The AI in Sustainable Fisheries and Aquaculture Market Size was valued at USD 573.3 Mn in 2023 and is predicted to reach USD 1,462.8 Mn by 2031 at a 12.7% CAGR during the forecast period for 2024-2031.
AI in sustainable fisheries and aquaculture states combining AI technologies and techniques into industrial procedures and systems to increase automation, real-time decision-making, and inclusive operational efficiency. Hence, the adoption of AI in sustainable fisheries and aquaculture is expected to increase in the near future as concerns grow over the rapid usage of deep learning, machine learning, computer vision, and natural language processing. Increasing demand for seafood owing to declining wild fish stock is expected to drive global AI's growth in the sustainable fisheries and aquaculture market. AI provides the potential to optimize resource utilization, reduce waste, and decrease the environmental impact in various industries. These are other factors expected to augment the target market growth. The increasing adoption of AI in fisheries and aquaculture industries globally is expected to boost market expansion in the coming years.
However, the reduction in physical access and environmental uncertainties of AI in sustainable fisheries and aquaculture, a temporary ban on fisheries and aquaculture, coupled with the COVID-19 outbreak, are factors that may limit the growth of the target market during the forecast period. Furthermore, increasing R&D activities, government initiatives to use sustainable components for production, and investments by prominent players are expected to create lucrative growth opportunities in revenue for players operating in the global AI in Sustainable Fisheries and Aquaculture market over the forecast period.
The AI in the sustainable fisheries and aquaculture market is segmented based on species, application, technology, and end-user. The market is segmented based on species: finfish, shellfish, and crustaceans. The market is segmented by application into aquaculture monitoring and control, fish health monitoring and disease detection, feed management and optimization, water quality monitoring, stock management and yield prediction. The technology segment includes machine learning algorithms, computer vision systems, natural language processing, robotics and automation, data analytics and predictive modelling. The end-user segment includes fish farms and hatcheries, seafood processing companies, research institutions and universities, government agencies and regulatory bodies, and technology providers and AI solution developers.
The machine learning algorithm segment is expected to hold a major share in the global AI in sustainable fisheries and aquaculture market in 2023. This is attributed to the growing usage of technology for accurate predictions, improved decision-making, and optimized processes. Thus, there is a rise in the adoption of AI technology in fisheries and aquaculture industries.
The fish farms and hatcheries segment is projected to grow at a rapid rate in the global AI in sustainable fisheries and aquaculture market owing to the need to monitor and control the aquaculture environment, observe feed management, and upgrade stock management. Hence, with the growing popularity of AI-based products, there is an increase in demand for AI in sustainable fisheries and aquaculture in the end-user sector, especially in countries such as the US, Germany, the UK, China, and India.
The North America AI in the sustainable fisheries and aquaculture market is expected to register the highest market share in terms of revenue in the near future. This can be attributed to the strong focus on the environment in the region, with the increasing adoption of AI in sustainable fisheries and aquaculture with advanced computer vision systems, machine learning algorithms, and robotics. In addition, the fisheries industry in the region is focusing on the production of AI in sustainable fisheries and aquaculture to develop sustainable and environmental-friendly solutions. Growing demand for AI technology components across industries and widespread adoption of AI in sustainable fisheries and aquaculture in the production of quality products in the region are factors increasing the growth of the target market in the region. In addition, Asia Pacific is projected to grow at a rapid rate in the global AI in sustainable fisheries and aquaculture market due to growing concerns about the environment, rapid industrialization, government initiatives, and increasing funding in various industries.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 573.3 Mn |
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Revenue Forecast In 2031 |
USD 1,462.8 Mn |
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Growth Rate CAGR |
CAGR of 12.7% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Species, By Application, By Technology, By End User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
