Artificial Intelligence in Agriculture Market
Report ID: SQMIG15C2135
Report ID: SQMIG15C2135
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Report ID:
SQMIG15C2135 |
Region:
Global |
Published Date: August, 2025
Pages:
187
|Tables:
146
|Figures:
70
Global Artificial Intelligence in Agriculture Market size was valued at USD 2.54 Billion in 2024 and is poised to grow from USD 2.9 Billion in 2025 to USD 8.24 Billion by 2033, growing at a CAGR of 13.96% in the forecast period (2026–2033).
The artificial intelligence in agriculture market growth, driven by the increasing need for efficient farming practices, enhanced productivity, and the rising global demand for food. AI technologies such as machine learning, computer vision, and robotics are transforming agricultural operations by improving crop management, precision farming, and yield prediction. AI is being used to analyze large volumes of data gathered from satellites, drones, and IoT devices to optimize planting, watering, and harvesting schedules, as well as to monitor plant health and soil conditions in real-time.
Furthermore, AI-powered solutions are enhancing the sustainability of farming by enabling the precise use of water, fertilizers, and pesticides, which reduces waste and environmental impact. Automated systems such as AI-driven tractors and robots are being increasingly adopted to perform tasks like planting, harvesting, and weeding, improving labor efficiency and reducing operational costs.
Additionally, AI in agriculture helps farmers make data-driven decisions that can increase profitability while minimizing risks. The market is witnessing the entry of startups focused on providing AI-driven platforms, agriculture robots, and analytics tools, which are helping to drive innovation. As the world continues to face challenges such as climate change and a growing global population, AI’s role in ensuring food security, enhancing crop resilience, and improving resource efficiency will become even more crucial.
What are the Key AI Technologies Used in Agriculture for Precision Farming?
AI technologies are having a significant impact on the market, enhancing farming practices, improving productivity, and promoting sustainability. Recent developments in AI are enabling smarter decision-making and more efficient use of resources, helping farmers tackle global challenges like food security, climate change, and labor shortages.
Market snapshot - 2026-2033
Global Market Size
USD 2.23 Billion
Largest Segment
Software
Fastest Growth
Services
Growth Rate
13.96% CAGR
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Global artificial intelligence in agriculture market is segmented into technology, offering, application, deployment mode, end user and region. Based on technology, the market is segmented into machine learning, computer vision and predictive analytics. Based on offering, the market is segmented into hardware, software and services. Based on application, the market is segmented into precision farming, livestock monitoring, drone analytics, agricultural robots and others. Based on deployment mode, the market is segmented into cloud, on-premises and hybrid. Based on end user, the market is segmented into farmers, agricultural corporations, research institutions and government agencies. Based on region, the market is segmented into North America, Asia Pacific, Europe, Latin America, Middle East and Africa.
How are AI-powered Applications and Platforms Driving the Market?
As per artificial intelligence in agriculture market analysis, software is the dominant segment in the market. The primary reason for this is the increasing demand for AI-powered applications and platforms that provide real-time data analytics, precision farming, crop management, and predictive insights. The rise of cloud-based solutions, coupled with the widespread use of machine learning and computer vision, is driving the software market. These platforms enable farmers to monitor and manage crops more effectively, offering tailored recommendations for irrigation, fertilization, pest control, and disease management.
As per global artificial intelligence in agriculture market outlook, the services segment is experiencing the fastest growth in the market. This growth is driven by the increasing adoption of AI technologies and the need for consulting, system integration, and customized solutions. As AI in agriculture becomes more sophisticated, there is a growing demand for AI-related services that help farmers integrate AI technologies into their operations effectively. The services include training, support, cloud management, and AI system integration, which enable farmers to make the most of their AI solutions.
How Do Cloud-based Solutions Enable Farmers to Access AI Tools and Analytics?
The cloud segment is the dominant segment in the market. This is primarily due to the increasing demand for scalability, flexibility, and cost-efficiency in agricultural operations. Cloud-based solutions enable farmers to access powerful AI tools and analytics without needing heavy upfront investments in infrastructure. Cloud platforms allow for real-time data processing, remote access, and collaboration, which are essential for applications like precision farming, crop management, and predictive analytics. Moreover, cloud computing offers unlimited storage, making it ideal for managing vast amounts of data generated by IoT sensors, satellites, and drones.
As per global artificial intelligence in agriculture market forecast, the hybrid segment is the fastest-growing segment in the market. This growth is driven by the increasing need to combine the flexibility of cloud solutions with the control and security offered by on-premises infrastructure. Hybrid solutions enable agricultural businesses to process sensitive data locally on-premises while taking advantage of the cloud for scalability and big data analytics. Farmers and agriculture companies are adopting hybrid models to balance the benefits of cloud computing such as easy scalability and cost-effectiveness with the need for data privacy and regulatory compliance that on-premises solutions provide.
