Artificial Intelligence In Agriculture Market Research Report: By Technology (Machine Learning, Computer Vision, and Predictive Analytics), By Offering (Hardware, Software, AI-as-a-Service, and Service), By Application (Precision Farming, Agriculture Robots, Livestock Monitoring, Drone Analytics, Labor Management, and Others), and Region (North America, Europe, Asia-Pacific, and Rest of the World) Global Industry Analysis, Size, Share, Growth, Trends, Regional Analysis, Competitor Analysis and Forecast 2023-2031.
The global artificial intelligence in agriculture market was valued at USD 1.08 billion in 2022, and is predicted to reach approximately USD 4.58 billion by 2031, at a CAGR of 17.4% from 2023 to 2031. The agriculture industry is being transformed by Artificial Intelligence (AI), leading to enhanced efficiency, sustainability, and productivity. AI is employed in agriculture through a range of technologies, including machine learning, computer vision, and robotics. These advancements empower farmers to make informed decisions based on data and optimize their operations. By analyzing satellite imagery, weather patterns, and sensor data, AI aids in crop monitoring, disease detection, and yield prediction. It also facilitates precision farming by providing targeted interventions like optimized irrigation and pesticide usage, resulting in reduced costs and environmental impact.
ARTIFICIAL INTELLIGENCE IN AGRICULTURE MARKET: REPORT SCOPE & SEGMENTATION
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Report Attribute |
Details |
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Estimated Market Value (2022) |
1.08 Bn |
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Projected Market Value (2031) |
4.58 Bn |
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Base Year |
2022 |
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Forecast Years |
2023 - 2031 |
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Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment- By Technology, By Offering, By Application, & Region |
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Segments Covered |
By Technology, By Offering, By Application, & Region |
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Forecast Units |
Value (USD Billion or Million), and Volume (Units) |
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Quantitative Units |
Revenue in USD million/billion and CAGR from 2023 to 2031 |
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Regions Covered |
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, and Rest of World |
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Countries Covered |
U.S., Canada, Mexico, U.K., Germany, France, Italy, Spain, China, India, Japan, South Korea, Brazil, Argentina, GCC Countries, and South Africa, among others |
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Report Coverage |
Market growth drivers, restraints, opportunities, Porter’s five forces analysis, PEST analysis, value chain analysis, regulatory landscape, market attractiveness analysis by segments and region, company market share analysis, and COVID-19 impact analysis. |
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Delivery Format |
Delivered as an attached PDF and Excel through email, according to the purchase option. |
Global Artificial Intelligence In Agriculture Market Dynamics
The agriculture industry faces significant challenges due to the increasing global population and the subsequent need to meet rising food demand. This has created immense pressure to enhance productivity and efficiency. The availability of vast amounts of agricultural data, including information on weather patterns, soil conditions, and plant health, has paved the way for AI-driven insights and decision-making in the industry. Additionally, advancements in technologies such as machine learning, computer vision, and robotics have made AI solutions more accessible and cost-effective for farmers. Moreover, government initiatives and support, combined with the growing awareness of sustainable farming practices, are encouraging the widespread adoption of AI in agriculture.
Global Artificial Intelligence In Agriculture Market Drivers
The agriculture industry faces the challenge of producing more food with limited resources. AI provides advanced analytics and predictive modeling capabilities that enable farmers to optimize crop yields, reduce losses, and make informed decisions to enhance productivity and efficiency.
Restraints:
One of the main restraints in the adoption of AI in agriculture is the lack of awareness and technical skills among farmers. Many farmers may not be familiar with AI technologies or lack the necessary training to implement and utilize them effectively.
Opportunities:
The growing awareness and emphasis on sustainable farming practices present an opportunity for AI in agriculture. AI can assist in optimizing resource utilization, reducing waste, and minimizing environmental impact by enabling precision farming techniques such as targeted irrigation and optimized pesticide usage.
Segment Overview
By Technology
Based on the technology, the global artificial intelligence in agriculture market is segmented into machine learning, computer vision, and predictive analytics. The machine learning segment is dominating the market with the largest revenue share of around 35.7% in 2022. The reasons behind this can be ascribed to multiple factors. With the help of machine learning algorithms, farmers can analyze vast amounts of agricultural data and extract valuable insights, enabling them to make informed decisions. These algorithms are capable of processing intricate patterns and trends, resulting in enhanced crop monitoring, disease detection, and yield prediction.
