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Artificial Intelligence in Agriculture Market Segmentation by Technology (Machine Learning, Computer Vision, and Predictive Analytics); by Deployment (Cloud, On-Premise, and Hybrid); by Offering (Software, Hardware, AI-as-a-Service, and Services); and by Application (Weather Tracking, Precision Farming, and Drone Analytics) – Global Demand Analysis & Opportunity Outlook 2030

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Inflation And Looming Recession to Haunt Businesses:

In 2022 & 2023, market players expected to sail in rough waters; might incur losses due to huge gap in currency translation followed by contracting revenues, shrinking profit margins & cost pressure on logistics and supply chain. Further, U.S. economy is expected to grow merely by 3% in 2022.

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Purchasing power in the couPurchasing power in the country is expected to fell nearly by 2.5%. On the other hand, European countries to see the worst coming in the form of energy crisis especially in upcoming winters!! Right after COVID-19, inflation has started gripping the economies across the globe. Higher than anticipated inflation, especially in western world had raised concerns for national banks and financial institutions to control the economic loss and safeguard the interest of the businesses. Increased interest rates, strong USD inflated oil prices, looming prices for gas and energy resources due to Ukraine-Russia conflict, China economic slowdown (~4% in 2022) disrupting the production and global supply chain and other factors would impact each industry negatively.                                                         Request Insights

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  • April 2021- Trimble and HORSCH partnered to enable autonomy in agriculture with the goal of building a future for workflows and autonomous machines in the industry.

  • January 2019- Microsoft India embarked on a journey to bring AI sensors to agricultural fields with the aim of increasing yields and reducing costs with the help of smartphones.

Global Artificial Intelligence in Agriculture Market Highlights 2022 – 2030

The global artificial intelligence in agriculture market is estimated to garner a large amount of revenue and grow at a CAGR of ~25% over the forecast period, i.e., 2022 – 2030. The growth of the market can be primarily attributed to the increasing usage of smart sensors in agricultural fields, and the upsurge in demand for agricultural produce around the globe. According to the World Bank, in 2018, agriculture accounted for 4 percent of the global gross domestic product and in some developing countries it accounted for more than 25 percent of the GDP. Along with these, there is a high demand for real-time livestock monitoring globally, which is giving impetus to the application of advanced AI solutions, such as facial recognition for livestock and image classification with body condition score. This in turn is expected to significantly drive market growth in the near future. Furthermore, growing government initiatives towards the adoption of drones for modernizing agricultural practices is projected to offer ample growth opportunities to the market in the near future.

Artificial Intelligence in Agriculture Market Graph

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The market is segmented by technology into machine learning, computer vision, and predictive analytics, out of which, the machine learning segment is anticipated to hold the largest share in the global artificial intelligence in agriculture market. This can be accounted to the rising adoption of machine learning-enabled solutions by agricultural organizations and farmers around the world for enhancing their farm productivity and gaining a competitive edge in business operations. Additionally, on the basis of offering, the software segment is predicted to acquire the most significant share during the forecast period, which can be credited to the growing usage of AI software to increase farm efficiency, and high integration of mobile technologies with farming techniques. Apart from these, intensifying demand for real-time data management systems is also assessed to boost the growth of the market segment in the imminent time. 

Major Macro-Economic Indicators Impacting the Market Growth

Research and Development Expenditure Graph

The never-ending growth in internet accessibility around the world along with numerous technological advancements comprising 5G, blockchain, cloud services, Internet of Things (IoT), and Artificial Intelligence (AI) among others have significantly boosted the economic growth in the last two decades. As of April 2021, there were more than 4.5 billion users that were actively using the internet globally. Moreover, the growth in ICT sector has significantly contributed towards GDP growth, labor productivity, and R&D spending among other transformations of economies in different nations of the globe. Furthermore, the production of goods and services in the ICT sector is also contributing to the economic growth and development. As per the statistics in the United Nations Conference on Trade and Development’s database, the ICT good exports (% of total good exports) globally grew from 10.816 in 2015 to 11.536 in 2019. In 2019, these exports in Hong Kong SAR, China amounted to 56.65%, 25.23% in East Asia & Pacific, 26.50% in China, 25.77% in Korea, Rep., 8.74% in the United States, and 35.01% in Vietnam. These are some of the important factors that are boosting the growth of the market.

