Artificial Intelligence in Agriculture Market Size, Share and Growth

Updated on : October 22, 2024

Artificial Intelligence in Agriculture Market Size & Growth

The Artificial Intelligence in Agriculture Market size is projected to grow from USD 1.7 billion in 2023 to USD 4.7 billion by 2028; growing at a Compound Annual Growth Rate (CAGR) of 23.1% from 2023 to 2028.

AI in agriculture offers several advantages to the farmers such as real-time insights from their fields, monitor soil quality, plant health, temperature, automate irrigation, pesticide process- all of which are helping to improve the overall harvest quality and accuracy. AI in agriculture has various applications aimed at optimizing the efficiency of crop production such as precision farming, livestock monitoring, drone analytics, agriculture robots, labor management.  Increasing crop productivity through deep learning technology driving the growth of the AI in agriculture market.

The objective of the report is to define, describe, and forecast the artificial intelligence in agriculture market share based on technology, offering, application and region.

Artificial Intelligence in Agriculture Market Forecast to 2028

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Artificial Intelligence in Agriculture Market Trends:

Rising need for real-time data by growers and farmers to take preventive measures

Increasing agricultural activities and the growing need for real-time data largely drive the market for AI in agriculture. Real-time data from agricultural farms help make prompt decisions regarding preventive measures. Farmers from North America, South America, and Europe use sensors, drones, guidance technologies, and soil sampling techniques to gather data on soil moisture and nutrient levels across their fields. Farmers and growers from the US, Canada, Brazil, and most Western European countries are turning to high-tech tools for data collection and data analysis. Drone-enabled scouting is one of the most convenient ways of collecting farm data.

Government schemes encouraging adoption of AI solutions to manage small farms

There are over 570 million farms worldwide, and 95% of all these farms are less than 5 hectares in size. AI solutions are predominantly implemented in farms with over 100 hectares of land. This can be attributed to the high initial investment required for implementing AI solutions. Farmers owning lands over 100 hectares generally have the capability to invest in AI-based solutions for farm management and other applications. However, with governments around the world supporting the use of AI for agricultural applications and providing aid to farmers with small farms, there is an opportunity for solution providers to focus on farms with less than 5 hectares of land. For instance, in the US, the Department of Agriculture provides small and mid-size producers with programs that avail farmers with easy loans and improve their technological know-how to use the best technology for farming.

High cost of AI-driven precision farming equipment

The major restraining factor for the AI in agricultural market is the high cost of AI-enabled farming products and solutions, including sensors, software, and robots. Many factors are responsible for the high cost of gathering precise field data. For instance, companies develop AI-powered solutions or platforms according to customer requirements. They offer AI-powered prebuilt and custom-built solutions such as analytics systems, virtual assistants, and chatbots. Similarly, AI features and AI management are also important factors that incur additional costs.

Availability of limited workforce with technological expertise

Artificial intelligence (AI) is a complex system, and for developing, managing, and successfully implementing AI systems, farmers require certain skill sets. For instance, people dealing with AI systems should know about technologies such as cognitive computing, machine learning, deep learning, and image recognition. In addition, the integration of AI solutions in existing systems is a difficult task that requires extensive data processing to replicate the behavior of a human brain. Even a minor error can result in system failure or adversely affect the desired result.

Artificial Intelligence in Agriculture Market Segmentation

Machine learning enabled AI in agriculture contributes largest market share through the forecast period.”

Machine learning-enabled solutions are being significantly adopted by agricultural organizations and farmers worldwide to enhance farm productivity and to gain a competitive edge in business operations. Technological advancement and proliferation in farm data generation are some of the major driving factors for the AI in agriculture market. With the use of machine learning farmers able to capture the factor of soil, seeds quality fertilizer application, environmental variables and irrigation.

AI in agriculture market for software segment is to hold the largest market share through the forecast period.

artificial intelligence in agriculture market share has been segmented based on offerings into hardware, software, AI-as-a-service, and service. Software segment is to hold the largest market share through the forecast period. The software integrated into a computer system is responsible for carrying out complex operations. It synthesizes the data received from the hardware and processes it in the AI system to generate an intelligent response. Furthermore software segment is segmented into AI platform and AI solution. Where in AI platform data is combined with a decision-making algorithm to enable developers to create a business solution.

