USD 1.06 billion
Artificial Intelligence in Agriculture Market Size, Share, Growth Analysis, By Component(Hardware, software and services), By Application(Precision farming, drone analytics, agriculture robots, livestock monitoring and others), By Region - Industry Forecast 2024-2031
Report ID:
SQMIG45A2173 |
Region:
Global |
Published Date: February, 2024
Pages:
157
|Tables:
63
|Figures:
75
Artificial Intelligence in Agriculture Market Insights
Artificial Intelligence in Agriculture Market size was valued at USD 1.38 billion in 2022 and is poised to grow from USD 1.70 billion in 2023 to USD 8.96 billion by 2031, at a CAGR of 23.1% during the forecast period (2024-2031).
The Global Artificial Intelligence in Agriculture Market is currently experiencing a remarkable surge, revolutionizing the agricultural landscape with cutting-edge technologies. AI-powered solutions are reshaping traditional farming practices, optimizing efficiency, and augmenting production capabilities. Presently, farmers worldwide are embracing AI-driven tools and techniques to streamline various processes, encompassing crop monitoring, pest detection, and yield forecasting. Real-time data analytics facilitated by AI aids in making well-informed decisions, thereby reducing resource wastage and enhancing crop yields. The integration of drones and autonomous robots equipped with AI algorithms enables precise and targeted crop management, optimizing the use of fertilizers and pesticides. Additionally, AI-powered agricultural machinery further enhances productivity while reducing labor costs. The adoption of AI chatbots and virtual assistants assists farmers in obtaining valuable insights, weather forecasts, and market trends, fostering better planning and risk management. As AI in agriculture continues to evolve, its applications extend to genomics and crop breeding, leading to the development of superior, resilient plant varieties. Despite its substantial growth, challenges such as data privacy, high implementation costs, and limited access to advanced technology in certain regions remain present. Nevertheless, the future holds promising prospects for the global market as the agriculture industry increasingly embraces the transformative potential of artificial intelligence in its quest for sustainable and efficient practices.
US Artificial Intelligence in Agriculture Market is poised to grow at a sustainable CAGR for the next forecast year.
Market Snapshot - 2024-2031
Global Market Size
Largest Segment
Software
Fastest Growth
Software
Growth Rate
23% CAGR
Global Artificial Intelligence in Agriculture Market ($ Bn)
Country Share for North America Region (%)
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Artificial Intelligence in Agriculture Market Segmental Analysis
Global Artificial Intelligence in Agriculture Market is segmented on the basis of component, application, and region. Based on component, the market can be segmented 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 region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Artificial Intelligence in Agriculture Market Analysis By Component
The dominant segment in the Global Artificial Intelligence in Agriculture Market is the software segment. Software solutions play a pivotal role in leveraging AI technology to provide actionable insights, data analysis, and predictive analytics. AI-powered software platforms enable farmers to make data-driven decisions, optimize resource allocation, and implement precision agriculture practices. With the growing emphasis on data-driven farming, the demand for AI software solutions is steadily rising, making it the most influential segment in the market.
The fastest-growing segment in the Global Artificial Intelligence in Agriculture Market is the services segment. As AI adoption in agriculture gains momentum, there is a growing need for specialized services to support farmers and agricultural organizations in integrating AI technologies into their existing systems. These services encompass AI consulting, installation, customization, training, and maintenance, which are vital to ensure seamless implementation and maximize the benefits of AI in agriculture. The increasing recognition of AI's transformative potential and the complexities involved in deploying AI solutions lead to a surging demand for AI-related services, making it the fastest-growing segment in the market.
Artificial Intelligence in Agriculture Market Analysis By Application
The dominant segment in the Global Artificial Intelligence in Agriculture Market is precision farming. Precision farming, also known as precision agriculture, involves the use of AI-driven technologies to monitor and manage crop conditions with exceptional accuracy and efficiency. AI-powered precision farming solutions enable farmers to gather real-time data on soil health, weather conditions, and crop growth, facilitating targeted interventions such as precise irrigation and customized fertilization. The significant impact of precision farming on enhancing agricultural productivity and sustainability makes it the most prominent and widely adopted application of AI in agriculture.