By Offering
Based on the type of offering, the global artificial intelligence in agriculture market is segmented into hardware, software, AI-as-a-service, and service. The software segment is dominating the market with the largest revenue share of around 32.4% in 2022. The reasons behind this can be attributed to various factors. In agriculture, the role of AI software is pivotal as it enables the processing of data, analytics, and decision-making. It serves as the fundamental infrastructure for implementing AI algorithms and models, granting farmers the ability to harness the potential of AI in their operations.
By Application
Based on application, the global artificial intelligence in agriculture market is segmented into precision farming, agriculture robots, livestock monitoring, drone analytics, labor management, and others. The precision farming segment is anticipated to grow at a higher CAGR of 18.6% during the forecast period, The expansion of this field can be credited to multiple factors. AI-driven precision farming techniques empower farmers to optimize the utilization of resources such as water, fertilizers, and pesticides by implementing interventions with accuracy. Leveraging AI-based technologies like machine learning and satellite imagery, farmers can monitor crop health, soil conditions, and weather patterns in real time.
Global Artificial Intelligence In Agriculture Market Overview by Region
By Region, the global artificial intelligence in agriculture market has been divided into North America, Europe, Asia-Pacific, and the Rest of the World. North America held the largest revenue share, of around 52.5% in 2022. North America harbors technologically progressive nations such as the United States and Canada, renowned for their emphasis on agricultural innovation. These countries boast well-established infrastructure, access to cutting-edge AI technologies, and a regulatory framework that promotes the integration of AI in agriculture. North America exhibits a notable concentration of influential market players and research institutions, fueling innovation and fostering collaborations within the industry. Moreover, the region features a substantial agricultural sector grappling with challenges like labor shortages and sustainability issues, making it highly receptive to AI-powered solutions.
Global Artificial Intelligence In Agriculture Market Competitive Landscape
In the global artificial intelligence in the agriculture market, a small number of prominent players hold significant market dominance and have established a strong regional presence. These key participants are committed to ongoing research and development initiatives. Additionally, they actively engage in strategic growth endeavors such as product development, product launches, joint ventures, and partnerships. By pursuing these strategies, these companies aim to strengthen their market position and expand their customer base to capture a substantial share of the market.
Some of the prominent players in the global artificial intelligence in agriculture market include Deere & Company, IBM Corporation, Microsoft Corporation, Google LLC, The Climate Corporation, Farmers Edge Inc., Granular Inc., AgEagle Aerial Systems Inc., Descartes Labs, Inc., Raven Industries Inc., AGCO Corporation, Gamaya SA, and various other key players.
Global Artificial Intelligence In Agriculture Market Recent Developments
In May 2022, AGRA and Microsoft have announced an expansion of their partnership to improve the digital transformation of agriculture in Africa, with the objective of increasing food security. This collaboration intends to help governments, farmers, and SMEs in the area establish sustainable food systems by utilizing Microsoft's digital capabilities.
Scope of the Global Artificial Intelligence In Agriculture Market Report
Artificial Intelligence In Agriculture Market Report Segmentation
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ATTRIBUTE |
DETAILS |
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By Technology |
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By Offering |
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By Application |
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By Geography |
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Customization Scope |
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Pricing |
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Objectives of the Study
The objectives of the study are summarized in 5 stages. They are as mentioned below:
To identify and estimate the market size for the global artificial intelligence in agriculture market segmented by technology, by offering, by application, region and by value (in U.S. dollars). Also, to understand the consumption/ demand created by consumers of artificial intelligence in agriculture between 2019 and 2031.
To identify and infer the drivers, restraints, opportunities, and challenges for the global artificial intelligence in agriculture market
To find out the factors which are affecting the sales of artificial intelligence in agriculture among consumers
To identify and understand the various factors involved in the global artificial intelligence in agriculture market affected by the pandemic
To provide a detailed insight into the major companies operating in the market. The profiling will include the financial health of the company's past 2-3 years with segmental and regional revenue breakup, product offering, recent developments, SWOT analysis, and key strategies.
