Artificial Intelligence in Agriculture Market Share | Global Industry Outlook and Statistics, Segmentation and Forecast to 2030

July 11 14:20 2022
Artificial Intelligence in Agriculture Market Share | Global Industry Outlook and Statistics, Segmentation and Forecast to 2030
Artificial Intelligence in Agriculture Market | Emergen Research
Increasing implementation of data generation through sensors is one of the key factors driving market revenue growth

The Artificial Intelligence (AI) in agriculture market size reached USD 1.70 Billion in 2021 and is expected to register a revenue CAGR of 27.0% during the forecast period to a latest analysis by Emergen Research. The increasing implementation of data generation through sensors is a key factor driving revenue growth of the market. Precision agriculture is one type of farm management strategy that can assist farmers in producing more crops with fewer resources. The next big thing in farming may be AI-powered precision agriculture. To assist farmers to maximize yields and cut costs, precision farming combines the best soil management techniques, variable rate technologies, and the most efficient data management processes. Farmers may identify fields that require irrigation, fertilizer, or pesticide application by using real-time insights from AI. Additionally, innovative farming techniques such as vertical agriculture may assist boost food production while using fewer resources. Herbicide use is reduced, harvest quality is improved, earnings are increased, and there are significant cost savings as a result.

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Major Players/Manufacturers profiled in the report are:

Microsoft Corporation, Descartes Labs, Inc., Gamaya Inc., Precision Hawk, Connecterra B.V, Autonomous Tractor Corporation, Taranis, IBM Corporation, Granular Inc., and VineView.

However, precision agriculture and smart farming create a number of legal questions that frequently go unresolved since there are no defined norms and regulations surrounding the use of AI in general, not just in agriculture. Farmers may experience severe issues as a result of privacy and security threats such as cyberattacks and data leaks; these dangers can affect a lot of farms. The agricultural industries in developing nations are distinct from those in Western Europe and the U.S.  AI in agriculture may be advantageous in some areas, but it may be challenging to market such technology in places where agricultural technology is uncommon. Farmers will probably require assistance implementing it. Therefore, IT companies may need to adopt a proactive strategy if they want to conduct business in areas with developing agricultural economies. They will need to offer training and continuous assistance for farmers and agribusiness owners who are prepared to adopt innovative solutions in addition to their products.

Some Key Highlights From the Report

The software segment is expected to register significant market revenue growth. AI-based software boosts crop productivity and yield by utilizing prediction-based analytics and computer vision. The advantages of AI-enabled software for upcoming applications in agriculture, such as drone analytics and precision farming, are what is really driving the market’s growth.

The predictive analysis segment is expected to grow considerably. One of the most intriguing technologies now being used, significantly modified, and created is predictive analytics. Only a handful of the numerous statistical methods that make up predictive analytics as a whole include modeling, machine learning, and data mining.

The drone analytics segment is expected to register steady growth. The majority of the labor-intensive task associated with growth can be eliminated by using drones to explore an area and unearth new information. Drone analytics help identify plant stress, assess the health and productivity of plants, and There are a variety of tasks that can be accomplished, including the detection of resistant weeds or invasive species, altering nitrogen fertilization for row crops, speedy storm damage assessment to settle claims, optimum water use by keeping track of drought stress at different growth stages, inventorying plant population, size, and health, offering guidance on the best time to harvest, and accurately estimating yield.

The market in Europe is expected to register considerable growth. Agriculture, which is in charge of approximately half of Europe’s economy, is the main industry there.

On 26 April 2020, in an effort to increase the effectiveness, openness, and sustainability of world food production, IBM and Yara International (Norway), a leader in crop nutrition and digital farming solutions, have extended an invitation to farmer associations, business stakeholders, academic institutions, and non-governmental organizations (NGOs) in the food and agriculture sector.

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Emergen Research has segmented the artificial intelligence in agriculture market on the basis of component, technology, application, and region:

 Component Outlook (Revenue, USD Billion; 2019–2030)

Hardware

Software

Technology Outlook (Revenue, USD Billion; 2019–2030)

Machine Learning & Deep Learning

Computer Vision

Predictive Analysis

Application Outlook (Revenue, USD Billion; 2019–2030)

Precision Farming

Drone Analytics

Agriculture Robots

Others

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Regional Outlook (Revenue, USD Billion; 2019–2030)

North America

U.S.

Canada

Mexico

Europe

Germany

France

U.K.

Italy

Spain

Benelux

Rest of Europe

Asia Pacific

China

India

Japan

South Korea

Rest of APAC

Latin America

Brazil

Rest of LATAM

Middle East & Africa

Saudi Arabia

U.A.E.

South Africa

Turkey

Rest of MEA

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Key Benefits of Buying the Global Artificial Intelligence in Agriculture Report:

Comprehensive analysis of the changing competitive landscape

Assists in decision making processes for the businesses along with detailed strategic planning methodologies

The report offers an 8-year forecast and assessment of the Global Artificial Intelligence in Agriculture Market

Helps in understanding the key product segments and their estimated growth rate

In-depth analysis of market drivers, restraints, trends, and opportunities

Comprehensive regional analysis of the Global Artificial Intelligence in Agriculture Market

Extensive profiling of the key stakeholders of the business sphere

Detailed analysis of the factors influencing the growth of the Global Artificial Intelligence in Agriculture Market

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