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How is North America Leading the Adoption of AI in Agriculture?
As per industry analysis, the North America region is one of the leaders in adopting AI technologies in agriculture. The region benefits from advanced agricultural infrastructure, robust technological advancements, and strong government support for smart farming solutions. North American countries are utilizing AI-based systems to improve crop management, precision farming, and sustainability practices. The integration of AI-powered drones, robots, and IoT sensors has helped increase farm productivity and optimize resource use, particularly in countries like the United States and Canada.
Artificial Intelligence in Agriculture Market in the United States
As per regional forecast, the United States is a pioneer in the market, with significant advancements in precision farming, AI-powered crop monitoring, and automated machinery. The country is home to many AI-driven platforms that provide real-time analytics for farming, such as predictive models for crop yield forecasting and soil health monitoring. Major players like John Deere, Monsanto, and Trimble have led the charge in deploying AI technologies to improve farming efficiency.
Artificial Intelligence in Agriculture Market in Canada
Canada is also seeing a rise in AI-driven agricultural practices, particularly in precision agriculture and crop health monitoring. The country’s large-scale farming operations and cold climate agriculture create a unique demand for AI solutions tailored to optimize yield predictions and resource management. AI is being used to monitor weather patterns, irrigation schedules, and soil conditions in real-time, enabling farmers to reduce operational costs and improve productivity. Canadian firms are increasingly partnering with global tech companies to advance AI solutions in agriculture, making the country a key player in the sector.
What Factors are Driving the Growth of AI in Agriculture in Asia-Pacific?
The Asia-Pacific (APAC) region is rapidly growing in the market, with countries like Japan, South Korea, and China leading the way in technological advancements. APAC countries are increasingly adopting AI technologies for precision farming, disease prediction, and automated irrigation systems. The region’s diverse agricultural practices and large-scale farming operations make AI adoption crucial for improving efficiency, sustainability, and food security. The growing focus on smart farming in this region is driving the demand for AI-powered solutions that optimize crop management and resource use.
Artificial Intelligence in Agriculture Market in Japan
Japan is a major adopter of AI in agriculture, particularly due to its push for smart farming and automation. The country has implemented AI-driven robots for planting, harvesting, and monitoring crops in an effort to counter labor shortages in the agricultural sector. Japan is also integrating AI technologies to monitor crop health, optimize irrigation, and enhance sustainability. With a focus on robotics, machine learning, and IoT, Japan’s agricultural market is poised for continued growth as AI technologies drive efficiencies in food production.
Artificial Intelligence in Agriculture Market in South Korea
South Korea is emerging as a leader in AI adoption for agriculture, with a strong focus on precision farming, data analytics, and AI-powered agricultural robots. The government and private sector are heavily investing in AI research and agriculture technology to improve efficiency and yield prediction. AI solutions such as drones and robots are being used to monitor crop health, soil conditions, and weather patterns to provide data-driven solutions. South Korea's push for smart agriculture is setting the stage for continued AI-driven innovation in the country.
How is Europe Utilizing AI to Enhance Sustainability and Precision Farming in Agriculture?
As per regional outlook, Europe is seeing significant adoption of AI technologies in agriculture, driven by the need for sustainability, precision farming, and resource management. Germany, United Kingdom, and Italy are leading the charge in integrating AI-driven solutions to improve crop yields, reduce resource consumption, and enhance data analysis for smarter farming decisions. Europe’s agricultural sector is heavily influenced by EU regulations around sustainability and environmental impact, which has led to an increased focus on AI solutions that promote efficient and eco-friendly farming.
Artificial Intelligence in Agriculture Market in Germany
Germany is one of the key players in the market in Europe. The country’s agricultural industry is integrating AI-driven solutions for precision farming, automated machinery, and crop management. Germany's focus on technology and innovation has led to the adoption of AI in several farming processes, such as automated tractors, crop monitoring systems, and data-driven decision-making platforms. German farmers are increasingly relying on AI tools to optimize resource use, reduce environmental impact, and improve farm productivity.
Artificial Intelligence in Agriculture Market in the United Kingdom
The United Kingdom is also embracing AI-driven solutions to enhance agricultural efficiency. The UK is focusing on AI-powered systems for crop health monitoring, automated harvesting, and data analytics. As part of the broader trend towards smart farming, UK farmers are adopting AI tools to boost productivity, minimize resource waste, and optimize crop management. The UK's strong agricultural technology ecosystem is contributing to the market's growth, with increasing collaborations between tech firms and agriculture companies.
