AI Agriculture Market: Global Size, Share, Trends, Growth and Forecast, 2022-2032
AI Agriculture Market: Overview and Definition
AI agriculture, also known as precision agriculture, is the use of advanced technologies such as artificial intelligence (AI), machine learning, and big data analytics to optimize and automate agricultural practices. These technologies can be used to collect and analyze data on a wide range of factors, including weather patterns, soil moisture levels, plant growth rates, and pest and disease outbreaks.
AI agriculture has the potential to revolutionize the agricultural industry by improving crop yields, reducing waste and environmental impact, and increasing efficiency and profitability for farmers. With the help of AI, farmers can make better decisions about planting, fertilizing, and harvesting crops, and can use data-driven insights to manage resources more effectively.
The global AI agriculture market is driven by the increasing demand for food due to population growth, urbanization, and changing dietary patterns. The use of AI in agriculture can help to address these challenges by enabling farmers to produce more food with fewer resources, such as water, fertilizer, and labor.
In addition to improving crop yields and resource management, AI agriculture can also help to reduce the environmental impact of agriculture by minimizing the use of pesticides and other harmful chemicals.
However, the high cost of AI technology and the lack of infrastructure and technical expertise in some regions may limit the adoption of these technologies in the agricultural industry. In addition, concerns about data privacy and security may also impact the growth of the market in some regions.
With the rapidly growing population worldwide, estimated to reach around a mammoth 10 Billion mark by 2050, the demand for food for sustenance has been and will continue to be on the rise. The increasing application of Artificial Intelligence in all sectors is expected to boost for the catering of the growing needs. In the Agricultural Sector, AI has been developing and already has a wide range of applications including precision farming, crop monitoring, crop analytics, and others done by robots, drones, and ground-based wireless sensors and other technological equipments. These help the stakeholders in optimum supply and fulfillment of the increasing demand. The AI in Agriculture market is expected to reach around $4 Billion by 2027 from $1 Billion in 2022 at a comprehensive CAGR of 25.5% during the period.
MARKET DRIVERS:
The growth of this market is attributed by major factors including rising demand for high crop yield, growing focus on enhanced crop management, increasing crop productivity by implementing deep learning techniques, increasing population, rising adoption of information management systems , increasing penetration of internet of things (IoT) in the agriculture industry , surging utilization of drones for pesticide spraying, etc.
Moreover, development of new products including agricultural drones with new technologies, such as weather data, advanced image recognition, and precise analysis, which have now been mainstreamed for smart farming, supporting farmers in a range of tasks from analysis and planning to the real planting of crops, and ensuing observing of fields to determine health and growth. For instance, Agrobotix LLC (now acquired by AgEagle Aerial Systems) is a drone enabled software company that provides quality imaging and data analysis for sustainable and precision agriculture, and is supporting over more than 53 crops, including corn, grape, apple, sugarcane, and so on for sustainable and precision farming across 50 countries.
Furthermore, 70-80% of the new equipment purchases have been deemed to contain some form of precision farming tools along with the demand of smart green applications. This, along with, increasing use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is anticipated to boost the growth of artificial intelligence in the agriculture market.
However, high cost of systems and services, requirement of a lot of data to train machines to make accurate predictions, lack of standards and lack of awareness about use of artificial intelligence in agriculture sector in some underdeveloped and developing countries are some factors that restrain the growth of artificial intelligence in the agriculture market.
AI AGRICULTURE MARKET SEGMENTATION:
Based on Technology:
- Machine Learning
- Computer Vision
- Predictive Analytics
Based on Offering:
- Hardware
- Software
- AI-as-a-Service
- Services
Based on Deployment:
- Cloud
- On-Premise
- Hybrid
Based on Application:
- Precision Farming
- Agriculture Robots
- Livestock Monitoring
- Drone Analytics
- Labor Management
- Others
Based on region:
- North America
- Asia Pacific
- Europe
- Latin America
- Middle East & Africa
REGIONAL INSIGHT:
North America dominated the AI in agriculture industry and also generated the highest revenue in the AI agriculture market during the period. This is majorly attributed to the early adoption of technologies such as machine learning (ML) and computer vision for agricultural applications, including precision farming, livestock management, greenhouse management, and soil management. Moreover, certain players in the region are offering services to regional consumers by engaging in partnerships with other leading players. Companies such as IBM Corporation and Raven Industries Inc. are increasingly collaborating with other players, to enhance their offerings for the agriculture industry. Hence, with the increasing use of AI in agriculture, to deliver advanced analytical insights to farmers, the market is growing in this region and is expected to lead the global market, in terms of revenue, over the forecast period too.
