Artificial Intelligence in Agriculture Industry

The report "Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, AI-as-a-Service), Application (Drone Analytics, Precision Farming) and Region - Global Forecast to 2028" The AI in agriculture industry is projected to grow from USD 1.7 billion in 2023 to USD 4.7 billion in 2028; it is expected to grow at a CAGR of 23.1%  from 2023 to 2028. The growth of the market is attributed to the benefits of the AI in agriculture over traditional practices. During the forecast period, development of AI in agriculture in application such as drone analytics, precision farming, and agriculture robots are expected to create growth opportunities for the market.

Browse 157 market data Tables and 46 Figures spread through 190 Pages and in-depth TOC on "Artificial Intelligence in Agriculture industry by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, AI-as-a-Service), Application (Drone Analytics, Precision Farming) and Region - Global Forecast to 2028"
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Machine learning enabled AI in agriculture is to account for the larger share of AI in agriculture industry in 2022.

Machine learning enabled AI in agriculture is to account for the larger share of AI in agriculture industry. Machine learning-enabled solutions are significantly adopted by agricultural organizations and farmers worldwide to enhance farm productivity and gain a competitive edge in business operations. 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 segment is to grow at a highest CAGR between 2023 and 2028.

AI in agriculture industry is segmented based on offering into hardware, software, AI-as-a-service, and service. 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 is leading to the growth of the AI-as-a-Service segment.

Drone analytics application of AI in agriculture is to record the largest market share throughout the forecast period.

Unmanned aerial vehicles (UAVs), commonly known as drones, make an important contribution to the AI technological revolution in the agricultural sector. Drones are mainly used in agricultural farms to gather data related to a variety of factors, such as plant counting, soil & field analysis, crop spraying, and crop monitoring. Drones are equipped with several sensors and microcontrollers, near-infra-red spectrometers, multispectral cameras, and GPS receivers. They fly over the fields, capture high-resolution pictures, and gather data, which is sent directly to the cloud/software and made available to the customer.

Market in Asia Pacific holds significant opportunities for the market during forecasted period.

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.

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