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Artificial Intelligence In Agriculture Market

Artificial Intelligence in Agriculture Market Forecasts to 2028 – Global Analysis By Technology (Computer Vision, Machine Learning, Predictive Analytics), Deployment (Cloud, Hybrid, On-Premise), Offering, Application, and By Geography

4.9 (23 reviews)
Published: March 2022 ID: SMRC19114
4.9 (23 reviews)
Published: March 2022 ID: SMRC19114

This report covers the impact of COVID-19 on this global market
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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, agriculture analytics market, 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
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan       
o China       
o India        
o Australia 
o New Zealand
o South Korea
o Rest of Asia Pacific   
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o 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

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

1 Executive Summary       
         
2 Preface        

 2.1 Abstract       
 2.2 Stake Holders      
 2.3 Research Scope      
 2.4 Research Methodology     
  2.4.1 Data Mining     
  2.4.2 Data Analysis     
  2.4.3 Data Validation     
  2.4.4 Research Approach     
 2.5 Research Sources      
  2.5.1 Primary Research Sources    
  2.5.2 Secondary Research Sources    
  2.5.3 Assumptions     
         
3 Market Trend Analysis      
 3.1 Introduction      
 3.2 Drivers       
 3.3 Restraints      
 3.4 Opportunities      
 3.5 Threats       
 3.6 Technology Analysis     
 3.7 Application Analysis     
 3.8 Emerging Markets      
 3.9 Impact of Covid-19      
         
4 Porters Five Force Analysis      
 4.1 Bargaining power of suppliers     
 4.2 Bargaining power of buyers     
 4.3 Threat of substitutes     
 4.4 Threat of new entrants     
 4.5 Competitive rivalry      
         
5 Global Artificial Intelligence in Agriculture Market, By Technology  
 5.1 Introduction      
 5.2 Computer Vision      
 5.3 Machine Learning      
 5.4 Predictive Analytics      
         
6 Global Artificial Intelligence in Agriculture Market, By Offering  
 6.1 Introduction      
 6.2 AI-as-a-Service      
 6.3 Hardware      
  6.3.1 Network      
  6.3.2 Processor     
  6.3.3 Storage Device     
 6.4 Services       
  6.4.1 Integration     
  6.4.2 Support & Maintenance    
 6.5 Software       
  6.5.1 AI Platform     
  6.5.2 AI Solution     
         
7 Global Artificial Intelligence in Agriculture Market, By Deployment  
 7.1 Introduction      
 7.2 Cloud       
 7.3 Hybrid       
 7.4 On-Premise      
         
8 Global Artificial Intelligence in Agriculture Market, By Application  
 8.1 Introduction      
 8.2 Agriculture Robots      
 8.3 Drone Analytics      
 8.4 Fish Farming Management     
 8.5 Labor Management      
 8.6 Livestock Monitoring     
  8.6.1 Animal Growth Monitoring    
  8.6.2 Animal Health Monitoring    
 8.7 Precision Farming      
  8.7.1 Crop Scouting     
  8.7.2 Field Mapping     
  8.7.3 Irrigation Management    
  8.7.4 Weather Tracking & Forecasting   
  8.7.5 Yield Monitoring     
  8.7.6 Indoor Farming     
 8.8 Smart Green House Management    
 8.9 Soil Management      
  8.9.1 Nutrient Monitoring    
  8.9.2 Moisture Monitoring    
 8.10 Supply Chain Efficiency      
 8.11 Farm Machinery Automation     
 8.12 Crop Growth Assessment     
         
9 Global Artificial Intelligence in Agriculture Market, By Geography  
 9.1 Introduction      
 9.2 North America      
  9.2.1 US      
  9.2.2 Canada      
  9.2.3 Mexico      
 9.3 Europe       
  9.3.1 Germany      
  9.3.2 UK      
  9.3.3 Italy      
  9.3.4 France      
  9.3.5 Spain      
  9.3.6 Rest of Europe     
 9.4 Asia Pacific      
  9.4.1 Japan      
  9.4.2 China      
  9.4.3 India       
  9.4.4 Australia      
  9.4.5 New Zealand     
  9.4.6 South Korea     
  9.4.7 Rest of Asia Pacific     
 9.5 South America      
  9.5.1 Argentina     
  9.5.2 Brazil      
  9.5.3 Chile      
  9.5.4 Rest of South America    
 9.6 Middle East & Africa     
  9.6.1 Saudi Arabia     
  9.6.2 UAE      
  9.6.3 Qatar      
  9.6.4 South Africa     
  9.6.5 Rest of Middle East & Africa    
         
10 Key Developments       
 10.1 Agreements, Partnerships, Collaborations and Joint Ventures  
 10.2 Acquisitions & Mergers     
 10.3 New Product Launch     
 10.4 Expansions      
 10.5 Other Key Strategies     
         
11 Company Profiling       

 11.1 Cainthus Corporation     
 11.2 Connecterra B.V      
 11.3 CropX Inc       
 11.4 Descartes Labs, Inc      
 11.5 Farmers Edge      
 11.6 Granular, Inc      
 11.7 IBM       
 11.8 John Deere      
 11.9 Microsoft Corporation     
 11.10 Precision Hawk Inc      
 11.11 Prospera       
 11.12 Trimble       
 11.13 The Climate Corporation     
 11.14 Trace Genomics, Inc      
 11.15 Vision Robotics Corporation     


