Artificial Intelligence in Agriculture Market Share, Size, Trends, Industry Analysis Report, By Technology (Computer Vision, Machine Learning & Deep Learning, and Predictive Analytics); By Application; By Component; By Region; Segment Forecast, 2024 - 203

Artificial Intelligence in Agriculture Market Share, Size, Trends, Industry Analysis Report, By Technology (Computer Vision, Machine Learning & Deep Learning, and Predictive Analytics); By Application; By Component; By Region; Segment Forecast, 2024 - 2032

The global artificial intelligence in agriculture market size is expected to reach USD 11.96 billion by 2032, according to a new study by Polaris Market Research. The report “Artificial Intelligence in Agriculture Market Share, Size, Trends, Industry Analysis Report, By Technology (Computer Vision, Machine Learning & Deep Learning, and Predictive Analytics); By Application; By Component; By Region; Segment Forecast, 2024 - 2032” gives a detailed insight into current market dynamics and provides analysis on future market growth.

Artificial intelligence methods in agriculture enhance productivity and crop yields. Consequently, agribusiness companies are embracing AI technologies, particularly those based on predictive analytics. AI applications and techniques contribute to pest control, the cultivation of healthier crops, soil monitoring, and the overall optimization of various tasks within the food supply chain. The agriculture sector is progressively incorporating artificial intelligence to enhance the quality and precision of harvests by leveraging farm data analysis.

Moreover, the integration of automation into agriculture plays a pivotal role in resource allocation, involving fertilizers and water distribution, identifying the ideal sowing dates, and weed detection, thus spurring the need for artificial intelligence solutions. This technology further assists in making seed-sowing recommendations by leveraging historical long-term weather records, production data, forecasts for commodity pricing, seed details, and various other inputs. The manifold advantages of AI-driven applications are inspiring numerous technology giants and startups to create IoT-enabled devices, facilitating the widespread implementation of AI applications in agriculture.

The adoption of artificial intelligence techniques is driven, in part, by the scarcity of skilled labor available for agricultural tasks. The diminishing interest of younger generations in the agricultural sector contributes to this labor shortage. Consequently, both private and public entities are making swift investments in AI-based automation systems to counter the labor scarcity challenge. Many countries with aging populations are inclined to embrace such technologies to mitigate the workforce shortage in agriculture. These challenges are anticipated to create numerous growth opportunities for the market.

Additionally, a study published in the National Library of Medicine in June 2021 highlighted the significant impact of coronary artery disease (CAD) on global health. CAD alone is responsible for approximately 610,000 deaths annually, accounting for an estimated one in four deaths and making it the foremost cause of mortality in the United States. With the incidence of CAD rising, there is a growing demand for effective Artificial Intelligence in Agriculture devices to address this pressing medical need. Consequently, this factor is projected to drive the demand for Artificial Intelligence in Agricultures throughout the forecast period.

Artificial Intelligence in Agriculture Market Report Highlights

In 2022, Predictive analytics, a component of AI, utilizes historical data, machine learning algorithms, and statistical techniques to predict future events or outcomes. In the agricultural sphere, predictive analytics is becoming increasingly significant as it assists farmers in optimizing their operations, making well-informed decisions, and managing risks effectively. These models analyze historical data related to crop yields, weather conditions, soil quality, and other relevant factors to extract valuable insights.

The software segment dominated the market share throughout the forecast period. One of the primary factors driving the growth of AI software in the agricultural market is its seamless integration with farming machinery, resulting in labor cost savings and real-time data collection. The substantial volume of data stored in the cloud, along with analytical tools, enables farmers to comprehensively manage all aspects of farming. This software notably enhances farmers' ability to respond effectively to changing demands.

In 2022, the Precision farming segment secured the largest share of revenue. Several pivotal factors underpin the expansion of this market, encompassing heightened water efficiency, diminished reliance on fertilizers and pesticides, and the real-time gathering of diverse crop characteristics. Advanced technologies like IoT, machine learning, sophisticated sensors, and big data analytics play a crucial role in discerning soil nutrient levels, making a substantial contribution to the enhancement of agricultural productivity and the preservation of soil health.

In 2022, North America asserted its dominance as the largest market. The agricultural sector in North America is wholeheartedly adopting AI technology to boost productivity, streamline resource allocation, and enhance decision-making processes. The region offers a wide array of AI applications in agriculture, including precision farming, remote sensing, crop monitoring, predictive analytics, and automated farming systems. Through the utilization of this technology, farmers can improve crop yields, reduce costs, manage risks, and make well-informed, data-driven decisions

The global key market players include Companies such as AgEagle Aerial Systems Inc., aWhere Inc., Deere & Company, Descartes Labs, Inc., ec2ce, GAMAYA, Granular, Inc., IBM Corporation, Microsoft, PrecisionHawk, Prospera Technologies, Taranis, The Climate Corporation, Tule Technologies Inc., VineView.

Polaris Market Research has segmented the Artificial Intelligence in Agriculture market report based on technology, application, component, and region:

Artificial Intelligence in Agriculture, Technology Outlook (Revenue - USD Billion, 2019 - 2032)

Computer Vision

Machine Learning & Deep Learning

Predictive Analytics

Artificial Intelligence in Agriculture, Application Outlook (Revenue - USD Billion, 2019 - 2032)

Precision Farming

Agriculture Robots

Livestock Monitoring

Drone Analytics

Artificial Intelligence in Agriculture, Component Outlook (Revenue - USD Billion, 2019 - 2032)

Services

Software

Hardware

Artificial Intelligence in Agriculture, Regional Outlook (Revenue - USD Billion, 2019 - 2032)

North America

U.S.

Canada

Europe

Germany

UK

France

Italy

Spain

Russia

Netherlands

Asia Pacific

China

India

Japan

South Korea

Indonesia

Malaysia

Latin America

Argentina

Brazil

Mexico

Middle East & Africa

UAE

Saudi Arabia

Israel

South Africa