AI in Agriculture Market To Generate $8,308.5 Million Revenue by 2030

The AI in agriculture market size is expected to advance at a CAGR of 26.7% during 2022–2030, to reach $8,308.5 million by 2030. This can be ascribed to the increasing demand for high agricultural production, the surging focus on the utilization of internet of things (IoT), the rising need for real-time livestock monitoring, and the growing adoption of drones in farms.

The agriculture industry is strongly adopting next-generation technologies, such as AI, ML, computer vision, predictive analytics, facial recognition, and big data. This is mainly due to the rising cost of supplies, changing consumer preferences related to sustainability, and shortage of labor, which is further encouraging governments to implement advanced farming solutions. Also, various technological advancements are seen in areas such as vertical farming, precision agriculture, livestock monitoring, and automation and robotics.

Some of the benefits offered by advanced technologies in the agricultural sector include better utilization of limited space, environment-friendly and energy-efficient systems, improved waste management, and enhanced quality of agricultural products.

Increasing Demand for Monitoring Livestock

The rising need for monitoring livestock is a key factor driving the industry. Livestock plays an important role in fulfilling the demand for meat, milk, eggs, and wool. With the changing lifestyles, the growing population, and the increasing per-capita income levels, there is a rise in meat, eggs, and milk consumption globally. Also, to fulfill the demand for protein-rich foods, the health of livestock needs to be monitored on a regular basis.

With the application of advanced AI solutions, such as facial recognition for livestock and image classification combined with feeding patterns and body condition scores, dairy farms are now able to individually monitor all behavioral aspects in a herd. Further, for monitoring the health of livestock, many companies are increasingly using machine vision that helps recognize hide patterns, facial features, and water and food intake of livestock, as well as helps in recording their behavior and temperature.

Moreover, facial recognition also helps in the diagnosis of abnormality in cows before they show severe symptoms, thus saving farmers from the loss of low milk production. For instance, in China, Beijing Unitrace Tech, an AI company, developed a livestock health monitoring system with facial recognition for managing a herd of cows.

APAC Offers Lucrative Growth Potential to the Industry

In the APAC region, the increasing effort by governments as well as various multinational companies (MNCs) for spreading awareness about farm analytics and data sciences to farmers, is driving the market. Further, to promote technological advancements in the agriculture sector, the Government of China is rapidly investing in agricultural AI to enhance food security and increase food production.

Similarly, the Ministry of Civil Aviation announced the drone policy ‘Drone Regulations 1.0’ in India. Under the regulations, the policy guidelines state to assist and promote technology and innovation in the advancement of drones, coupled with drone-based devices, which have a wide range of applications, ranging from agriculture to disaster relief.

On the other hand, the European AI in agriculture market is expected to exhibit significant growth during the forecast period. This can be because smart agriculture and precision farming already taking off high, greater use of IoT in farming is opening new doors for industry players, and the increasing use of robotic systems in agriculture. Moreover, the rising research activities by governments and other research and development (R&D) organizations toward the use of AI-based technologies in agriculture are driving the regional market.

The most significant AI in agriculture market players include Raven Industries Inc., Farmers Edge Inc., Deere & Company, A.A.A Taranis Visual Ltd., Gamaya SA, AGCO Corporation, Bayer AG, IBM Corporation, Ag Leader Technology, and Trimble Inc.