The AI-powered fish farming market size is expected to see rapid growth in the next few years. It will grow to $1 billion in 2030 at a compound annual growth rate (CAGR) of 14.7%. The growth in the forecast period can be attributed to increasing focus on sustainable aquaculture, rising investments in smart fish farms, expansion of offshore and ras systems, growing adoption of predictive analytics in aquaculture, increasing demand for yield optimization. Major trends in the forecast period include increasing adoption of real-time water quality analytics, rising deployment of automated feeding systems, growing use of AI-based disease detection, expansion of smart aquaculture platforms, enhanced focus on resource optimization.
The increasing global focus on sustainable seafood production is expected to enhance the growth of the AI-powered fish farming market in the future. Sustainable seafood production involves aquaculture and fishing practices that meet current food needs while conserving ecosystems, protecting fish stocks, and reducing environmental impact. The expansion of sustainable seafood production is driven by rising adoption of responsible fishing and aquaculture practices that limit overfishing, protect marine environments, and ensure long-term supply stability. AI-powered fish farming promotes sustainable seafood production through real-time data analytics, automation, and predictive monitoring that optimize feed use, reduce waste, improve fish health, and minimize environmental impact. For example, in March 2024, according to the Department of Agriculture, Fisheries, and Forestry, an Australia-based government agency, aquaculture’s share of seafood production value is projected to increase from 60% in 2023-24 to 64% by 2028-29, with total real value expected to reach $2.21 billion by 2028-29. Therefore, the increasing global focus on sustainable seafood production is supporting the growth of the AI-powered fish farming market.
Leading companies operating in the AI-powered fish farming market are focusing on developing advanced solutions, such as species-specific machine learning-enabled automatic feeding systems, to improve feed efficiency, reduce input costs, and enhance overall productivity amid rising feed prices and supply chain challenges. Species-specific machine learning refers to AI algorithms that analyze real-time sensor data, fish or shrimp movement patterns, and environmental conditions to determine optimal feeding volumes and timing tailored to the behavior of different aquatic species. For example, in March 2024, eFishery, an Indonesia-based aquaculture technology company, enhanced its eFeeder AI-enabled smart feeding solution, which integrates real-time sensor-driven feed optimization, IoT connectivity for remote monitoring, and adaptive learning capabilities to dynamically adjust feeding schedules based on species activity levels. Designed to support more efficient and scalable aquaculture operations, the solution demonstrates how AI-driven feeding automation improves operational efficiency and productivity in modern fish farming systems.
In August 2025, OptoScale AS, a Norway-based provider of advanced solutions for the aquaculture industry, acquired Optimeering Aqua for an undisclosed amount. This acquisition enabled OptoScale to strengthen its technological offerings by integrating AI-driven predictive modeling and production planning into its real-time monitoring platform, supporting improved forecasting, proactive decision-making, and comprehensive AI-powered insights for fish farming operations. Optimeering Aqua is a Norway-based company delivering AI-based production planning and decision-support software that forecasts fish growth, mortality, welfare, and lice development.
Major companies operating in the AI-powered fish farming market are Det Norske Veritas (DNV), Cermaq Group, Biobase Technology Co. Ltd., AKVA Group ASA, Aquabyte AS, ScaleAQ AS, InnovaSea Systems Inc., Deep Trekker Inc, IMENCO AS, Aquaconnect, Bluegrove AS, CPI Equipment Inc., ReelData AI Ltd., Eruvaka Technologies Pvt. Ltd., AquaMaof Aquaculture Technologies Ltd., CageEye AS, GoSmart Technologies Ltd., Maritech Systems Ltd., OptoScale AS, SeaSmart AI Solutions, Umitron Pte. Ltd.
Tariffs are impacting the AI-powered fish farming market by increasing costs of imported sensors, underwater cameras, automated feeding hardware, edge computing devices, and environmental monitoring equipment. Aquaculture operators in Asia-Pacific and Europe are most affected due to reliance on imported smart farming technologies, while North America faces higher system integration costs. These tariffs are raising initial deployment expenses and slowing adoption among small farms. However, they are also encouraging domestic manufacturing of aquaculture sensors, localized system integration services, and regional innovation in cost-efficient smart fish farming solutions.
