Artificial Intelligence In Agriculture Market Size, Share, Trends & Analysis Report 2020-2027

Artificial Intelligence In Agriculture Market Size, Share, Trends & Analysis Report 2020-2027

Artificial intelligence in agriculture market growth and trends

The Global AI in the agriculture market size was estimated at USD 527 million in 2019 and it is projected to grow at a cagr of 21.1% from 2020 to 2027. Artificial intelligence (AI) helps to improve the productivity of agricultural land and cost reduction. The technology can accurately calculate the net output and timeline from a piece of land using advanced machine learning and predictive analytics. AI is also being used in the agriculture sector for crop health monitoring and Diagnostic applications.

Artificial intelligence is also known as AI is the revolutionary technology that is being used in almost all of the machinery in today’s world, it basically enables the Machines to work smartly and give maximum output without any human interference. The agricultural sector is highly underdeveloped and utilization minimum Technology, this trend is partially observable in the developing economy where the farming sector is economically weak and unorganized. However as technological advancements are appearing in the agricultural sector, awareness is being created among farmers to showcase to them how technology can benefit there day to day farming tasks and improve their crop productivity substantially compared to the traditional farming methods. 

Artificial intelligence in the agriculture market is a completely new concept with a very large scope of development, many new companies as well as established ones are investing in developing advanced farming Technologies using artificial intelligence. The AI in the agriculture market is capable of the following key functionalities:

  • Predictive Analytics
  • Crop yield estimation and forecasting
  • Crop health monitoring
  • Pest detection and preventive measures
  • Training and education of farmers
  • In-depth analytics related to Agricultural productivity

The world has witnessed an outburst in the Global population in the last century, we are moving towards reaching the 8 billion population mark in the upcoming few years. This substantial growth in the human population has created a huge gap in the demand and supply of food. The existing techniques used for agriculture incapable of producing the output necessary to fulfill the growing population demand. Continuing with the traditional method may create problematic situations such as poverty and malnourishment in the majority of the population especially in developing countries. To cope up with such tragic situations, we need to implement its technology in the agricultural sector in order to improve the overall crop productivity. Technologies such as artificial intelligence, machine learning, augmented and virtual reality, Big Data Analytics, Internet of things (IoT) Mein enable technological transformation in the agricultural industry in the next 10 years. 

The application of various technologies including drones, infrared cameras, and robots is increasing in the agriculture sector. The cameras monitor the agricultural field to determine crop health and pest attack, it is also capable of predicting the optimum water level for crops. Companies such as Microsoft are working towards creating AI-based agriculture Technology to accurately predict the harvest and net yield forecasts. Automation using machine learning has enabled timely e water and pesticides sprinkling on the crops in order to improve overall net output.

Component Type Overview

The AI in the agriculture market has been segmented based on component type into hardware, software, and services. Technological advancement in the software segment is expected to boost the segmental growth in the upcoming few years. The availability of numerous developmental platforms for software has enabled the development of more advanced software that can fulfill key requirements of almost all agricultural businesses. It is highly necessary for companies to standardize the deployment platform so that are universal ecosystem can be created and may improve the rate of agriculture application development. The growing usage of Technologies such as predictive Analytics for analyzing the net crop yield is expected to boost the demand for the AI-based agriculture software market.

Companies such as IBM, Microsoft Corporation, Deer, and Company are investing heavily in the development of AI-based agriculture solutions that may perform functions such as crop yield Estimation and forecasting, crop health monitoring, water level management, and monitoring, big data, and other.

Application overview

The artificial intelligence in the agriculture market can be segmented based on the application type into Precision farming, livestock management & monitoring, agricultural robotics, remote monitoring & Analytics, and others. The market has been dominated by the Precision farming segment with a greater than 40% market share in 2019. Precision farming enables the farmers to optimize the farming related operations, reduce operational costs, and improve the overall productivity. Precision farming act as a central nerve for the AI-based agriculture solutions, basically it collects all the data through various sensors and equipment, analyze it, and provide valuable information for improving the overall process.

Technology overview

On the basis of Technology, the AI in the agriculture market has been segmented into Predictive Analytics, machine learning, and computer vision. Predictive Analytics act as a key backbone of enabled agricultural solutions, It enables advanced features such as irrigation management, pesticide control, and monitoring, crop Health Management, weather tracking, and forecasting. Therefore the predictive analytics segment is expected to grow substantially between 2020 to 2027.

The machine learning and deep learning segment are expected to grow at a cagr of 23.35% over the forecast period, these technologies are widely used for agriculture and farming automation and hold huge market growth potential.

Regional overview

The North America region is the most technologically advanced in the world, the region accounted for the largest Market share in 2019. The technological penetration and adoption rate in the United States and Canada is considerably higher as compared to other countries. Moreover, the per capita income and purchasing power of the United States is also substantially higher compared to the rest of the world, therefore the region is expected to witness a high growth rate over the forecast period.

Increasing agriculture development projects and government initiatives in the Asia Pacific region is anticipated to boost the regional market growth rate over the projected period. The Asia-pacific region is a mixture of hardware manufacturing countries such as China, Japan, and Taiwan as well as software manufacturing hubs such as India. Therefore the Asia Pacific AI in the agriculture market is anticipated to witness an exponential growth rate over the forecast period.

AI in the agriculture market share insights 2020

Global AI in the agriculture market is dominated by companies such as Microsoft Corporation, IBM Corporation, Prospera Technologies, Deer & Company among others. Companies are competing on the basis of AI-based solution features and advancements. The companies are also practicing strategic initiatives such as mergers, acquisitions, partnerships/collaboration, and Research and Development in order to improve their overall market share.

Although the AI in the agriculture market is growing at an exponential growth rate, it is highly necessary for companies to create awareness among farmers in developing countries. Companies may start educational or training programs to create awareness about artificial intelligence and its application in the agriculture sector.


Market Segmentation

  • Global AI in Agriculture Component Overview (Revenue, USD Million, 2017 – 2027)
    • Hardware
    • Software
    • Services
  • Global AI in Agriculture Technology Overview (Revenue, USD Million, 2017 – 2027)
    • Predictive Analytics
    • Machine Learning
    • Computer vision
  • Global AI in Agriculture Application Overview (Revenue, USD Million, 2017 – 2027)
    • Precision farming
    • Livestock management & monitoring
    • Agricultural robotics
    • Remote monitoring & Analytics
    • Others
  • Global AI in Agriculture Regional Overview (Revenue, USD Million, 2017 – 2027)
    • North America
      • The U.S.
      • Canada
    • Europe
      • UK
      • Germany
      • France
    • Asia Pacific
      • China
      • India
      • Japan
      • South Korea
      • Taiwan
    • Latin America
      • Brazil
      • Mexico
    • Middle East & Africa
      • UAE
      • KSA



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