The fastest-growing segment in the Global Artificial Intelligence in Agriculture Market is agriculture robots. AI-powered agriculture robots are witnessing rapid adoption due to their ability to automate various labor-intensive tasks such as planting, harvesting, and weeding. These robots are equipped with sophisticated AI algorithms and sensors, allowing them to navigate through fields, identify crops, and execute precise actions. The increasing demand for labor-saving solutions, coupled with the need to address labor shortages in the agriculture sector, has accelerated the adoption of agriculture robots. Moreover, the continuous advancements in robotics technology and AI integration further fuel the growth of this segment, making it the fastest-growing application in the market.
Global Artificial Intelligence in Agriculture Market By Component
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Artificial Intelligence in Agriculture Market Regional Insights
The dominant region in the Global Artificial Intelligence in Agriculture Market is North America. North America has emerged as a key player in the adoption and integration of AI technologies in agriculture. The region's dominance can be attributed to the presence of advanced farming practices, significant investments in AI research and development, and a strong focus on agricultural innovation. Moreover, the region's well-established infrastructure and extensive use of precision farming techniques contribute to the widespread adoption of AI solutions, making North America the leading market for artificial intelligence in agriculture.
The fastest-growing region in the Global Artificial Intelligence in Agriculture Market is Asia Pacific. The Asia Pacific region is witnessing a rapid surge in the adoption of AI-driven technologies in agriculture. Factors driving this growth include the region's large population, increasing demand for food security, and a shift towards sustainable agricultural practices. AI-powered solutions are helping farmers in Asia Pacific to optimize crop yields, enhance resource efficiency, and tackle challenges posed by climate change. Additionally, supportive government initiatives and rising investments in agricultural modernization are further accelerating the growth of AI in agriculture across the Asia Pacific region.
Global Artificial Intelligence in Agriculture Market By Geography
- Largest
- Fastest
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Artificial Intelligence in Agriculture Market Dynamics
Artificial Intelligence in Agriculture Market Drivers
Increasing need for sustainable and efficient agricultural practices
- One key driver of the Global Artificial Intelligence in Agriculture Market is the increasing need for sustainable and efficient agricultural practices. As the world population continues to grow, there is a rising demand for food production, putting pressure on the agriculture industry to maximize yields while minimizing resource consumption. AI-powered solutions offer the potential to optimize agricultural processes, such as precision farming and data-driven decision-making, leading to more sustainable and efficient farming practices. This driver is compelling farmers and agricultural organizations to adopt AI technologies to meet the challenges of food security and environmental sustainability.
Artificial Intelligence in Agriculture Market Restraints
High initial implementation cost
- One key restraint of the Global Artificial Intelligence in Agriculture Market is the high initial implementation cost. Integrating AI technologies into existing agricultural systems requires substantial investment in AI hardware, software, and services. Additionally, training personnel and updating infrastructure to accommodate AI-driven solutions can be financially burdensome, especially for small and resource-constrained farmers. The cost factor often acts as a deterrent for widespread AI adoption in agriculture, hindering the market's growth to some extent. Overcoming this restraint would require cost-effective AI solutions, accessible financing options, and supportive government incentives to encourage wider adoption of AI in the agriculture sector.
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Artificial Intelligence in Agriculture Market Competitive Landscape
The competitive landscape of the Global Artificial Intelligence in Agriculture Market is characterized by intense rivalry and a diverse array of players offering AI-powered solutions and services to the agriculture industry. Major participants are continuously engaged in research and development to enhance their AI algorithms, sensors, and software platforms, striving to gain a competitive edge. Additionally, partnerships, collaborations, and strategic acquisitions are prevalent as companies seek to expand their market presence and cater to evolving customer needs. The market's competitive nature is further driven by the growing focus on providing customized AI solutions for precision farming, drone analytics, agriculture robots, and other applications, ensuring a dynamic and rapidly evolving landscape.