Artificial Intelligence in Agriculture Market in Italy
Italy is witnessing the rise of AI technologies in its agricultural sector, particularly for precision farming and sustainability efforts. AI-powered systems in Italy are used for crop management, soil health monitoring, and irrigation control. The country's agricultural focus on sustainability and resource efficiency has spurred demand for AI-driven solutions that optimize water use, minimize waste, and improve crop yields. With a strong emphasis on eco-friendly farming, Italy is positioned as an important market for AI in agriculture.
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Artificial Intelligence in Agriculture Market Drivers
Increasing Demand for Sustainable Farming
Rise in Data Generation from IoT and Sensors
Artificial Intelligence in Agriculture Market Restraints
High Initial Costs of AI Technologies
Data Privacy and Security Concerns
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The artificial intelligence in agriculture industry is rapidly evolving, driven by advancements in precision farming, data analytics, and automation. In 2024, the competitive landscape is increasingly characterized by strategic partnerships, mergers, and investments aimed at enhancing operational efficiency, sustainability, and scalability in farming practices.
As per market strategies, John Deere has been focusing on enhancing its autonomous machinery through AI technologies, while Bayer is leveraging AI for crop protection and yield optimization.
In recent years, several startups have emerged as key players in the market, offering innovative solutions that leverage artificial intelligence to optimize farming practices. These startups focus on precision agriculture, data analytics, and automation to improve crop management, reduce resource waste, and enhance sustainability.
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
According to SkyQuest analysis, the market sees significant growth driven by durable agriculture, data-driven, decision-making and increasing demand for operational efficiency. AI technologies including machine learning, computer vision and robotics change agricultural practices by increasing accurate agriculture, adaptation of resource use and improving crop management. The integration of AI with IoT units, drones and sensors allows you to monitor the time and analysis of soil, crops and weather conditions, so that farmers can make more informed decisions. Despite the challenges such as high initial costs and privacy problems, the market is expanded, increasing the speed of trends such as AI-operated automation and A-IoT integration. This progress is expected to improve productivity, stability and cost defenses in the agricultural sector, making AI an important tool for the future of agriculture. With a mix of established players in the market and new startups, through innovations in precision farming, AI-operated analysis and automatic systems competing for artificial intelligence in the agricultural market share.
| Report Metric | Details |
|---|---|
| Market size value in Agriculture | USD 2.54 Billion |
| Market size value in 2033 | USD 8.24 Billion |
| Growth Rate | 13.96% |
| Base year | 2024 |
| Forecast period | 2026-2033 |
| Forecast Unit (Value) | USD Billion |
| Segments covered |
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| 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 |
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| Customization scope | Free report customization with purchase. Customization includes:-
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Table Of Content
Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
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.
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Global Artificial Intelligence in Agriculture Market size was valued at USD 2.54 Billion in 2024 and is poised to grow from USD 2.9 Billion in 2025 to USD 8.24 Billion by 2033, growing at a CAGR of 13.96% in the forecast period (2026–2033).
The artificial intelligence in agriculture industry is rapidly evolving, driven by advancements in precision farming, data analytics, and automation. In 2024, the competitive landscape is increasingly characterized by strategic partnerships, mergers, and investments aimed at enhancing operational efficiency, sustainability, and scalability in farming practices. 'John Deere', 'Monsanto (Bayer)', 'Trimble Inc.', 'AG Leader Technology', 'Corteva Agriscience', 'The Climate Corporation', 'DJI Innovations', 'Raven Industries', 'CNH Industrial', 'Kubota Corporation', 'NVIDIA Corporation', 'IBM Corporation'
The growing global focus on sustainability is a significant driver of the market. With concerns over environmental degradation, climate change, and resource scarcity, farmers are seeking ways to increase productivity while minimizing their environmental footprint. AI technologies enable precision farming by providing data-driven insights into resource optimization such as water, fertilizers, and pesticides. By optimizing the use of these resources, farmers can reduce waste, lower costs, and ensure that farming practices are environmentally friendly.
AI-Driven Automation in Farming Operations: AI-driven automation is a major artificial intelligence in agriculture market trend in the agriculture sector, with the rise of autonomous vehicles, drones, and robots revolutionizing traditional farming practices. Technologies like robotic harvesters, AI-powered tractors, and automated irrigation systems are transforming the industry by reducing labor costs, improving the accuracy of tasks, and increasing operational efficiency. For instance, AI-driven robots can automate tasks such as weeding, planting, and harvesting, which are traditionally labor-intensive and time-consuming.
How is North America Leading the Adoption of AI in Agriculture?
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