AI in agriculture market worth $4.7 billion in 2028

The growth of the AI in agriculture market is attributed to the benefits of artificial intelligence (AI) in agriculture over traditional practices, according to the research report. During the forecast period, development of AI in agriculture in applications such as drone analytics, precision farming, and ag robots are expected to create growth opportunities for the market.

Machine learning

Machine learning enabled AI in agriculture is to account for the larger share of AI in agriculture market. Technological advancements and the generation of large volumes of data are some major factors driving the need for machine learning-enabled farming tools.

Deep learning, part of machine learning, is based on multiple algorithms creating non-linear relationships in data. The growing use of deep learning algorithms in a wide variety of applications in agriculture, including crop and soil monitoring, insect and plant disease detection, and livestock health monitoring, is the major factor boosting the growth of the AI in agriculture market.

AI-as-a-Service

The AI-as-a-service segment is to grow at a highest CAGR during the forecast period. Increasing demand for machine learning tool kits and applications designed for AI-based services leads to the growth of the AI-as-a-Service segment. Meanwhile, drones make an important contribution to the AI technological revolution in the agricultural sector, according to the researchers.

Adoption of AI in agriculture in Asia Pacific

The market has been segmented into China, Japan, south Korea, India, Australia, and the rest of Asia Pacific. The rapidly increasing population, availability of arable farms, and government support through subsidies are major factors fueling the adoption of AI in agriculture in Asia Pacific. The region has emerged as a global focal point for large investments and business expansion opportunities.

The main factors contributing to the growth of the AI in agriculture market in Asia Pacific include the growing practices of precision farming to increase crop yield, rising drone analytics services, and increasing adoption of agriculture robots in farming. Machine learning, deep learning, and computer vision are some of the innovative technologies transforming the agriculture industry in this region, the report states.