The APAC region is expected to be the fastest growing region in terms of AI-enabled agricultural solutions. The growth can majorly be attributed to the high adoption rate of AI in the agriculture sector in major countries, such as China, India, Japan, and Australia. With India and China witnessing huge growth in the adoption of AI solutions in agriculture, owing to the increasing efforts made by the governments, as well as various multinational companies (MNCs), for spreading awareness about farm analytics and data sciences among Indian farmers and the entry of Alibaba Group in the agricultural solution business with its AI technology, to assist small farmers in the country, this region is expected to continue to grow at a more rapid rate.
European region is estimated to account for the largest market growth. Software and hardware solutions like 'Internet of the Soil' exist in this region, which is used for observing soil conditions like humidity, temperature, electrical conductivity. Few firms have urbanized vertical indoor farming systems using IoT, Big Data, and cloud analytics, which can be employed in supermarkets, restaurants, local distribution warehouses, permitting businesses to grow their own fresh crop on site to deliver to customers.
FEW KEY PLAYERS IN AI AGRICULTURE MARKET:
- IBM Corporation
- Microsoft Corporation
- Bayer AG
- Google LLC
- Deere & Company
- A.A.A Taranis Visual Ltd.
- AgEagle Aerial Systems Ltd.
- Gamaya SA
- AGCO Corporation
- Ag Leader Technology
- Trimble Inc.
- Granular Inc.
- Raven Industries Inc.
- Other Key & Niche Players
RECENT DEVELOPMENTS:
- In March 2020, Farmers Edge and Nufarm Brasil, a leading crop protection company, announced an exclusive, three-year partnership to digitize at least three million acres of farmland in Brazil by 2023. Leveraging the strengths of both companies, Farmers Edge and Nufarm will provide improved crop protection, and the modern tools growers need for making better-informed agronomic decisions to maximize profitability.
- In January 2020, IBM and Yara International (Norway), a global leader in crop nutrition and digital farming solutions, invited farmer associations, industry players, academia, and NGOs from the food and agriculture industry to join a movement to develop an open data exchange that facilitates collaboration around farm and field data, with the aim of improving the efficiency, transparency, and sustainability of global food production.
- In January 2020, Deere & Company announced the list for its startup collaborator program. The startup companies included are DataFarm (Brazil), FaunaPhotonics (Denmark), Fieldin (Israel), and EarthSense (US).
Timeline Considered for Analysis:
- 2021: Base Year
- 2022 to 2027: Forecast Period
Research Scope and Deliverables
Overview & Executive Summary
Market Drivers, Trends, Challenges and Opportunities
Market Size and Forecast Projections
Macroeconomic Indicators of Various Countries Impacting the Growth of the Market
Extensive Coverage of Industry Players including Recent Product Launches and Market Activities
Porter’s Five Force Analysis
Market Segmentation Analysis:
Industry report analyzes the global AI agriculture market by the following segments:
- Technology
- Offering
- Deployment
- Application
Customization: We also offers customization’s in the industry report as per the company’s specific needs.
Key Questions Answered in the Global AI agriculture Industry Report
- What is the overall market size in 2021? What will be the market growth during the forecast period i.e. 2022-2027?
- Which region would have high demand for product in the upcoming years?
- What are the factors driving the growth of the market?
- Which sub-market will make the most significant contribution to the market?
- What are the market opportunities for existing and entry-level players?
- What are various long-term and short-term strategies adopted by the market players?
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- Publication date: 20th September 2023
- Base year: 2022
- Forecast year: 2023-2033
- Format: PDF, PPT,Word,Excel
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