Artificial intelligence (AI) in agriculture market size was valued at US$ 1.63 billion in 2022 and is expected to reach US$ 7.97 billion by 2030; it is estimated to record a CAGR of 21.9% from 2022 to 2030.
The report includes growth prospects in light of current artificial intelligence (AI) in agriculture market trends and driving factors influencing the market growth.
Artificial Intelligence (AI) in Agriculture Market Analyst Perspective:
Unmanned Aerial Vehicles (UAVs), also known as drones, are making waves in the agricultural industry by offering smart farming solutions that use real-time data collection and processing to improve farm-wide decision-making and efficiency, freeing up time and money that could be used elsewhere in farm businesses. UAVs offer significant advantages in various agricultural tasks, including air spraying, air seeding, remote sensing detection, and data collection. Due to such huge applications, the use of UAVs is growing significantly in the agriculture industry. For example, in October 2023, ATV, a France-based manufacturer of anti-freeze tower blades and composite industrial parts, partnered with UrbanMatrix Technologies. This alliance's objective is to address the frost problem by harnessing cutting-edge UAV solutions, marking a significant step toward smart farming. To cite another example, in February 2022, the Prime Minister of India, Narendra Modi, launched 100 Made-in-India agricultural drones across the country, which carried out farm operations in unique simultaneous flights. Thus, due to their huge applications, the use of UAVs is growing in farming. UAV, along with AI, revolutionizes agricultural monitoring by collecting real-time data on plant health and soil conditions. AI systems then examine this data to provide useful insights for optimal resource allocation, such as water and fertilizers. Thus, the growing use of UAVs in farming drives the growth of artificial intelligence (AI) in agriculture market
Artificial Intelligence (AI) in Agriculture Market Overview:
Artificial intelligence (AI) is transforming agriculture and associated sectors. Technologies such as predictive analytics, machine learning, computer vision, and data analytics are helping agriculture overcome hurdles and reach its full potential. The use of Al in agriculture enables data collection and analysis from several sources, including soil conditions, weather patterns, crop health, and historical data.
Al-based systems can provide farmers with important information to boost yields, reduce waste, and limit environmental concerns. Farmers and stakeholders can use data-driven insights and intelligent decision-making to improve productivity, optimize resource consumption, and manage agronomic challenges. Al in agriculture can automate tedious chores with smart machinery and robotics. These innovations reduce workforce shortages and enable farmers to prioritize strategic planning and management.
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Artificial Intelligence (AI) in Agriculture Market: Strategic Insights
Market Size Value in US$ 1.63 billion in 2022 Market Size Value by US$ 7.97 billion by 2030 Growth rate CAGR of 21.9% from 2022 to 2030 Forecast Period 2022-2030 Base Year 2022
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Artificial Intelligence (AI) in Agriculture Market: Strategic Insights
| Market Size Value in | US$ 1.63 billion in 2022 |
| Market Size Value by | US$ 7.97 billion by 2030 |
| Growth rate | CAGR of 21.9% from 2022 to 2030 |
| Forecast Period | 2022-2030 |
| Base Year | 2022 |
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Artificial Intelligence (AI) in Agriculture Market Driver:
Growing Government Support for Implementation of AI Solution to Boost Artificial Intelligence (AI) in Agriculture Market Growth
Governments across the world are transforming the agriculture sector to be more efficient, sustainable, and inclusive to ensure food security. Governments around the world encourage the implementation of Al for agricultural applications in order to provide aid to farmers. The governments of North American countries leveraged AI in agriculture to automate weed detection and optimize irrigation while addressing issues such as workforce stability and data privacy concerns. For instance, in November 2023, the US Senate Committee on Agriculture, Nutrition, and Forestry held a hearing, "Innovation in American Agriculture: Leveraging Technology and Artificial Intelligence (AI)."