Artificial Intelligence in Agriculture Market Top Player’s Company Profiles
- Deere & Company (US)
- AgEagle Aerial Systems Inc. (US)
- The Climate Corporation (US)
- Granular, Inc. (US)
- Descartes Labs, Inc. (US)
- Prospera Technologies (Israel)
- Taranis (Israel)
- aWhere Inc. (US)
- GAMAYA (Switzerland)
- ec2ce (Spain)
- PrecisionHawk (US)
- VineView (US)
- Tule Technologies Inc. (US)
- Farmwise (US)
- Connecterra (Netherlands)
- Ceres Imaging (US)
- Arable Labs, Inc. (US)
- FarmLogs (US)
Artificial Intelligence in Agriculture Market Recent Developments
- In May 2022, the Alliance for a Green Revolution in Africa (AGRA) and Microsoft unveiled an expanded partnership aimed at driving digital agriculture transformation in Africa to enhance food security. Through this collaboration, AGRA will leverage Microsoft's digital tools to support governments, farmers, and small and medium-sized enterprises (SMEs) in building robust food systems within the region.
- In February 2022, Farmers Edge and Deere & Company, a prominent manufacturer of agriculture machinery and heavy equipment based in the US, forged an agreement allowing FarmCommand users to seamlessly integrate their data with the John Deere Operations Center account. This integration empowers users with valuable insights to make informed decisions that lead to improved yields and profitability.
- In October 2021, IBM introduced the IBM Environment Intelligence Suite, a sophisticated AI-driven software tailored for environment intelligence. This innovative suite enables companies to proactively anticipate climate risks, including floods and wildfires, while providing essential weather data, climate risk analytics, and carbon accounting to comprehend agricultural production and market intelligence.
- In March 2021, Climate LLC, a subsidiary of Bayer Crop Science Digital, successfully launched the industry-leading digital farming platform, climate FieldView, in South Africa. This strategic launch of the product in Africa equips farmers with powerful tools to manage risks, boost productivity, and simplify their agricultural operations effectively.
Artificial Intelligence in Agriculture Key Market Trends
- Increasing adoption of digital farming platforms: One key market trend in the Global Artificial Intelligence in Agriculture Market is the increasing adoption of digital farming platforms. Agricultural organizations and farmers are embracing AI-driven digital farming platforms that offer comprehensive solutions for crop management, data analytics, and decision-making. These platforms integrate various AI technologies, such as machine learning, satellite imagery, and IoT sensors, to provide real-time insights and recommendations for optimizing agricultural practices. The trend towards digital farming platforms reflects the industry's shift towards data-driven and technology-enabled approaches to enhance productivity, sustainability, and profitability in agriculture.
Artificial Intelligence in Agriculture Market SkyQuest Analysis
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyzes the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
According to our Global Artificial Intelligence in Agriculture Market analysis, the market is experiencing significant growth, driven by the adoption of AI-powered solutions to revolutionize traditional farming practices. AI technologies are being used in precision farming, drone analytics, agriculture robots, and livestock monitoring, among other applications, to optimize crop yields, reduce resource wastage, and improve decision-making. North America stands out as the dominant region in this market, while the Asia Pacific region emerges as the fastest-growing segment due to its focus on food security and sustainable agricultural practices. Key drivers include the need for efficient and sustainable farming practices, while high initial implementation costs act as a restraint. The market is highly competitive, with various players offering AI solutions and services to cater to evolving customer needs. Additionally, the trend towards adopting digital farming platforms reflects the industry's shift towards data-driven and technology-enabled approaches in agriculture.
