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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. Robotics and automation in agriculture are likely to remain key trends in the market.
Artificial Intelligence (AI) in Agriculture Market Analysis
Shifting preference from traditional to AI-based farming methods, growing use of unmanned ariel vehicles (UAVs) in farming, and increasing need for real-time analytics in agriculture are driving the market. The market is anticipated to grow during the forecast period, due to the growing government support for implementation of AI solutions. Moreover, growing research and development activities to develop AI-based solutions and increasing smart farming are creating lucrative opportunities for the market.
Artificial Intelligence (AI) in Agriculture Market Overview
Artificial intelligence (AI) is revolutionizing agriculture industry. Predictive analytics, computer vision, machine learning, and data analytics are helping agriculture overcome obstacles and realize its full potential. The use of Al in agriculture allows for data collection and analysis from a variety of sources, including soil conditions, weather patterns, crop health, and historical data.
Al-based systems can provide farmers with valuable information for increasing yields, reducing waste, and minimizing environmental concerns. Farmers and stakeholders can employ data-driven insights and intelligent decision-making to boost productivity, optimize resource use, and deal with agronomic issues. Smart machinery and robotics can be used to automate monotonous tasks in agriculture. These advances help farms address workforce shortages and focus on 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 Drivers and Opportunities
Shifting Preference from Traditional to AI-based Farming Methods
Traditional potato growers across Canada have faced challenges in nutrient management, a crucial aspect of farming that directly impacts crop yields. The conventional methods of soil treatments and foliar feeding, while effective to a certain extent, have limitations, especially for nutrients required at later stages of potato growth. Thus, potato growers across Canada are deploying AI solutions to predict the nutritional needs of the potato plant. For example, in November 2023, with groundbreaking developments in the agricultural sector, Canadian potato growers are turning to AI to monitor and predict the nutritional needs of their crops in real-time. Thus, the adoption of AI by Canadian farmers propels the growth of AI in agriculture market.
Growing Research and Development Activities to Develop AI-based Solutions
The UK boasts world-class technology and research capabilities and is the global leader in the development of AI-enabled solutions. Moreover, UK researchers are using AI to revolutionize traditional industries such as farming. As per January 2024 data, researchers at Harper Adams University are trying to make farming more sustainable and productive with AI.
The UK government has also announced US$ 39.82 million in funding to support the development of artificial intelligence projects across diverse sectors such as farming, fashion, and emergency services. An additional US$ 5.38 million has been awarded to feasibility studies for 100 projects from small businesses, fostering innovative AI ideas to boost productivity across various sectors. Thus, such government support is projected to propel the growth of AI in agriculture market.
Artificial Intelligence (AI) in Agriculture Market Report Segmentation Analysis
Key segments that contributed to the derivation of artificial intelligence (AI) in agriculture market analysis are components and applications.
- Based on component, artificial intelligence (AI) in agriculture market is divided into hardware, software, and services. The hardware segment held a larger market share in 2022.
- In terms of application, the market is divided into precision farming, drone analytics, agriculture robots, livestock monitoring, and others. The precision farming segment held a larger market share in 2022.
Artificial Intelligence (AI) in Agriculture Market Share Analysis by Geography
The geographic scope of the artificial intelligence (AI) in agriculture market report is mainly divided into five regions: North America, Asia Pacific, Europe, Middle East & Africa, and South & Central America.
The market in Asia Pacific is projected to expand during the forecast period, due to the growing demand for technologically advanced solutions. In countries such as Australia, where the agricultural workforce is quickly aging, the demand for skilled labor is greater than ever. Farming, with its integration of cutting-edge technology such as Al and machine learning, holds the key to closing this gap and bringing agriculture into the contemporary era. Several Australian farmers are already witnessing the benefits of Al-powered systems. For example, in October 2023, the Sunray Strawberries at Wamuran deployed the DeepBerry automated monitoring system; the system uses both visual and infrared imaging to accurately detect ripeness, bruising, fungus, fruit size, shape, and foreign objects. It can process more than 7,000 gunnets per hour. Implementation of such automated systems propels the growth of Al in agriculture market.
Artificial Intelligence (AI) in Agriculture Market Report Scope
Artificial Intelligence (AI) in Agriculture Market News and Recent Developments
The artificial intelligence (AI) in agriculture market is evaluated by gathering qualitative and quantitative data post primary and secondary research, which includes important corporate publications, association data, and databases. A few of the developments in the artificial intelligence (AI) in agriculture market are listed below:
- 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. (Source: Chipotle Mexican Grill, Company Website, December 2023).
Artificial Intelligence (AI) in Agriculture Market Report Coverage and Deliverables
The “Artificial Intelligence (AI) in Agriculture Market Size and Forecast (2020–2030)” report provides a detailed analysis of the market covering below areas:
- Artificial intelligence (AI) in agriculture market size and forecast at global, regional, and country levels for all the key market segments covered under the scope
- Artificial intelligence (AI) in agriculture market trends as well as market dynamics such as drivers, restraints, and key opportunities
- Detailed PEST/Porter’s Five Forces and SWOT analysis
- Artificial intelligence (AI) in agriculture market analysis covering key market trends, global and regional framework, major players, regulations, and recent market developments
- Industry landscape and competition analysis covering market concentration, heat map analysis, prominent players, and recent developments for the artificial intelligence (AI) in agriculture market
- Detailed company profiles
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
Shifting preference from traditional to AI-based farming methods is the major factors that propel the global artificial intelligence (AI) in agriculture market.
North America dominated the artificial intelligence (AI) in agriculture market in 2023.
The global artificial intelligence (AI) in agriculture market is estimated to register a CAGR of 21.9% during the forecast period 2023–2031.
The global artificial intelligence (AI) in agriculture market is expected to reach US$ 9.48 billion by 2031.
Robotics and automation in agriculture to play a significant role in the global artificial intelligence (AI) in agriculture market in the coming years.
The key players holding majority shares in the global artificial intelligence (AI) in agriculture market are 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.
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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