Artificial Intelligence in Agriculture Market Analysis and Global Outlook 2023 to 2030 | IBM, John Deere, Microsoft

PRESS RELEASE
Published October 31, 2023

New Jersey, United States – A recently published market research report by Infinity Business Insights indicates substantial growth projections for the Artificial Intelligence in Agriculture Market by the year 2030. The report provides a detailed breakdown of the market’s size and segmentation across various categories, product types, applications, and geographical regions. Additionally, the report offers an extensive analysis of critical factors, including key trends, drivers, constraints, challenges, and the competitive landscape. Furthermore, it highlights recent market developments, including noteworthy mergers and acquisitions (M&A) activities within the industry.

Market Overview: The market for Artificial Intelligence in Agriculture is experiencing significant growth as the agriculture sector increasingly integrates AI technologies to enhance crop management, livestock monitoring, and overall farm operations. Artificial Intelligence in Agriculture involves the application of machine learning, computer vision, and data analytics to improve decision-making, automate tasks, and optimize resource utilization in farming. This market primarily serves the agriculture and agribusiness sectors, supporting a wide range of activities, from precision farming and crop analytics to supply chain optimization. The demand for AI in Agriculture is driven by the need to address global challenges, including feeding a growing population, managing limited resources, and mitigating the impact of climate change. As agriculture becomes more data-driven and technology-dependent, the market for Artificial Intelligence in Agriculture continues to expand.

The global artificial intelligence in agriculture market is expected to grow at a CAGR of 6.1% from 2023 to 2030. This growth is being driven by the increasing demand for artificial intelligence solutions to improve the efficiency and productivity of agricultural operations.

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Top key players:
IBM, John Deere, Microsoft, Agribotix, The Climate Corporation, ec2ce, Descartes Labs, Sky Squirrel Technologies, Mavrx, aWhere, Gamaya, Precision Hawk, Granular, Prospera, Cainthus, Spensa Technologies, Resson, FarmBot, Connecterra, Vision Robotics, Harvest Croo, Autonomous Tractor Corporation, Trace Genomics, Vine Rangers

Artificial Intelligence in Agriculture Industry Analysis
Artificial Intelligence in Agriculture primarily serves the agriculture and agribusiness sectors, encompassing various activities such as crop production, livestock management, and supply chain optimization. These technologies support farmers in optimizing resource usage, crop health, and overall farm efficiency. In livestock management, AI technologies aid in disease detection and herd management. Agribusinesses benefit from improved supply chain management, better market insights, and traceability of agricultural products. As the agriculture industry faces increasing demands for sustainable and efficient food production, Artificial Intelligence in Agriculture is poised to play a pivotal role in the transformation of modern farming practices.

Future Benefits: The future benefits of Artificial Intelligence in Agriculture revolve around increased productivity, resource efficiency, and sustainability. AI technologies enable farmers to make data-informed decisions, optimize planting and harvesting, and monitor crop health and yield. Predictive analytics and machine learning models provide insights into the best practices for soil management, water usage, and pest control, ultimately leading to higher crop yields and reduced resource waste. Additionally, AI-driven automation enhances the precision and efficiency of farm operations, from planting and irrigation to harvesting. As the agriculture industry evolves, AI is expected to play a pivotal role in meeting global food production demands, improving resource management, and reducing the environmental footprint of farming.

Global Artificial Intelligence in Agriculture Market Split by Product Type and Applications

This report segments the Artificial Intelligence in Agriculture Market on the basis of Types:
Machine Learning
Computer Vision

On the basis of Application, the Artificial Intelligence in Agriculture Market is segmented into:
Precision Farming
Drone Analytics
Agriculture Robots

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Recent Development: Recent developments in Artificial Intelligence in Agriculture include advancements in computer vision, data analytics, and remote sensing technologies. AI-powered drones and satellites equipped with high-resolution cameras and sensors provide real-time data on crop health, enabling early disease detection and efficient monitoring. Data analytics and AI algorithms are becoming more sophisticated, allowing for predictive insights and recommendations based on historical and real-time data. Additionally, the integration of edge computing devices and IoT sensors in the field provides farmers with on-site processing and decision support, reducing latency and improving real-time decision-making.

Competitive Analysis: The market for Artificial Intelligence in Agriculture is competitive, with numerous technology providers, agtech companies, and AI solution vendors offering a wide range of applications. Key players compete based on the comprehensiveness of their AI solutions, the accuracy of their predictive models, and the ease of integration with existing farm equipment and data systems. User-friendly interfaces, scalability, and the ability to provide actionable insights are pivotal in attracting farmers and agribusinesses. Continuous innovation in AI algorithms, expanded capabilities for automation, and improvements in data collection and analytics are key to staying competitive in this dynamic and evolving market.

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Regional Analysis:
The market for Artificial Intelligence in Agriculture is a global one, with adoption and development occurring in various regions with active agriculture sectors. Key regions include North America, Europe, and Asia, where precision farming and agtech adoption are prevalent. Regional factors include crop types, climate conditions, and government policies, which influence the adoption of AI technologies in agriculture.

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1.To gain an in-depth understanding of Artificial Intelligence in Agriculture Market
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4.It gives pin point investigation of changing rivalry elements and keeps you in front of contenders.
5.It helps in settling on educated business choices by having total bits of knowledge of market and by making inside and out investigation of market sections.

FAQs:
A. During the projected period, what will be the market’s development rate, development force, or speed increase?
B. What are the fundamental drivers of the market?
C. As far as worth, how large was the developing business sector in 2023?

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Table of Contents:
1. Introduction
2. Executive Summary
3. Advantages of Our Market Analysis
4. Global Artificial Intelligence in Agriculture Market Visions
5. Global Artificial Intelligence in Agriculture Market, by Application
6. Global Artificial Intelligence in Agriculture Market, by Types
7. Global Artificial Intelligence in Agriculture Market, by End-User
8. Global Artificial Intelligence in Agriculture Market, by Procedure
9. Global Artificial Intelligence in Agriculture Market, by region
10. Competitive Landscape
11. Company Outlines

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