Global Artificial Intelligence in Agriculture Market Regional Synopsis

On the basis of geographical analysis, the global artificial intelligence in agriculture market is segmented into five major regions including North America, Europe, Asia Pacific, Latin America and the Middle East & Africa region. The market in the Asia Pacific is estimated to witness noteworthy growth over the forecast period on the back of the growing adoption rate of AI in agriculture in countries such as India, China, Japan and Australia, and entry of major companies in agricultural solutions business in the region. In addition, growing investments by multinational companies to spread awareness regarding farm analytics and data sciences among farmers is also predicted to boost the region’s market growth in the upcoming years. Moreover, the market in North America is anticipated to gather the largest share during the forecast period owing to the early adoption of technologies such as machine learning and IoT, and rising usage of computer vision for agricultural applications, such as livestock management, precision farming and soil management. In 2021, almost 80 percent of the total number of companies in North America have adopted machine learning technology. More than 4 percent of self-reported data scientists or data researchers in the US specifically work as machine learning engineers.

Artificial Intelligence in Agriculture Market Share Image

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The global artificial intelligence in agriculture market is further classified on the basis of region as follows:

  • North America (U.S. & Canada) Market size, Y-O-Y growth, Market Players Analysis & Opportunity Outlook
  • Latin America (Brazil, Mexico, Argentina, Rest of Latin America) Market size, Y-O-Y growth & Market Players Analysis & Opportunity Outlook
  • Europe (U.K., Germany, France, Italy, Spain, Hungary, Belgium, Netherlands & Luxembourg, NORDIC (Finland, Sweden, Norway, Denmark), Ireland, Switzerland, Austria, Poland, Turkey, Russia, Rest of Europe), Poland, Turkey, Russia, Rest of Europe) Market size, Y-O-Y growth Market Players Analysis & Opportunity Outlook
  • Asia-Pacific (China, India, Japan, South Korea, Singapore, Indonesia, Malaysia, Australia, New Zealand, Rest of Asia-Pacific) Market size, Y-O-Y growth & Market Players Analysis & Opportunity Outlook
  • Middle East and Africa (Israel, GCC (Saudi Arabia, UAE, Bahrain, Kuwait, Qatar, Oman), North Africa, South Africa, Rest of Middle East and Africa) Market size, Y-O-Y growth Market Players Analysis & Opportunity Outlook

Market Segmentation

Our in-depth analysis of the global artificial intelligence in agriculture market includes the following segments:

By Technology

  • Machine Learning
  • Computer Vision
  • Predictive Analytics

By Deployment

  • Cloud
  • On-Premise
  • Hybrid

By Offering

  • Software
  • Hardware
  • AI-as-a-Service
  • Services

By Application

  • Weather Tracking
  • Precision Farming
  • Drone Analytics

Growth Drivers

  • Increasing Usage of Smart Sensors in Agricultural Fields
  • Upsurge in Demand for Agricultural Produce Globally


  • High Cost of Gathering Precise Field Data

Top Featured Companies Dominating the Market

  • Microsoft Corporation
    • Company Overview
    • Business Strategy
    • Key Product Offerings
    • Financial Performance
    • Key Performance Indicators
    • Risk Analysis
    • Recent Development
    • Regional Presence
    • SWOT Analysis 
  • AgEagle Aerial Systems Inc.
  • Descartes Labs, Inc.
  • IBM Corporation
  • John Deere and Company
  • The Climate Corporation
  • Trimble Inc.
  • aWhere Inc.
  • Farmers Edge Inc.
  • Prospera Technologies Ltd.


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