AI Market in Agriculture by Solution (Robotics, Crop Monitoring, Automated Irrigation, AI-Guided Drone), by Type (Product [Hardware, Software], Service [Installation, Training, Support & Maintenance]), by Geography (U.S., Canada, U.K., Germany, France, China, Japan, India, South Korea, Brazil, Peru) – Global Market Size, Share, Development, Growth, and Demand Forecast, 2013-2023

AI Market in Agriculture Overview

The AI market size in agriculture was valued at $110.3 million in 2016, and is forecasted to advance at 23.2% CAGR during the forecast period. The increasing penetration of internet of things (IOT) in the agriculture industry is a key factor driving the growth of the AI market in agriculture. As per a recent research, IoT device installations in the agriculture space is expected to increase from $30 million in 2015 to nearly $75 million in 2020, at a CAGR of around 20%.

 

GLOBAL AI MARKET IN AGRICULTURE, BY SOLUTION, $M (2013 - 2023)

On the basis of solution, the global AI market in agriculture is categorized into robotics, crop monitoring, automated irrigation, AI-guided drone, and others. As per the research, crop monitoring is the largest solution type throughout the period of analysis. The market for crop monitoring accounted for more than 35% of the global revenue in 2016. And during the forecast period AI guided drone is expected to be the fastest growing solution.

Many new product launches with new technology integration in crop monitoring space are coming up with research groups and regional unions, to improve regional crop monitoring capabilities. This has been a prominent factor for the growth of the AI market in agriculture in recent times. For instance, Joint Research Centre (JRC) in European Union (EU), in September 2017, launched an EU-wide crop and weather monitoring e-service. Worldwide web users can leverage the benefits of the new launch to view weather and crop conditions in near to real-time, across EU.

With increasing research and development of advanced robotics technology in the agriculture sector, farming practices are becoming more sophisticated and modernized. The focus of agriculture stakeholders has now shifted from traditional farming practices to refining the output using advanced farming methods and reducing the extent of carbon footprint in the entire agricultural process. Proponents of the robotics market are hosting offerings that are equipped with the intelligence to operate in unstructured and dynamic agricultural environments, preparing for a promising growth of AI in the agriculture industry.

Precision agriculture through smart agriculture practices, including the use of sensors, has also been gaining huge interest from agriculture stakeholders in the AI market in agriculture, in the past few years. Precision agriculture, which allows maximizing yields using minimal resources such as seeds, fertilizer, and water, enables farmers to understand their crops at a micro scale, help in conserving valuable and costly resources, and reduce the overall impact on the environment.

AI Market in Agriculture Dynamics

Drivers

Of the many advantages that IoT brings to the table of the present day automated technology landscape, its ability to innovate and transit the current farming methods to a new level is absolutely revolutionary. The inclusion of IoT sensors in agriculture practices is capable of providing farmers with critical information about rainfall, crop yields, soil nutrition, and pest infestation. Such information is valuable to the overall farm production and offer the most accurate data to be used for improving complete farming techniques. This factor has been driving the AI market in Agriculture in recent times with good results.

Increase in the adoption of cattle face recognition technology has also been one of the major drivers for the growth of the AI market in agriculture. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle. Therefore, through the adoption of AI in agriculture, cattle facial recognition can enable diagnoses of lame cows before they show severe symptoms, thus saving farmers from the loss of low milk production. This factor helps in the optimization of farmer’s inventory and decreases the cost of feed to a great extent.

Restraints

Some of the major barriers to the growth of the AI market in agriculture are the high cost of cutting-edge AI technology and lack of AI in agriculture understanding among end users. In a recent study, more than 60% of the small and medium businesses (SMBs) surveyed said that they are not on the radar of seriously implementing AI in their business process due to budget constraints and lack of skilled workforce.

Opportunity

With a huge space still untouched in agriculture for the intrusion of automatic response systems, there is a vast opportunity for the agriculture industry to leverage emerging technology of chatbots for assisting farmers with the answers to all their queries, and giving relevant advice and recommendations to their specific farm related problems. This in turn propels the growth of the AI market in agriculture.

AI Market in Agriculture Competitive Landscape

The AI market in agriculture is presently moderately competitive, where some prominent global level players are enjoying monopoly. Some of the major players operating in this industry are Intel Corporation, Google Inc., International Business Machines Corporation, NVIDIA Corporation, Sentient Technologies, Numenta Inc., and Microsoft Corporation.

The companies in the global AI market in agriculture are trying to improve their offerings through new product launches. For instance, in October 2017, Climate Corporation announced the launch of the Climate FieldView digital agriculture platform in Western Canada for the 2018 growing season. Climate Corporation is a subsidiary of Monsanto Company, and through the new launch’s analytics-based digital tools, the Canadian farmers will now be able to converge their data one connected platform. This would help them in identifying and more efficiently managing the variations in their fields.