| Report Metric | Details |
|---|---|
| Market size value in Agriculture | USD 1.38 billion |
| Market size value in 2031 | USD 8.96 billion |
| Growth Rate | 23.1% |
| Base year | 2023 |
| Forecast period | 2024-2031 |
| Forecast Unit (Value) | USD Billion |
| Segments covered |
|
| Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
| Companies covered |
|
| Customization scope | Free report customization with purchase. Customization includes:-
|
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Table Of Content
Executive Summary
Market overview
- Exhibit: Executive Summary – Chart on Market Overview
- Exhibit: Executive Summary – Data Table on Market Overview
- Exhibit: Executive Summary – Chart on Artificial Intelligence in Agriculture Market Characteristics
- Exhibit: Executive Summary – Chart on Market by Geography
- Exhibit: Executive Summary – Chart on Market Segmentation
- Exhibit: Executive Summary – Chart on Incremental Growth
- Exhibit: Executive Summary – Data Table on Incremental Growth
- Exhibit: Executive Summary – Chart on Vendor Market Positioning
Parent Market Analysis
Market overview
Market size
- Market Dynamics
- Exhibit: Impact analysis of DROC, 2021
- Drivers
- Opportunities
- Restraints
- Challenges
- Exhibit: Impact analysis of DROC, 2021
- SWOT Analysis
KEY MARKET INSIGHTS
- Technology Analysis
- (Exhibit: Data Table: Name of technology and details)
- Pricing Analysis
- (Exhibit: Data Table: Name of technology and pricing details)
- Supply Chain Analysis
- (Exhibit: Detailed Supply Chain Presentation)
- Value Chain Analysis
- (Exhibit: Detailed Value Chain Presentation)
- Ecosystem Of the Market
- Exhibit: Parent Market Ecosystem Market Analysis
- Exhibit: Market Characteristics of Parent Market
- IP Analysis
- (Exhibit: Data Table: Name of product/technology, patents filed, inventor/company name, acquiring firm)
- Trade Analysis
- (Exhibit: Data Table: Import and Export data details)
- Startup Analysis
- (Exhibit: Data Table: Emerging startups details)
- Raw Material Analysis
- (Exhibit: Data Table: Mapping of key raw materials)
- Innovation Matrix
- (Exhibit: Positioning Matrix: Mapping of new and existing technologies)
- Pipeline product Analysis
- (Exhibit: Data Table: Name of companies and pipeline products, regional mapping)
- Macroeconomic Indicators
COVID IMPACT
- Introduction
- Impact On Economy—scenario Assessment
- Exhibit: Data on GDP - Year-over-year growth 2016-2022 (%)
- Revised Market Size
- Exhibit: Data Table on Artificial Intelligence in Agriculture Market size and forecast 2021-2027 ($ million)
- Impact Of COVID On Key Segments
- Exhibit: Data Table on Segment Market size and forecast 2021-2027 ($ million)
- COVID Strategies By Company
- Exhibit: Analysis on key strategies adopted by companies
MARKET DYNAMICS & OUTLOOK
- Market Dynamics
- Exhibit: Impact analysis of DROC, 2021
- Drivers
- Opportunities
- Restraints
- Challenges
- Exhibit: Impact analysis of DROC, 2021
- Regulatory Landscape
- Exhibit: Data Table on regulation from different region
- SWOT Analysis
- Porters Analysis
- Competitive rivalry
- Exhibit: Competitive rivalry Impact of key factors, 2021
- Threat of substitute products
- Exhibit: Threat of Substitute Products Impact of key factors, 2021
- Bargaining power of buyers
- Exhibit: buyers bargaining power Impact of key factors, 2021
- Threat of new entrants
- Exhibit: Threat of new entrants Impact of key factors, 2021
- Bargaining power of suppliers
- Exhibit: Threat of suppliers bargaining power Impact of key factors, 2021
- Competitive rivalry
- Skyquest special insights on future disruptions
- Political Impact
- Economic impact
- Social Impact
- Technical Impact
- Environmental Impact
- Legal Impact
Market Size by Region
- Chart on Market share by geography 2021-2027 (%)
- Data Table on Market share by geography 2021-2027(%)
- North America
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- USA
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Canada
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Europe
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- Germany
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Spain
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- France
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- UK
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of Europe
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Asia Pacific
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- China
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- India
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Japan
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- South Korea
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of Asia Pacific
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Latin America
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- Brazil
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of South America
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Middle East & Africa (MEA)
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- GCC Countries
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- South Africa
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of MEA
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
KEY COMPANY PROFILES
- Competitive Landscape
- Total number of companies covered
- Exhibit: companies covered in the report, 2021
- Top companies market positioning
- Exhibit: company positioning matrix, 2021
- Top companies market Share
- Exhibit: Pie chart analysis on company market share, 2021(%)
- Total number of companies covered
Methodology
For the Artificial Intelligence in Agriculture Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Artificial Intelligence in Agriculture Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Analyst Support
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Artificial Intelligence in Agriculture Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the Artificial Intelligence in Agriculture Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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