The overall AI in agriculture market is estimated to be USD 1.0 billion in 2020 and is projected to reach USD 4.0 billion by 2026, at a CAGR of 25.5% between 2020 and 2026. The growth of the market is propelled by the increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep-learning technology, and government support for the adoption of modern agricultural techniques. However, the high cost of gathering precise field data restrains the market growth.
By technology, the computer vision segment is projected to register the highest CAGR during the forecast period. This high growth rate is attributed to the increasing use of computer vision technology for agriculture applications, such as plant image recognition, and the rising demand for continuous crop health monitoring and analysis.
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By offering, the AI-as-a-Service segment is projected to register the highest CAGR during the forecast period. Increasing demand for machine learning tool kits and applications that are available in AI-based services along with the benefits, such as advanced infrastructure at minimal cost, transparency in business operations, and better scalability, is leading to the growth of the AI-as-a-Service segment.
By application, the drone analytics segment is projected to register the highest CAGR during the forecast period owing to its extensive use in diagnosing and mapping crop health and making real-time decisions. Favorable government mandates for the use of drones in agriculture are also expected to fuel the growth of the AI in agriculture market in the drone analytics application segment.
By region, the AI in agriculture market in Asia Pacific (APAC) is projected to witness the highest CAGR during the forecast period. China, Japan, and India are some of the countries driving the market in APAC. The increasing adoption of deep learning and computer vision technologies for agriculture applications is a major driving factor for the market in the APAC region.