The Indian government is taking several steps to digitalize the agriculture sector. In response to agriculture issues, the World Economic Forum's Artificial Intelligence for Agriculture Innovation (AI4AI) program is being set up to help India's agricultural transformation by promoting the use of artificial intelligence (AI) and related technologies. One of the most successful AI4AI implementations is the "Saagu Baagu" pilot in July 2021, which was designed in collaboration with the Telangana State Government in the Khammam area. The program was backed by the Bill & Melinda Gates Foundation and implemented by Digital Green. The project has significantly improved the value chain for over 7,000 producers. Thus, such growing government support and initiatives are propelling the artificial intelligence (AI) in agriculture market growth.
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Artificial Intelligence (AI) in Agriculture Market Report Segmentation and Scope:
Artificial intelligence (AI) in agriculture market analysis has been carried out by considering the following segments: component, application, and geography. Based on component, the market is divided into hardware, software, and services. Based on application, the market is segmented into precision farming, drone analytics, agriculture robots, livestock monitoring, and others. Based on deployment, the market is divided into on-premise, cloud-based, and hybrid. Based on geography, the market is segmented into North America, Europe, Asia Pacific, the Middle East & Africa, and South & Central America.
By application, the artificial intelligence (AI) in agriculture market is segmented into precision farming, drone analytics, agriculture robots, livestock monitoring, and others. The precision farming segment accounted for the largest artificial intelligence (AI) in agriculture market share in 2022. Precision farming is the discipline of improving crop yields and assisting management decisions using high-technology sensor and analysis tools. It is a new concept adopted worldwide to reduce labor time, increase production, and guarantee effective management of fertilizers and irrigation processes. Various players globally collaborate to provide precision farming. In October 2023, Zuari FarmHub, an agritech company in India, announced its partnership with CropX Technologies, an agri-tech company specializing in digital agronomic solutions. The collaboration aims to revolutionize farming practices by introducing real-time monitoring technology that empowers farmers with data-driven insights for enhanced productivity and sustainability. The collaboration signifies a major milestone in advancing precision agriculture.
The drone analytics segment is anticipated to hold a significant artificial intelligence (AI) in agriculture market share by 2030. AI-enabled drone analytics allow farmers to monitor enormous agricultural tracts efficiently. Instead of undertaking time-consuming manual inspections, AI systems can automatically evaluate drone-captured data to identify areas that need care. This streamlines operations, reduces labor costs, and allows farmers to make informed decisions based on accurate and timely data. Aerial data generated by drones can be viewed, used, and analyzed by farmers with the help of drone analytics software. Using drone-acquired data for analytics in agriculture offers several significant benefits to the agriculture industry. Drone analytics in agriculture can provide details such as identifying resistant weeds or invasive species, adjusting nitrogen fertilization for row crops, providing guidance for optimal harvest timing, and accurately estimating yield. Such huge applications of drone analytics propel the growth of artificial intelligence (AI) in agriculture market.
AI-powered agriculture robots help farmers to improve production yields. Right from drones to autonomous tractors to robotic arms, AI technology is deployed in creative and innovative applications. Agricultural robots perform repetitive, slow, and dull tasks, which allow farmers to focus more on improving overall production yields. They also use resources more efficiently, enhance productivity, and lower food production costs. Further, various players across the region are unveiling AI-powered agriculture robots. For example, in January 2023, Meropy developed an AI-powered agricultural robot that autonomously inspects crops, saving farmers time and money. Such instances propel the growth of artificial intelligence (AI) in agriculture market.
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Artificial Intelligence (AI) in Agriculture Market Regional Analysis:
The Asia Pacific artificial intelligence (AI) in agriculture market is segmented into Australia, China, India, Japan, South Korea, and the Rest of Asia Pacific. China dominated the artificial intelligence (AI) in agriculture market in 2022. In response to reinforcing the nation's food security through technological innovation and bringing enough food to arid and urban areas, China opened unmanned veggie farms. In December 2023, Chinese scientists put the world's tallest unmanned vertical farm into operation in the southwestern province of Sichuan, with automated facilities that provide year-round harvests. Moreover, various players across China launched components for AI in agriculture. For example, in November 2022, DJI Agriculture introduced the Mavic 3 Multispectral, which includes a multispectral imaging system that quickly captures crop growth information to achieve more effective crop production for a wide range of application scenarios in precision agriculture and environmental monitoring, assisting farmers around the world in improving the quality and efficiency of their production, lowering costs and increasing income.
