Artificial Intelligence in Agriculture - Global Market Outlook (2021 - 2028)
According to Stratistics MRC, the Global Artificial Intelligence in Agriculture Market is accounted for $1.08 billion in 2021 and is expected to reach $1.67 billion by 2028 growing at a CAGR of 6.5% during the forecast period. Agriculture involves a number of processes and stages, the lion’s share of which are manual. By complementing adopted technologies, AI can facilitate the most complex and routine tasks. It can gather and process big data on a digital platform, come up with the best course of action, and even initiate that action when combined with other technology. With the introduction of AI technologies, farmers can yield healthier crops, monitor their soil and growing conditions, and control pests. AI in agriculture helps the farmer by organizing data for farmers; it helps with the workload and enhances a wide range of the tasks which are related to agriculture and the entire food supply chain. Artificial Intelligence in agriculture is used for various applications such as driverless tractors, rural automation, computerized water system frameworks, facial acknowledgment, etc.
Market Dynamics:
Driver:
Rising need for real-time livestock monitoring
The rising need for the monitoring of livestock is another key factor driving the AI in agriculture market. With the application of advanced AI solutions, such as facial recognition for livestock and image classification incorporated with body condition score and feeding patterns, dairy farms are now able to individually monitor all behavioural aspects of a herd. In addition, for monitoring the health of the livestock, farmers are increasingly using machine vision that helps recognize hide patterns and facial features, monitor water and food intake of livestock, as well as record their body temperature and behaviour.
Restraint:
Lack of experience with emerging technologies
The agricultural sector in developing countries is different from the agricultural sector in Western Europe and the US. Some regions could benefit from artificial intelligence agriculture, but it may be hard to sell such technology in areas where agricultural technology is not common. Farmers will most likely need help adopting it. Farmers tend to perceive AI as something that applies only to the digital world. They might not see how it can help them work the physical land. This is not because they’re conservative or wary of the unknown. Their resistance is caused by a lack of understanding of the practical application of AI tools. Although AI can be useful, there’s still a lot of work to be done by technology providers to help farmers implement it the right way.
Opportunity:
Trend of decline in the agricultural workforce
A lack of skilled labor, aging farmers, and younger generations finding farming an unattractive profession contribute to the decline, thus encouraging trends for automated farming operations. The trend of decline in the agricultural workforce is encouraging governments and private organizations to focus on automating operations by adopting artificial intelligence technologies in the agricultural sector. The developed countries are not an exception in this declining trend. Asia-Pacific, where agriculture occupies a significant part of the economy, is witnessing a massive decline in the workforce. In Japan, the number of people working in farms witnessed a steep fall decline from the previous year. The European agricultural sector has also faced an enormous decline in the workforce, nearly accounting for 12.8% for the corresponding period. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.
Threat:
Privacy and security issues
Since there are no clear policies and regulations around the use of AI not just in agriculture but in general, precision agriculture and smart farming raises various legal issues that often remain unanswered. Privacy and security threats like cyberattacks and data leaks may cause farmers serious problems. Unfortunately, many farms are vulnerable to these threats.
The services segment is expected to be the largest during the forecast period
The services segment is estimated to have a lucrative growth and is expected to witness the faster growth in the AI in agriculture market during the forecast period. This can be attributed to the rising adoption of AI solutions in the agriculture industry, thereby creating a high requirement for proper installation, maintenance, and training services among farmers and other industry stakeholders. This category is further bifurcated into managed and professional. Of the two, the professional service bifurcation is expected to be the faster-growing over the forecast period. This can be attributed to the increasing demand for support, maintenance, and training services by farmers who are deploying the AI technology.
The precision farming segment is expected to have the highest CAGR during the forecast period
The precision farming segment is anticipated to witness the fastest CAGR growth during the forecast period due to the fact that the precision farming method is gaining popularity among farmers, owing to the increasing need for optimum yield production from the limited available resources, as well as for reducing the cost of crop production. It comprises a technology-driven analysis of data acquired from the fields for increasing crop productivity. Precision devices integrated with AI technologies help in collecting farm-related data, thereby helping the farmers make better decisions and increase the productivity of their lands. Moreover, farm managers and producers are leveraging the capabilities of IoT devices for field mapping and irrigation management, which is also resulting in the rapid growth.
Region with highest share:
North America is projected to hold the largest market share during the forecast period due 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, with the increasing adoption of technologies like IoT, in combination with computer vision, in the agriculture space, the market would exhibit positive growth over the forecast period. Additionally, 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.
Region with highest CAGR:
Asia Pacific is projected to have the highest CAGR over the forecast period owing to the high adoption rate of AI in the agriculture sector in major countries, such as China, India, Japan, and Australia. In the region, China is witnessing huge growth in the adoption of AI solutions in agriculture, owing to the entry of Alibaba Group in the agricultural solution business with its AI technology, to assist small farmers in the country. In addition, the Indian AI in agriculture market is witnessing significant growth, due to the increasing effort by the government, as well as various multinational companies (MNCs), for spreading awareness about farm analytics and data sciences among Indian farmers in the region.
Key players in the market
Some of the key players profiled in the Artificial Intelligence in Agriculture Market include Cainthus Corporation, Connecterra B.V, CropX Inc, Descartes Labs, Inc, Farmers Edge, Granular, Inc, IBM, John Deere, Microsoft Corporation, Precision Hawk Inc, Prospera, Trimble, The Climate Corporation, Trace Genomics, Inc, and Vision Robotics Corporation.
Key Developments:
In August 2021, Trimble introduced Trimble Ventures to set up $200 million funds and invest in early and growth-stage startups that lend a strong focus on technology-enabled innovation in industries including agriculture.
In July 2020, Prospera Technologies and Bayer partnered to help improve the output at greenhouses by using big data and machine learning. Using machine learning and big data, the company has monitored the production of $5 trillion worth of agricultural produce. Prospera uses AI and advanced data collecting methods to ensure each plant, every seed, is brought to its full potential in the field. This way, farming can be done in minute detail, ensuring that nothing is wasted and that the resources of our planet provide a bountiful harvest.
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, Deere & Company announced the list for its startup collaborator program. The startup companies included are DataFarm (Brazil), FaunaPhotonics (Denmark), Fieldin (Israel), and EarthSense (US). This program will help the company leverage technologies offered by the startups and provide value to customers.
Technologies Covered:
Computer Vision
Machine Learning
Predictive Analytics
Offerings Covered:
AI-as-a-Service
Hardware
Services
Software
Deployments Covered:
Cloud
Hybrid
On-Premise
Applications Covered:
Agriculture Robots
Drone Analytics
Fish Farming Management
Labor Management
Livestock Monitoring
Precision Farming
Smart Green House Management
Soil Management
Supply Chain Efficiency
Farm Machinery Automation
Crop Growth Assessment
Regions Covered:
North America
US
Canada
Mexico
Europe
Germany
UK
Italy
France
Spain
Rest of Europe
Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
South America
Argentina
Brazil
Chile
Rest of South America
Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
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