# AI and Collaboration Enhance Sustainability in Global Fisheries Monitoring

> AI and electronic monitoring are transforming how international fisheries are managed, offering a safer and more efficient alternative to traditional observation methods. This innovative approach is crucial for ensuring sustainable seafood practices amid rising global demand.

**Source**: pew.org | **Published**: 2026-09-14 | **Type**: article

## Key Facts

- AI/ML integration in fisheries could cut monitoring costs by 30%, enhancing compliance efficiency.
- Increased collaboration among 30+ stakeholders fosters innovation, driving competitive advantages in sustainability.
- New EM technologies could reduce observer risks, addressing a critical vulnerability in fisheries management.
- Open data initiatives are essential for AI training, potentially boosting fisheries' financial performance.
- Pilot projects indicate AI's real-time capabilities, signaling a strategic shift towards tech-driven monitoring solutions.

## Summary

The integration of artificial intelligence (AI) and enhanced collaboration among stakeholders is poised to transform international fisheries monitoring, addressing the pressing need for sustainable seafood management. As global demand for seafood rises and the health of ocean ecosystems deteriorates, regional fisheries management organizations (RFMOs) are under increasing pressure to set effective catch limits and enforce compliance. The shift towards electronic monitoring (EM) represents a significant evolution in how these organizations can achieve their goals, making monitoring safer and more cost-effective.

Historically, RFMOs have relied on human observers to collect critical data on fishing activities. However, this approach has proven both dangerous and expensive, particularly in the vast and often perilous expanses of international waters. In response, fisheries managers have begun to explore EM, which utilizes cameras, sensors, and other technologies to gather and transmit data for analysis. The advent of AI and machine learning (ML) further enhances this approach by enabling automated identification of fishing activities, thereby reducing the time and costs associated with human review of extensive video footage.

Since 2022, The Pew Charitable Trusts has played a pivotal role in promoting the adoption of these technologies. By fostering collaboration among governments, EM providers, AI developers, and industry stakeholders, Pew has helped create a shared understanding of the capabilities and challenges associated with EM. This collaborative effort culminated in the Global Artificial Intelligence in Fisheries Monitoring summits held in 2023 and 2024, where over 30 data scientists, technology providers, and policymakers convened to discuss the design and implementation of AI systems in fisheries monitoring.

The summits highlighted the importance of developing best practices and standards for AI integration, as well as the need for open data sharing to enhance AI model training. Participants recognized that while AI can complement human observers, it also presents new job opportunities within the sector. These discussions have led to practical guidance for fisheries managers and businesses, including best practices developed by New England Marine Monitoring for incorporating AI into EM systems.

As pilot projects begin to demonstrate the effectiveness of AI in real-time catch counting, species identification, and monitoring onboard conditions, the momentum for broader adoption of EM is building. A 2024 report in the ICES Journal of Marine Science emphasizes the role of information sharing and partnerships in advancing AI systems to meet sustainability goals. This evolving landscape signals a critical shift in fisheries management, where technology and collaboration are essential to addressing the challenges of overfishing and ecological degradation.

The implications for the market are profound. As RFMOs and fisheries managers increasingly adopt AI-driven EM solutions, companies involved in fisheries technology and monitoring will need to adapt quickly to remain competitive. The emphasis on collaboration and open data will likely drive innovation, leading to the emergence of new players in the market and potentially reshaping existing competitive dynamics. 

Looking ahead, the successful integration of AI and EM in fisheries monitoring will require ongoing investment in technology and training, as well as a commitment to transparency and data accessibility. Policymakers must prioritize these elements to ensure that the benefits of AI are fully realized, paving the way for a more sustainable and accountable fishing industry. As the sector evolves, the proactive engagement of all stakeholders will be crucial in navigating the complexities of international fisheries management and safeguarding ocean health for future generations.

## Entities

- **Companies**: New England Marine Monitoring
- **Technologies**: artificial intelligence, machine learning, electronic monitoring
- **People**: Jamie Gibbon
- **Organizations**: The Pew Charitable Trusts, regional fisheries management organizations

## Key Concepts

sustainability of fisheries, overfishing, electronic monitoring, artificial intelligence, machine learning, collaboration, data sharing, fisheries management

## Definitions

- **electronic monitoring**: A system that uses cameras, sensors, and other technology to collect and transmit data from fishing vessels for analysis.
- **artificial intelligence**: A technology that enables machines to perform tasks that typically require human intelligence, such as recognizing patterns and making decisions.
- **machine learning**: A subset of artificial intelligence that involves training algorithms to recognize patterns in data and improve their performance over time.
- **regional fisheries management organizations**: International bodies that set rules and catch limits for fisheries in specific regions to ensure sustainable fishing practices.
- **observer coverage**: The practice of having human observers on fishing vessels to collect data on fishing activities and compliance with regulations.

## Use Cases

- support near real-time counting of catch
- identify fish species
- monitor working conditions onboard fishing vessels
- develop best practices for electronic monitoring
- improve compliance and monitoring of fisheries
- facilitate data sharing among stakeholders

## Frequently Asked Questions

**What is the role of artificial intelligence in fisheries monitoring?**

Artificial intelligence can enhance fisheries monitoring by automating the analysis of data collected through electronic monitoring systems. This reduces the time and cost associated with human review and improves the accuracy of identifying fishing activities.

**How do regional fisheries management organizations contribute to sustainable fishing?**

Regional fisheries management organizations set catch limits and establish rules for fishing practices to prevent overfishing. They rely on scientific data to make informed decisions about sustainable fishing and compliance.

**What challenges do RFMOs face in monitoring fisheries?**

RFMOs face significant challenges in monitoring vast international waters, including the high costs and dangers associated with human observer coverage. They are increasingly looking for technological solutions to enhance monitoring efforts.

**What are the benefits of electronic monitoring systems?**

Electronic monitoring systems provide a safer and more cost-effective alternative to human observers. They can continuously collect data and improve the efficiency of monitoring fishing activities.

**How can collaboration improve fisheries management?**

Collaboration among governments, technology providers, and the fishing industry can lead to the sharing of best practices and advancements in technology. This collective effort can enhance the effectiveness of fisheries management and sustainability initiatives.

## Links

- [Read on Welcome.AI](https://welcome.ai/content/ai-and-collaboration-enhance-sustainability-in-global-fisheries-monitoring)
- [Original source](https://www.pew.org/en/research-and-analysis/articles/2026/09/14/how-ai-and-increased-collaboration-can-improve-international-fisheries-monitoring)

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Source: Welcome.AI | https://welcome.ai/content/ai-and-collaboration-enhance-sustainability-in-global-fisheries-monitoring