Global AI in Agriculture Market Size Will Reach USD 2,400 million by 2026: Facts & Factors

According to a research report published by Facts and Factors, the global demand for AI in agriculture market in 2019 was above USD 750 million. The market is expected to grow above a CAGR of 20% and is anticipated to reach over USD 2,400 million by 2026.

Farming and agriculture is most important and oldest profession in the word. With the growing population, it is very important to produce more crops in less land and increase productivity. With the introduction of AI technologies, farmer can yield healthier crops, monitor their soil and growing conditions, and control pests. AI in agriculture helps the farmer by organizing data for farmers; it helps with workload, and enhances a wide range of the tasks which are related with agriculture and entire food supply chain. Artificial Intelligence in agriculture is used for various applications such as driverless tractors, rural automations, computerized water system frameworks, facial acknowledgment, etc.

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Rapid growth in the population increases the demand for agricultural products. In the recent years, innovative technologies are used to enhance the production. The increasing adoption of the advance technologies, growing need for livestock monitoring, increasing use of drones in agriculture, growing requirement for smart sensor, GPS tracker in agriculture may drive the AI in agriculture market. Moreover, in many countries government is also supporting for modern agricultural techniques. This techniques including predictive analysis, machine leaning, and computer vision that helps the farmer to analyze real-time data of temperature, weather conditions, crop prices, soil moisture, and plant health which further propelling the market growth. In emerging countries, many private organizations are focusing on automation in agriculture sector; thereby major farmers are focusing towards automation in agriculture. Furthermore, to improve the crop quality robots and drones are becoming the important part in the crop production. These factors are estimated to drive the market in the future years. However, lack of standard in data sharing and data collection, may restraint the market growth. It requires lot of money to buy robots, poor farmers cannot afford it. They prefer to farming in traditional way. Moreover, the high cost of research and development, and high investment in maintenance may impede the market growth. On the other hand, traditional farmer needed more labor to crop and keep the farm productive. AI bots helps the farmer to perform faster work than human labors and harvest crops at a high amount. It can accurately identify and eliminate weeds and reduce the farm cost. These factors may create attractive opportunities for the farmer, in turn, it can propel the market growth.

Top key players operating in the market are Gamaya, Precision Hawk, Microsoft, Agribotix(A AgEagle Company), IBM, John Deere, ec2ce, Descartes Labs, The Climate Corporation, Vineview, Taranis, aWhere, Granular, DTN, Resson, FarmBot, Connecterra, Prospera, Cainthus, Vision Robotics, Trace Genomics, CropX, Harvest Croo, Autonomous Tractor Corporation, and others.

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By technology segmentation, the computer vision category is expected to contribute the largest market share in the global AI in agriculture market. Computer vision technology helps the farmer to detect nutritional deficiency of the plant and monitor crop health.

On the basis of component segment, the software category led the market in 2019 and it is anticipated to grow in the future years attributed to growing use of AI software to improve efficiency of farm, and increasing need for real-time data management systems.

By application segment, in 2019, precision farming category headed the market and it is anticipated to grow over the forecast period owing to its increasing need for maximum yield production with the growing population.

By geography, in 2019, the North America dominated the market for the AI in agriculture owing to increasing investment in R&D activities and high adoption of the new technologies.

On the basis of deployment segment, cloud category headed the market in 2019. Cloud-based platform supports the access from any internet-connected device.

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Agriculture is the oldest and most important profession around the word. With the rising population, producing more crops in less land is very necessary. Farmers can produce healthier crops, track their soil condition and growing conditions and manage pests with the implementation of AI technologies. AI in agriculture helps the farmer by organizing farmers ' data; it helps with the workload and improves a wide range of related tasks. Rapid population growth is increasing demand for agricultural production. Innovative technologies have been used in recent years to increase the efficiency. Growing adoption of advanced technology, growing need for monitoring of livestock, increasing use of drones in agriculture, increasing demand for smart sensors, GPS tracker in agriculture will drive the AI in the agricultural sector.

High maintenance cost, huge investment in the research and development may restraint the market growth. However, use if the AI bots that helps the farmer to work faster than human labors and to produce a large volume of crops may create sufficient opportunities in the market.

The AI in agriculture market is segmented based on technology, application, component, deployment and region. On the basis of technology segmentation, the market is classified into machine learning, computer vision, and predictive analytics. By application segmentation, the market is divided into precision farming, livestock monitoring, drone analytics, agriculture robots, others. By component, the market is separated into hardware, software, AI-as-a-service, service. By deployment segmentation, the market is bifurcated into cloud, on-premise, and hybrid.

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This report segments the AI in agriculture market as follows:

Global AI in agriculture Market: By Technology Segmentation Analysis

Machine Learning
Computer Vision
Predictive Analytics

Global AI in agriculture Market: By Component Segmentation Analysis

Hardware
Software
AI-as-a-Service
Service

Global AI in agriculture Market: By Application Segmentation Analysis

Precision Farming
Livestock Monitoring
Drone Analytics
Agriculture Robots
Others

Global AI in agriculture Market: By Deployment Segmentation Analysis

Cloud
On-premise
Hybrid

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