AI in Agriculture Market: Segmented: by Offerings (Hardware, Software and Services); By Technology (Machine Learning, Predictive Analytics and Computer Vision); By Application (Livestock Monitoring Application, Precision Farming Application, Agriculture Robots Application, Drone Analytics Application and Others); By Region (North America, Latin America, Europe, Asia-Pacific and Middle-East & Africa) - Analysis of market share, size & trends for 2016-19 and forecasts to 2030
Artificial Intelligence in Agriculture Market is anticipated to surpass USD 8322 Million by 2030 from USD 893 Million in 2020 at a CAGR of 22.5% throughout the forecast period, i.e. 2020-2030
Artificial Intelligence in Agriculture uses modern and innovative agricultural technologies to improve productivity and yield to deliver better and more efficient farming services. Using specific equipment such as the Internet of Thing models, sensors and actuators, geo-positioning systems, Unmanned Aerial Vehicles (UAVs or drones), robotics & fertilizers, irrigation management, and so on, farmers can advance their production and harvest by controlling pests, increasing productivity, monitoring the soil quality while reducing the time, energy and work needed for these tasks. Artificial Intelligence in agriculture helps and assists in evaluating and taking decisions to boost crop growth and production. In agriculture, artificial intelligence has a variety of uses, including agricultural automation, digital water network systems, face recognition, and tractors without a driver. One of the important factors that boost the market for artificial intelligence in agriculture is the increase in usage of AI and the need for better yields of goods.
Factors such as growing stress on the food supply chain due to exponentially increasing population, rising implementation of the Internet of Things in the agricultural sector, improving the standard of living, growing focus on enhanced crop monitoring, and increased demand for higher agricultural yield, are driving growth in the artificial intelligence market. Moreover, limited land for agriculture coupled with supportive government policies to encourage the use of AI technologies is anticipated to fuel the market growth. Nonetheless, insufficient knowledge of high technology machine learning solutions in agriculture can hamper the growth of artificial intelligence in the agriculture market. However, the increased use of drones in farms is expected to accelerate the deployment of artificial intelligence in the agriculture market.
Based on offerings, the global AI in Agriculture Market is segmented into hardware, software, and services. The software segment captured a significant share in 2019 and is projected to have the highest CAGR during the forecast period. The convergence of digital technology with agriculture techniques, increased adoption of automation and control systems, such as GPS / GNSS receivers, irrigation controls, guidance & steering systems, and the demand for database management systems has created a new approach to farming practices that stimulates market growth.
Based on technology, AI in the agriculture market is categorized into machine learning, predictive analytics, and computer vision. The machine learning segment accounted for a major share in 2019 and is expected to grow at a CAGR of XX% during the forecast period. Machine-learning technologies for increasing yields and gaining a competitive advantage in business activities are embraced by farming organizations and farmers worldwide. Machine learning is anticipated to expand exponentially different agricultural practices over the forecast timeframe. Furthermore, the application of computer education to sensor data expands the potential of production enhancement and turns farm management systems into true artificial intelligence systems. Hence, the machine learning segment is expected to expand.
Global AI in the agriculture market is segregated by application into livestock monitoring application, precision farming application, agriculture robot’s application, drone analytics application, and others. The precision farming application accounted for a share of XX% in 2019 and is projected to hold a significant share in 2020-30 owing to the growing popularity of the precision farming method amongst farmers as a result of the need to maximize production with the available scarce resources and to reduce costs of cultivation. Also, the ability of IoT-based systems in field mapping and management are utilized by agricultural managers and manufacturers, which also contribute to rapid market development.
Rising demand for Agricultural Produce
Growing global demand for food, farmers need to increase crop production either by increasing the amount of agricultural land or by adopting advanced agricultural methods such as precision farming. Another major factor that has prompted farmers to implement digital farming solutions in their farms to boost the productivity of agricultural land is the increased demand for quality crops that meet the increasing requirements of grains and plants.
High Equipment Cost
Some of the factors limiting the growth of Artificial Intelligence in the agriculture market are the high cost of devices used in Artificial Intelligence in agriculture and the lack of awareness among farmers. High costs incurred in the production of Artificial Intelligence in agricultural equipment, in turn, increase the price of the final product, which is likely to restrict the growth of the market over the forecast period.
Global Artificial Intelligence in Agriculture market is segmented based on regional analysis into five major regions. These include North America, Latin America, Europe, Asia-Pacific, and the rest of the world is classified as Middle-East and Africa.
North America to register a remarkable CAGR during the forecast period
Owing to the concentration of leading industrial automation players and the introduction of artificial intelligence technologies in North America, the share in 2019 accounted for more than other regions. North America is marked by an enhanced standard of living of the people, continuous technological investments, major IoT investments, and growing policy emphasis on the development of in-house AI equipment. These factors are likely to boost growth shortly.
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