Artificial Intelligence (AI) in Agriculture Market Competitive Analysis:
The artificial intelligence (AI) in agriculture market forecast can help stakeholders plan their growth strategies. Tule Technologies Inc, Precisionhawk Inc, Easytosee Agtech Sl, Deere & Co, Climate LLC, Gamaya Sa, International Business Machines Corp, Microsoft Corp, Prospera Technologies Ltd, and Taranis are among the prominent players profiled in the artificial intelligence (AI) in agriculture market report. In addition, several other players have been studied and analyzed during the study to get a holistic view of the market and its ecosystem.
Artificial Intelligence (AI) in Agriculture Market Recent Developments:
Inorganic and organic strategies such as mergers and acquisitions are highly adopted by companies in the Artificial Intelligence (AI) in Agriculture Market. As per company press releases, below are a few recent key developments:
- In 2023, Chipotle Mexican Grill announced minority investments in Greenfield Robotics and Nitricity. The investment from Chipotle will help Greenfield Robotics expand its fleet and develop additional capabilities for its robots, such as micro-spraying, cover crop planting, and soil testing.
- In 2022, AgroCares, an ag-tech company that provides data-driven nutrient testing solutions, and trinamiX GmbH, a leading provider of mobile spectroscopy, announced a collaboration to incorporate trinamiX's high-performance hardware into AgroCares' next-generation Nutrient Scanner solution.
- In 2022, Valmont Industries, Inc. entered into a definitive agreement to acquire Prospera Technologies Inc. ("Prospera"). The transaction was valued at ~US$ 300 million. The acquisition builds on Valmont's successful partnership and focuses on achieving higher crop yields using fewer resources.
Report Coverage
Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends
Segment Covered
Component and Application
Regional Scope
North America, Europe, Asia Pacific, Middle East & Africa, South & Central America
Country Scope
This text is related
to country scope.
Frequently Asked Questions
The artificial intelligence (AI) in agriculture market was estimated to be valued at US$ 1.6. billion in 2022 and is projected to reach US$ 7.9 billion by 2030; it is expected to grow at a CAGR of 21.9% during the forecast period.
Increasing need for real-time analytics in agriculture, growing government support for implementation of AI solution, and growing use of unmanned ariel vehicles (UAVs) in Farming are driving factors of artificial intelligence (AI) in agriculture market.
Robotics and automation in agriculture is expected to set the future trend for the artificial intelligence (AI) in agriculture market in the coming years.
The key players holding majority shares in artificial intelligence (AI) in agriculture market include Microsoft, Corp., IBM Corp., Wipro, Valmont Industries, Inc., and Granular Inc.
The artificial intelligence (AI) in agriculture market is expected to reach US$ 7.97 billion by 2030.
Asia Pacific is anticipated to grow with the highest CAGR over the forecast period.
Software segment led the artificial intelligence (AI) in agriculture market with a significant share in 2022 and hardware segment is expected to grow with the highest CAGR.
The List of Companies - Artificial Intelligence In Agriculture Market
- IBM Corporation
- Microsoft
- Deere & Company
- The Climate Corporation
- Prospera Technologies
- Taranis
- GAMAYA
- ec2ce
- PrecisionHawk
- Tule Technologies Inc.
The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.
- Data Collection and Secondary Research:
As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.
Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.
- Primary Research:
The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.
For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.
A typical research interview fulfils the following functions:
- Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
- Validates and strengthens in-house secondary research findings
- Develops the analysis team’s expertise and market understanding
Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:
- Industry participants: VPs, business development managers, market intelligence managers and national sales managers
- Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.
Below is the breakup of our primary respondents by company, designation, and region:
Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.
- Data Analysis:
Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.
- 3.1 Macro-Economic Factor Analysis:
We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.
- 3.2 Country Level Data:
Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.
- 3.3 Company Profile:
The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.
- 3.4 Developing Base Number:
Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.
- Data Triangulation and Final Review:
The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.
We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.
We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.
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