labor, productivity, and scale. While GPS-guided autosteer has long been a standard feature, the current trend involves the integration of advanced technology enabling machines to execute intricate tasks, such as planting, weeding, and harvesting, without human intervention or, in certain instances, without a cab. Key players in the original equipment manufacturing sector, including Deere and Company, are spearheading this transformation. Deere's autonomous 8R Tractor, showcased at the Consumer Electronics Show in January 2024, exemplifies this trend. 

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Which Factors Are Causing a Surge in Market Growth?

The market is segmented based on

• Component
  • Software
  • Hardware
  • Services
• Technology
  • Machine learning
  • Predictive analytics
  • Computer vision
• Application
  • Precision farming
  • Drone analytics
  • Livestock monitoring
  • Agriculture robotics
  • Labor Management
• Geography
  • North America
    • Canada
    • US
  • APAC
    • China
    • India
    • Japan
  • Europe
    • Germany
    • UK
    • France
  • South America
  • Middle East and Africa

According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows: 

• Imperative for increased food production and yield enhancement
• Focus on input cost reduction and operational efficiency
• Rising emphasis on sustainable practices and regulatory pressures

However, the market also witnesses some limitations, which are as follows:

• High cost of implementation and uncertain return on investment
• Data management, interoperability, and connectivity issues
• Technical complexity and scarcity of skilled labor

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Market Scope in AI In Agriculture Market Research Report

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Research Analysis Overview

In the AI-driven agricultural sector, sensor networks collect data which is analyzed through data analytics dashboards, enabling AI-powered decision support for predictive maintenance, farm equipment automation, and optimized fertilizer application. Crop monitoring dashboards, integrated pest management, smart irrigation scheduling, yield mapping, harvest optimization, and supply chain traceability are other applications. Risk management tools, precision livestock farming, agricultural robotics, autonomous vehicles, environmental monitoring, soil fertility assessment, water resource management, disease surveillance, weed control techniques, farm labor optimization, genetic modification, precision breeding, and crop simulation modeling are additional benefits of AI technology in agriculture.

Market Research Overview

In the agricultural sector, precision agriculture is driving the adoption of advanced IT solutions. This includes the implementation of sensors for monitoring crop health, robotic harvesting systems for efficient farming, and variable rate fertilization to optimize nutrient usage. These technologies fall under the application software market segment of the IT software industry. Technavio's market analysis covers global application software companies providing solutions for agriculture, excluding those specializing in interactive home entertainment or systems software. The market size is determined by the consolidated revenue of these businesses offering IT software solutions, including cloud-based applications, for precision agriculture.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.

Technavio Research
Jesse Maida
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