The rising demand for agricultural production is leading to the increasing adoption of drone analytics, internet of things (IoT) devices, and livestock monitoring techniques by farmers. These factors are projected to lead to an increase in the revenue of the artificial intelligence (AI) in agriculture market from $852.2 million in 2019 to $8,379.5 million in 2030, at a 24.8% CAGR during 2020–2030 (forecast period). The need for AI among farmers is also driven by the increasing pressure to produce more from the diminishing land area under cultivation.
Predictive analytics, machine learning (ML), and computer vision are the three categories under the technology segment. Among these, the largest share in the AI in agriculture market in 2019 was held by the ML category because of the rising adoption of the technology by the agrarian community and governments. This is being done to utilize data analytics and agronomic sciences to augment the productivity of farmlands. The predictive analytics category will witness the highest CAGR during the forecast period due to the usage of this technology for real-time weather, plant health, and soil moisture tracking.
Read More: AI in Agriculture Market Analysis and Demand Forecast Report
Based on application, the market is classified into agricultural robots, precision farming, drone analytics, livestock monitoring, and others. Among these, the precision farming classification dominated the industry during 2014–2019 (historical period). This is attributed to the rising pressure to produce more from the farmlands left and do it cost-effectively. However, the increasing demand for high-quality crops and growing funding for drone applications will propel the drone analytics category at the highest pace during the forecast period.
Due to the increasing demand for food crops, the AI in agriculture market is witnessing rapid growth. As per the United Nations (UN), the global population is set to rise from 7.7 billion in 2019 to 10.9 billion in 2100, thereby propelling the demand for a wide array of crops. Apart from this, the rapid urbanization, rising disposable income, and changing consumption habits in India, China, Brazil, and the U.S. are driving the food demand. This is why the government in these countries is collaborating with tech giants to facilitate the adoption of AI in agricultural practices.
The key trend in the AI in agriculture market is the usage of smart sensors by farmers. Sensors allow farmers to monitor the growth of crops deeply and obtain the maximum yield, while using as less seeds, water, and other resources as possible. With sensors, the agrarian community can study the farmlands and pinpoint the areas that need crop treatment. With time, an array of sensors, such as optical, location, mechanical, electrochemical, soil moisture, airflow, and weather sensors, have become available for agricultural use.
North America was the largest AI in agriculture market during the historical period as a result of the earlier adoption of computer vision and ML for precision farming, livestock management, soil management, and greenhouse management than elsewhere on earth. The fastest industry growth will be seen in Asia-Pacific (APAC) till 2030 due to the high usage of agricultural robots, drone analytics, and precision farming in China, India, Thailand, and Indonesia. In addition, the rapid urbanization and rise in population are leading to the need for advanced technologies to augment crop production.
Hence, with the growing population leading to the increasing demand for food, the usage of AI in farmlands will rise.
