AI in Agriculture Market To Advance at 24.8% CAGR between 2020 and 2030

The rising penetration of the internet of things (IoT) technology in the agriculture sector, mounting demand for high crop yields, increasing deployment of drones for pesticide spraying, surging need for real-time livestock monitoring, and growing focus on improved crop management are expected to drive the artificial intelligence (AI) in agriculture market at a CAGR of 24.8% during the forecast period (2020-2030). The market revenue stood at $852.2 million in 2019, and it is projected to reach $8,379.5 million by 2030.

The increasing adoption of drones by farmers has become a key growth driver for the market. Drones are being used for scanning soil health, estimating yield data, applying fertilizers, and assisting in irrigation schedules. Moreover, the surging number of government initiatives facilitating the adoption of drones for improving agricultural practices is having a positive impact on the market. For example, in January 2019, the state government of Maharashtra, India, partnered with the World Economic Forum (WEF) to enhance agricultural yield by gathering details about agricultural farms through drones.

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Moreover, the soaring requirement for real-time livestock monitoring is supporting the AI in agriculture market growth. Dairy farms can easily monitor their herd by using advanced AI solutions, such as image classification integrated with the body condition score and feeding patterns of animals and facial recognition. Farmers are also using machine vision to track the health of their livestock. Machine vision helps in identifying the facial features and hide patterns, recording body temperature and behavior, and monitoring the water and food intake of the rudiments.

The categories under the type segment of the AI in agriculture market include product and service. During the forecast period, the service category will grow at the faster pace due to the burgeoning requirement for proper installation, training, and maintenance services among farmers and other industry stakeholders. The category is further divided into professional and managed. Of these, the professional category will witness the faster growth in the coming years owing to the booming demand for maintenance, support, and training services from farmers using AI solutions.

Geographically, the North American region recorded the highest demand for such solutions during the historical period (2014-2019), and it is expected to lead the AI in agriculture market in the forecast years as well. This will be due to the early adoption of computer vision and machine learning (ML) technologies for agricultural applications, including soil management, livestock management, greenhouse management, and precision farming. Moreover, the surging integration of IoT with computer vision will support the market growth over the forecast period.

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The Asia-Pacific (APAC) AI in agriculture market is projected to record the fastest growth in the forecast years. This can be primarily owed to the high adoption rate of AI solutions in the agriculture industry in Australia, India, China, and Japan. Among APAC nations, China is witnessing a widespread adoption of the AI technology in agriculture due to the entry of Alibaba Group in the agricultural solutions business with its AI technology to aid the small farmers in the nation.

Thus, the rising utilization of drones on farms and increasing need to monitor the livestock on a real-time basis will propel the market growth in the coming years.

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This release was published on openPR.