Precision farming application of AI in agriculture to hold significant share during the forecast period”

The market for precision farming applications was valued at USD 542 million in 2022 and is projected to reach USD 1,432 million by 2028; it is expected to grow at a CAGR of 20.5% during the forecast period. This segment is likely to continue to hold the second-largest market share in the coming years due to the high adoption rate of AI technologies for precision farming applications. Precision farming and automatization in food production are priorities for food growers in the current situation, and AI fuels the gains.

Market for computer vision technology based AI products is expected to grow at highest CAGR during forecasted period.

The AI in agriculture market has been segmented based on technology into machine learning, computer vision, and predictive analytics. Artificial intelligence in agriculture market for computer vision technology based AI products is expected to grow at highest CAGR during forecasted period. This high growth rate is attributed to the rising need for continuous monitoring and analysis of crop health and increasing use of computer vision technology in agricultural applications such as sorting the produce according to weight, color, size, and ripeness and identifying defects in agricultural produce.

Artificial Intelligence in Agriculture Industry Regional Analysis

North America is to contribute the largest in the market during the forecast period

The North America held the largest artificial intelligence in agriculture market share during the forecast period. The AI in agriculture industry in this region has been segmented into US, Canada and Mexico. North America has large scale agriculture players in the region are already using AI technology to significantly improve the speed and accuracy of their planting and crop management techniques. The demand for advanced agricultural solutions is expected to drive the growth of the AI in agriculture market in this region.

Artificial Intelligence in Agriculture Market by Region

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In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews have been conducted with key industry experts in the AI in agriculture market space. The break-up of primary participants for the report has been shown below:

• By Company Type: Tier 1 – 45%, Tier 2 – 35%, and Tier 3 – 20%
• By Designation: C-level Executives – 35%, Directors – 43%, and Others – 22%
• By Region: North America –33%, Asia Pacific– 30%, Europe – 24%, and RoW – 13%

Top Artificial Intelligence in Agriculture Companies - Key Market Players

• Deere & Company (US),
• IBM (US),
• Microsoft (US),
• The Climate Corporation (US),
• Farmers Edge Inc. (Canada),
• Granular Inc. (Canada), 
• AgEagle Aerial Syatems Inc. (US),
• Descartes Labs, Inc. (US).

Artificial Intelligence in Agriculture Market Report Scope

Artificial Intelligence in Agriculture Market Highlights

This report categorizes the AI in agriculture market share based on technology, offering, application, geography.

Recent Developments in Artificial Intelligence in Agriculture Industry

• In May 2022, Alliance for a Green Revolution in Africa (AGRA) and Microsoft announced the expansion of their partnership to advance digital agriculture transformation in Africa to improve food security. The partnership of AGRA with Microsoft will support governments, farmers, and small and medium-sized enterprises (SMEs) to build food systems in the region by using digital tools provided by Microsoft.
• In February 2022, Farmers Edge and Deere & Company (US), a manufacturer of agriculture machinery and heavy equipment, entered into an agreement allowing users of FarmCommand to integrate their data with the John Deer Operations Center account. This will give users the insights to make decisions that drive yields and profits.
• In October 2021, IBM launched the IBM Environment Intelligence Suite, an AI-driven software for environment intelligence that helps companies anticipate the climate risks, such as floods and wildfires, and understand agricultural production and market intelligence by providing weather data, climate risk analytics, and carbon accounting.
• In March 2021, Climate LLC, a Bayer Crop Science Digital arm subsidiary, launched the industry-leading digital farming platform, climate FieldView, in South Africa. Launching the product in the African region helps the farmers manage risk and increase productivity while simplifying their operations actively.
• In January 2020, Descartes Labs launched a cloud-based geospatial data refinery and modeling platform called the Descartes Labs Platform. This platform has improved forecasting abilities in agriculture.

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