Intended Audience
Research Methodology
Our research methodology has always been the key differentiating reason which sets us apart in comparison from the competing organizations in the industry. Our organization believes in consistency along with quality and establishing a new level with every new report we generate; our methods are acclaimed and the data/information inside the report is coveted. Our research methodology involves a combination of primary and secondary research methods. Data procurement is one of the most extensive stages in our research process. Our organization helps in assisting the clients to find the opportunities by examining the market across the globe coupled with providing economic statistics for each and every region. The reports generated and published are based on primary & secondary research. In secondary research, we gather data for global Market through white papers, case studies, blogs, reference customers, news, articles, press releases, white papers, and research studies. We also have our paid data applications which includes hoovers, Bloomberg business week, Avention, and others.
Data Collection
Data collection is the process of gathering, measuring, and analyzing accurate and relevant data from a variety of sources to analyze market and forecast trends. Raw market data is obtained on a broad front. Data is continuously extracted and filtered to ensure only validated and authenticated sources are considered. Data is mined from a varied host of sources including secondary and primary sources.
Primary Research
After the secondary research process, we initiate the primary research phase in which we interact with companies operating within the market space. We interact with related industries to understand the factors that can drive or hamper a market. Exhaustive primary interviews are conducted. Various sources from both the supply and demand sides are interviewed to obtain qualitative and quantitative information for a report which includes suppliers, product providers, domain experts, CEOs, vice presidents, marketing & sales directors, Type & innovation directors, and related key executives from various key companies to ensure a holistic and unbiased picture of the market.
Secondary Research
A secondary research process is conducted to identify and collect information useful for the extensive, technical, market-oriented, and comprehensive study of the market. Secondary sources include published market studies, competitive information, white papers, analyst reports, government agencies, industry and trade associations, media sources, chambers of commerce, newsletters, trade publications, magazines, Bloomberg BusinessWeek, Factiva, D&B, annual reports, company house documents, investor presentations, articles, journals, blogs, and SEC filings of companies, newspapers, and so on. We have assigned weights to these parameters and quantified their market impacts using the weighted average analysis to derive the expected market growth rate.
Top-Down Approach & Bottom-Up Approach
In the top – down approach, the Global Batteries for Solar Energy Storage Market was further divided into various segments on the basis of the percentage share of each segment. This approach helped in arriving at the market size of each segment globally. The segments market size was further broken down in the regional market size of each segment and sub-segments. The sub-segments were further broken down to country level market. The market size arrived using this approach was then crosschecked with the market size arrived by using bottom-up approach.
In the bottom-up approach, we arrived at the country market size by identifying the revenues and market shares of the key market players. The country market sizes then were added up to arrive at regional market size of the decorated apparel, which eventually added up to arrive at global market size.
This is one of the most reliable methods as the information is directly obtained from the key players in the market and is based on the primary interviews from the key opinion leaders associated with the firms considered in the research. Furthermore, the data obtained from the company sources and the primary respondents was validated through secondary sources including government publications and Bloomberg.
Market Analysis & size Estimation
Post the data mining stage, we gather our findings and analyze them, filtering out relevant insights. These are evaluated across research teams and industry experts. All this data is collected and evaluated by our analysts. The key players in the industry or markets are identified through extensive primary and secondary research. All percentage share splits, and breakdowns have been determined using secondary sources and verified through primary sources. The market size, in terms of value and volume, is determined through primary and secondary research processes, and forecasting models including the time series model, econometric model, judgmental forecasting model, the Delphi method, among Flywheel Energy Storage. Gathered information for market analysis, competitive landscape, growth trends, product development, and pricing trends is fed into the model and analyzed simultaneously.
Quality Checking & Final Review
The analysis done by the research team is further reviewed to check for the accuracy of the data provided to ensure the clients’ requirements. This approach provides essential checks and balances which facilitate the production of quality data. This Type of revision was done in two phases for the authenticity of the data and negligible errors in the report. After quality checking, the report is reviewed to look after the presentation, Type and to recheck if all the requirements of the clients were addressed.