The AI-powered fish farming market research report is one of a series of new reports that provides AI-powered fish farming market statistics, including AI-powered fish farming industry global market size, regional shares, competitors with a AI-powered fish farming market share, detailed AI-powered fish farming market segments, market trends and opportunities, and any further data you may need to thrive in the AI-powered fish farming industry. This AI-powered fish farming market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Artificial intelligence (AI)-powered fish farming refers to the use of AI-based algorithms, sensors, and analytical tools to supervise, control, and enhance aquaculture activities. It leverages real-time insights on water conditions, fish behavior, and environmental factors to automate feeding, identify diseases, and forecast growth trends. It contributes to higher efficiency, sustainability, and profitability in fish farming while reducing resource consumption and environmental impact.
The main components of artificial intelligence (AI)-powered fish farming include hardware, services, and software. Hardware refers to physical devices such as sensors, cameras, automated feeders, drones, and monitoring equipment used to collect real-time data and support AI-driven aquaculture operations. Solutions are deployed through on-premises and cloud-based modes depending on infrastructure availability and data management needs. AI-powered fish farming systems are used in land-based recirculating aquaculture systems (RAS), offshore cage systems, and open water fish farms. Applications include feeding management, water quality monitoring, fish health monitoring, and stock and biomass management. End users of AI-powered fish farming solutions include small and medium fish farms, large commercial fish farms, and aquaculture research institutes.
The artificial intelligence (AI)-powered fish farming market consists of revenues earned by entities by providing services such as real-time water quality monitoring and analytics, automated and precision feeding services, environmental and weather forecasting, farm performance optimization, and decision support and reporting services. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-powered fish farming market also includes sales of smart water quality sensors, automated feeding systems, underwater cameras and vision systems, artificial intelligence-enabled farm management software platforms, edge computing hardware, and integrated aquaculture control systems. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
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Table of Contents
Executive Summary
AI-Powered Fish Farming Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses AI-powered fish farming market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for AI-powered fish farming? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The AI-powered fish farming market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Report Scope
Markets Covered:
1) By Component: Hardware; Services; Software2) By Deployment Mode: On-Premises; Cloud-Based
3) By Farm Type: Land-Based Recirculating Aquaculture Systems (RAS); Offshore Cage Systems; Open Water Fish Farms
4) By Application: Feeding Management; Water Quality Monitoring; Fish Health Monitoring; Stock and Biomass Management
5) By End-User: Small and Medium Fish Farms; Large Commercial Fish Farms; Aquaculture Research Institutes
Subsegments:
1) By Hardware: Water Quality Sensors; Underwater Cameras; Automated Feeding Systems; Environmental Monitoring Devices; Aquaculture Drones2) By Services: System Integration and Deployment Services; Consulting and Farm Planning Services; Monitoring and Maintenance Services; Data Analytics and Optimization Services; Training and Technical Support Services
3) By Software: Feeding Optimization Software; Water Quality Monitoring Software; Fish Health and Disease Detection Software; Biomass and Stock Management Software; Predictive Analytics and Farm Management Software
Companies Mentioned: Det Norske Veritas (DNV ); Cermaq Group; Biobase Technology Co. Ltd.; AKVA Group ASA; Aquabyte AS; ScaleAQ AS; InnovaSea Systems Inc.; Deep Trekker Inc; IMENCO AS; Aquaconnect; Bluegrove AS; CPI Equipment Inc.; ReelData AI Ltd.; Eruvaka Technologies Pvt. Ltd.; AquaMaof Aquaculture Technologies Ltd.; CageEye AS; GoSmart Technologies Ltd.; Maritech Systems Ltd.; OptoScale AS; SeaSmart AI Solutions; Umitron Pte. Ltd.
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this AI-Powered Fish Farming market report include:- Det Norske Veritas (DNV )
- Cermaq Group
- Biobase Technology Co. Ltd.
- AKVA Group ASA
- Aquabyte AS
- ScaleAQ AS
- InnovaSea Systems Inc.
- Deep Trekker Inc
- IMENCO AS
- Aquaconnect
- Bluegrove AS
- CPI Equipment Inc.
- ReelData AI Ltd.
- Eruvaka Technologies Pvt. Ltd.
- AquaMaof Aquaculture Technologies Ltd.
- CageEye AS
- GoSmart Technologies Ltd.
- Maritech Systems Ltd.
- OptoScale AS
- SeaSmart AI Solutions
- Umitron Pte. Ltd.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | March 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 0.58 Billion |
| Forecasted Market Value ( USD | $ 1 Billion |
| Compound Annual Growth Rate | 14.7% |
| Regions Covered | Global |
| No. of Companies Mentioned | 22 |