List of Tables        
1 Global Artificial Intelligence in Agriculture Market Outlook, By Region (2020-2028) ($MN)
2 Global Artificial Intelligence in Agriculture Market Outlook, By Technology (2020-2028) ($MN)
3 Global Artificial Intelligence in Agriculture Market Outlook, By Computer Vision (2020-2028) ($MN)
4 Global Artificial Intelligence in Agriculture Market Outlook, By Machine Learning (2020-2028) ($MN)
5 Global Artificial Intelligence in Agriculture Market Outlook, By Predictive Analytics (2020-2028) ($MN)
6 Global Artificial Intelligence in Agriculture Market Outlook, By Offering (2020-2028) ($MN)
7 Global Artificial Intelligence in Agriculture Market Outlook, By AI-as-a-Service (2020-2028) ($MN)
8 Global Artificial Intelligence in Agriculture Market Outlook, By Hardware (2020-2028) ($MN)
9 Global Artificial Intelligence in Agriculture Market Outlook, By Network (2020-2028) ($MN)
10 Global Artificial Intelligence in Agriculture Market Outlook, By Processor (2020-2028) ($MN)
11 Global Artificial Intelligence in Agriculture Market Outlook, By Storage Device (2020-2028) ($MN)
12 Global Artificial Intelligence in Agriculture Market Outlook, By Services (2020-2028) ($MN)
13 Global Artificial Intelligence in Agriculture Market Outlook, By Integration (2020-2028) ($MN)
14 Global Artificial Intelligence in Agriculture Market Outlook, By Support & Maintenance (2020-2028) ($MN)
15 Global Artificial Intelligence in Agriculture Market Outlook, By Software (2020-2028) ($MN)
16 Global Artificial Intelligence in Agriculture Market Outlook, By AI Platform (2020-2028) ($MN)
17 Global Artificial Intelligence in Agriculture Market Outlook, By AI Solution (2020-2028) ($MN)
18 Global Artificial Intelligence in Agriculture Market Outlook, By Deployment (2020-2028) ($MN)
19 Global Artificial Intelligence in Agriculture Market Outlook, By Cloud (2020-2028) ($MN)
20 Global Artificial Intelligence in Agriculture Market Outlook, By Hybrid (2020-2028) ($MN)
21 Global Artificial Intelligence in Agriculture Market Outlook, By On-Premise (2020-2028) ($MN)
22 Global Artificial Intelligence in Agriculture Market Outlook, By Application (2020-2028) ($MN)
23 Global Artificial Intelligence in Agriculture Market Outlook, By Agriculture Robots (2020-2028) ($MN)
24 Global Artificial Intelligence in Agriculture Market Outlook, By Drone Analytics (2020-2028) ($MN)
25 Global Artificial Intelligence in Agriculture Market Outlook, By Fish Farming Management (2020-2028) ($MN)
26 Global Artificial Intelligence in Agriculture Market Outlook, By Labor Management (2020-2028) ($MN)
27 Global Artificial Intelligence in Agriculture Market Outlook, By Livestock Monitoring (2020-2028) ($MN)
28 Global Artificial Intelligence in Agriculture Market Outlook, By Animal Growth Monitoring (2020-2028) ($MN)
29 Global Artificial Intelligence in Agriculture Market Outlook, By Animal Health Monitoring (2020-2028) ($MN)
30 Global Artificial Intelligence in Agriculture Market Outlook, By Precision Farming (2020-2028) ($MN)
31 Global Artificial Intelligence in Agriculture Market Outlook, By Crop Scouting (2020-2028) ($MN)
32 Global Artificial Intelligence in Agriculture Market Outlook, By Field Mapping (2020-2028) ($MN)
33 Global Artificial Intelligence in Agriculture Market Outlook, By Irrigation Management (2020-2028) ($MN)
34 Global Artificial Intelligence in Agriculture Market Outlook, By Weather Tracking & Forecasting (2020-2028) ($MN)
35 Global Artificial Intelligence in Agriculture Market Outlook, By Yield Monitoring (2020-2028) ($MN)
36 Global Artificial Intelligence in Agriculture Market Outlook, By Indoor Farming (2020-2028) ($MN)
37 Global Artificial Intelligence in Agriculture Market Outlook, By Smart Green House Management (2020-2028) ($MN)
38 Global Artificial Intelligence in Agriculture Market Outlook, By Soil Management (2020-2028) ($MN)
39 Global Artificial Intelligence in Agriculture Market Outlook, By Nutrient Monitoring (2020-2028) ($MN)
40 Global Artificial Intelligence in Agriculture Market Outlook, By Moisture Monitoring (2020-2028) ($MN)
41 Global Artificial Intelligence in Agriculture Market Outlook, By Supply Chain Efficiency (2020-2028) ($MN)
42 Global Artificial Intelligence in Agriculture Market Outlook, By Farm Machinery Automation (2020-2028) ($MN)
43 Global Artificial Intelligence in Agriculture Market Outlook, By Crop Growth Assessment (2020-2028) ($MN)
         
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.

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