IBM Corporation, Intel Corporation, Microsoft Corporation, XpertSea Solutions Inc., Aquabyte, Antai Technology, AquacultureTalent, ImpactVision, Aquaculture Analytics, Eruvaka Technologies, AquaByte AI, Deep Trekker Inc., OptoScale AI, VAKI Aquaculture Systems Ltd., Fishtek Marine, Scanmar AS, Bluegrove Ltd., AKVA Group, BioSort AS, Kongsberg Gruppen, InnovaSea Systems, Inc., Osmo Systems, Umitron, Manolin, and Others |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Sustainable Fisheries and Aquaculture Market Snapshot
Chapter 4. Global AI in Sustainable Fisheries and Aquaculture Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Species Estimates & Trend Analysis
5.1. by Species & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Species:
5.2.1. Finfish
5.2.2. Shellfish
5.2.3. Crustaceans
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Aquaculture Monitoring and Control
6.2.2. Fish Health Monitoring and Disease Detection
6.2.3. Feed Management and Optimization
6.2.4. Water Quality Monitoring
6.2.5. Stock Management and Yield Prediction
Chapter 7. Market Segmentation 3: By AI Technology Estimates & Trend Analysis
7.1. By AI Technology & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By AI Technology:
7.2.1. Machine Learning Algorithms
7.2.2. Computer Vision Systems
7.2.3. Natural Language Processing
7.2.4. Robotics and Automation
7.2.5. Data Analytics and Predictive Modeling
Chapter 8. Market Segmentation 4: By End-User Estimates & Trend Analysis
8.1. By End-User & Market Share, 2019 & 2031
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By End-User:
8.2.1. Fish Farms and Hatcheries
8.2.2. Seafood Processing Companies
8.2.3. Research Institutions and Universities
8.2.4. Government Agencies and Regulatory Bodies
8.2.5. Technology Providers and AI Solution Developers
Chapter 9. AI in Sustainable Fisheries and Aquaculture Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Species, 2024-2031
9.1.2. North America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.1.3. North America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by AI Technology, 2024-2031
9.1.4. North America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2024-2031
9.1.5. North America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.2. Europe
9.2.1. Europe AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Species, 2024-2031
9.2.2. Europe AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.2.3. Europe AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by AI Technology, 2024-2031
9.2.4. Europe AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2024-2031
9.2.5. Europe AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.3. Asia Pacific
9.3.1. Asia Pacific AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Species, 2024-2031
9.3.2. Asia Pacific AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.3.3. Asia-Pacific Thermal Cyclers Asia-Pacific AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by AI Technology, 2024-2031
9.3.4. Asia-Pacific AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2024-2031
9.3.5. Asia Pacific AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.4. Latin America
9.4.1. Latin America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Species, 2024-2031
9.4.2. Latin America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.4.3. Latin America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by AI Technology, 2024-2031
9.4.4. Latin America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2024-2031
9.4.5. Latin America AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Species, 2024-2031
9.5.2. Middle East & Africa AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.5.3. Middle East & Africa AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by AI Technology, 2024-2031
9.5.4. Middle East & Africa AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2024-2031
9.5.5. Middle East & Africa AI in Sustainable Fisheries and Aquaculture Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. IBM Corporation
10.2.2. Intel Corporation
10.2.3. Microsoft Corporation
10.2.4. XpertSea Solutions Inc.
10.2.5. Aquabyte
10.2.6. Antai Technology
10.2.7. AquacultureTalent
10.2.8. ImpactVision
10.2.9. Aquaculture Analytics
10.2.10. Eruvaka Technologies
10.2.11. AquaByte AI
10.2.12. Deep Trekker Inc.
10.2.13. OptoScale AI
10.2.14. VAKI Aquaculture Systems Ltd.
10.2.15. Fishtek Marine
10.2.16. Scanmar AS
10.2.17. Bluegrove Ltd.
10.2.18. AKVA Group
10.2.19. BioSort AS
10.2.20. Kongsberg Gruppen
10.2.21. InnovaSea Systems, Inc.
10.2.22. Aquabyte AI
10.2.23. Osmo Systems
10.2.24. Umitron
10.2.25. Manolin
10.2.26. Other Market Players
AI in Sustainable Fisheries and Aquaculture Market- By Species
AI in Sustainable Fisheries and Aquaculture Market- By Application
AI in Sustainable Fisheries and Aquaculture Market- By Technology
AI in Sustainable Fisheries and Aquaculture Market- By End-User
AI in Sustainable Fisheries and Aquaculture Market- By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
