The market size for global artificial intelligence in agriculture is projected to reach at USD 3 billion by 2025. The increasing demand for agricultural production due to the growing population, advanced technologies for enhancing crop productivity, and increasing adoption of data management systems, are the factors responsible for the growth of AI in agriculture market. Moreover, increasing initiatives by various governments promoting the implementation of modern agriculture methods, along with enhancing crop productivity by adopting deep learning techniques, are other predominant factors fueling the industry growth.
The incorporation of internet of things (IoT) and artificial intelligence (AI) technologies, such as predictive analytics, computer vision, and machine learning, enable farmers to analyze real-time information of temperature, plant health, weather condition, crop prices, and soil moisture in the market. However, heavy implementation costs and requirement of skilled personnel is likely to hinder the AI in agriculture market growth. The adoption of AI in agriculture is substantially higher in the developed nations such as the U.S., Canada, Germany, UK, among others, owing to the presence of key agriculture technology providers within the region.
Key Segments of the Global AI in Agriculture Market
Component Overview, 2018-2025 (USD Billion)
Technology Overview, 2018-2025 (USD Billion)
- Predictive Analytics
- Computer Vision
- Machine Learning
Application Overview, 2018-2025 (USD Billion)
- Agriculture Robots
- Drone Analytics
- Livestock Monitoring
- Precision Farming
Regional Overview, 2018-2025 (USD Billion)
- North America
- Rest of Europe
- Asia Pacific
- Rest of Asia-Pacific
- Middle East and Africa
- South Africa
- Rest of Middle East and Africa
- South America
- Rest of South America
Reasons for the study
- The purpose of the study is to give an exhaustive outlook of the global AI in agriculture solution market. Benchmark yourself against the rest of the market.
- Ensure you remain competitive as innovations by existing key players to boost the market.
What does the report include?
- The study on the global AI in agriculture solution market includes qualitative factors such as drivers, restraints, and opportunities
- The study covers the competitive landscape of existing/prospective players in the AI in agriculture solution industry and their strategic initiatives for the product development
- The study covers a qualitative and quantitative analysis of the market segmented based on component, technology, and application. Moreover, the study provides similar information for the key geographies.
- Actual market sizes and forecasts have been provided for all the above-mentioned segments.
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- This study is suitable for industry participants and stakeholders in the global AI in agriculture solution market. The report will benefit:
- Every stakeholder involved in the AI in agriculture solution market.
- Managers within the Tech companies looking to publish recent and forecasted statistics about the global AI in agriculture solution market.
- Government organizations, regulatory authorities, policymakers, and organizations looking for investments in trends of global AI in agriculture solution market.
- Analysts, researchers, educators, strategy managers, and academic institutions looking for insights into the market to determine future strategies.
Artificial Intelligence (AI) in agriculture is gaining popularity across various applications within the agriculture such as computerized water systems, drone analytics, driverless tractors, among others. Key players allocating significant resources and investment to keep up with the fierce market corporations with continuous product development. The recent development of Artificial Intelligence (AI), machine learning, and Internet of Things (IoT) and its implementation across various business segment also paved the way for greater development of AI in agriculture. Over the past years, there has been an upsurge in several agricultural technology trends, thus, helping farmers to enhance their crop yield and quality. For instance, drones equipped with multi-spectral, hyper-spectral, or thermal sensors are capable of identifying areas that need modifications in irrigation. As crops are in progress to grow, these sensors monitor their health status, and vegetation index by evaluating the crop’s thermal signature. However, the factors such as lack of standardization in data collection and data sharing is likely to restrict the growth of AI in agriculture industry. Although the artificial intelligence and machine learning technologies along with their advanced algorithm design have gained prominence in the past few years, the collection of meaningful, well-tagged agricultural data yet remains lagging and unstructured.
The global AI in agriculture solution market contains hardware, software, and service segment. In 2019, the software segment is likely to hold a significant market share due to the growing requirements of AI-based for the agricultural sector. These software facilitate farmers evaluate and monitor crop yield, appropriate time for sowing, determine suitable amount of fertilizers, water, land, and pesticides, and detect crop diseases.
Based on the technology segment, the market is bifurcated into predictive analytics, computer vision, and machine learning. Predictive analytics is anticipated to hold a considerable market share within the AI in agriculture industry. Predictive analysis enables farmers address the challenges such as weed management, pest control, weather tracking, irrigation & drainage management, among others, with the help of neural networks and image analysis. Moreover, drone-equipped agricultural solutions have been used to support predictive analytics.
Based on the application segment, the market is bifurcated into agriculture robots, drone analytics, livestock monitoring, precision farming, and others. In 2019, the precision farming segment gathered the largest market revenue and it is anticipated to dominate the market throughout the forecast period. Precision farming uses artificial intelligence for data interpretation, collection, and analysis of digital information. For example, GPS-enabled combine harvesters use AI to monitor the harvest produce for field unpredictability analysis that includes differences in soil makeup, water, or fungus, to generate georeferenced information.
The global AI in agriculture solution industry is a wide range to North America, Asia Pacific, Europe, South America, and the Middle East & Africa. The Asia Pacific region is expected to be the prominent region with the countries such as India as the highest AI in agriculture market. Countries such as Japan, China, and South Korea are anticipated to be at the forefront in the adoption of AI in agriculture owing to increased technological investment in the countries. Moreover, rising trend of cloud-based solution in medium and large industries propels the demand for AI in agriculture in the region.
The major players of the global AI in agriculture solution market are IBM, Deere & Company, AgEagle Aerial Systems, Microsoft, The Climate Corporation, Granular, Prospera Technologies, Taranis, aWhere, Descartes Labs, Tule Technologies, and more. The AI in agriculture solution market is fragmented with the existence of well-known global and domestic players across the globe.