Charting New Waters: AI's Transformative Impact on the Future of the Ocean Sector

Artificial Intelligence (AI) is transforming industries by granting machines with the capability to think, learn, and process vast amounts of data, thus automating complex tasks and generating critical insights. This technology significantly enhances productivity, making it an indispensable tool for contemporary advancements. Remarkable progress has already been witnessed in sectors such as retail, healthcare, and transportation. However, the ocean sector, despite its vast potential and importance, has received less attention. It is a domain rich with opportunities that merit greater focus and exploration.

The ocean sector in Canada faces unique challenges that demand innovative solutions. AI, which, in this context, refers to Machine Learning and Generative AI (GenAI), has the potential to address these challenges effectively, often achieving significant impacts with fewer resources, showcasing its transformative power in this crucial sector. However, there still exists much room for improvement in the adoption of this critical tool.

Trampoline’s Approach

To better understand the existing gaps and opportunities within the ocean sector, Trampoline, in collaboration with a Canadian NGO, led a comprehensive research initiative focused on AI adoption, industry challenges, and emerging opportunities. This initiative was designed to provide actionable insights that could drive innovation and inform strategic decision-making within the sector.

Our research was built on a robust qualitative and quantitative approach, including in-depth interviews with 14 industry experts and an extensive industry-wide survey with 98 respondents, capturing perspectives from key stakeholders across the ecosystem. In addition to these direct insights, we conducted a comprehensive market analysis to contextualize our findings within broader industry trends.

By synthesizing these diverse data sources, Trampoline identified three core challenges impeding AI adoption in the sector, along with targeted opportunities for overcoming them. Our findings have already informed discussions with industry leaders and policymakers, reinforcing our role as a strategic advisor in navigating the complexities of digital transformation within the ocean economy. In addition, our analysis generated a set of concrete short-term and long-term recommendations aimed at accelerating AI adoption within the ocean sector, which were sent directly to the relevant stakeholders.

Current Challenges Faced in Canada’s Ocean Sector

While the adoption of AI in Canada’s ocean sector offers substantial opportunities for innovation and efficiency, it is not without challenges. Throughout this research, Trampoline has identified three major obstacles that hinder the widespread integration of AI within the Canadian ocean sector: 1) The AI Knowledge Gap, 2) Advancing Technology & Breaking Down Barriers, and 3) Financial Strain & Uncertainty. Understanding these challenges is crucial for developing effective strategies to overcome them and fully harness the potential of AI to drive growth.

Challenge #1: The AI Knowledge Gap

One of the ocean sector’s biggest obstacles in adopting AI is the knowledge gap that exists within the industry. Although both large enterprises and SMEs experience this challenge from different contexts, the core issue remains the same: attracting, training, and retaining AI talent in the ocean industry is difficult. This challenge exists due to intense competition from other sectors, such as tech and finance. This, in combination with the high costs associated with upskilling existing employees, creates a significant barrier to building expertise within the ocean sector. Ultimately, the AI knowledge gap cannot be resolved without significant budgetary expenditures, which is often prohibitive to creating meaningful initiatives to address the problem.

Additionally, a general lack of awareness regarding AI’s value hinders progress, especially if key stakeholders lack understanding of AI's capabilities and its strategic advantages in optimizing the marine sector. This knowledge deficit creates resistance to change and a reluctance to invest in AI solutions, slowing technological advancement.

Challenge #2: Advancing Technology & Breaking Down Barriers

The ocean sector faces critical challenges in achieving the digital maturity required to fully embrace AI. Both large enterprises and SMEs face the challenge of requiring an update to their legacy systems, which are not currently attuned for large-scale digital projects, let alone AI initiatives. Replacing these complex legacy systems adds another layer of difficulty, as these types of upgrades can be timely and cost-consuming. Unfortunately, this upgrading process is a necessary step to properly leverage the power of AI, as its utilization requires the ability to collect, clean, structure, and analyze massive amounts of data. Without the proper digital infrastructure, organizations will not be able to harness AI’s transformative potential.

Beyond the infrastructure issues, the ocean sector is also struggling with data collection. Collecting accurate and relevant data in this industry is difficult due to the diversity of sources and formats. Significant effort is required to clean and organize data, posing a major barrier to AI deployment. In addition, data sharing between entities is hindered by privacy concerns, competitive interests, and regulatory barriers, further complicating data availability.

Challenge #3: Financial Strain & Uncertainty

The costs associated with AI adoption, including development, implementation, talent acquisition, and infrastructure, present significant barriers, especially for SMEs. Serving and improving AI models also comes with additional costs and expertise requirements, including continuous data refreshing, specialized hardware for re-training, and secure deployment in production-ready systems. Furthermore, many SMEs are hesitant to invest heavily in AI due to uncertainty about the return on investment, making them, and their investors, more risk-averse compared to larger organizations. The long development cycles and experimental nature of AI projects make it difficult to predict financial returns accurately, especially considering that SMEs are uncertain about the return on investment of these types of tools. Without properly measuring key performance indicators such as cost savings from automation, increased efficiency in resource utilization, reduction in operational downtime, or improved accuracy in data-driven decision-making, the Canadian ocean sector will struggle to justify AI investments to risk-averse stakeholders.

Future Opportunities & How to Overcome These Barriers

By addressing the skills gap, fostering collaboration, and improving technology and investment strategies, the ocean industry can fully harness the transformative potential of AI. These strategies aim to create a more supportive environment for AI integration, ensuring the sector’s growth and sustainability.

Opportunity #1: Bridge the Skills Gap

Addressing the skills gap in the ocean sector is crucial for the successful adoption of AI technologies. A key approach to solving this issue is to develop educational programs. For example, offering workshops and webinars can provide practical, hands-on experience with AI tools and technologies. These training types and formats can effectively disseminate knowledge and skills. For instance, online education platforms offer explanatory interactive courses to test knowledge, and practical projects to apply learned skills. Moreover, incorporating mentorship programs into educational frameworks can significantly enhance these efforts. This mentorship can help bridge the gap between theoretical knowledge and practical application, ensuring that participants not only learn about AI technologies, but also understand how to implement them effectively within the ocean sector.

In addition, the ocean sector could create various awareness campaigns about the importance and potential of AI in the ocean sector, which can significantly boost business interest and economic participation. Using impactful messaging, such as National Geographic's Planet or Plastic?, can resonate deeply with audiences, making AI's importance in ocean conservation unmistakable. Influential figures in the ocean and technology sectors could also participate in these campaigns, lending their voice and credibility to amplify the message. By leveraging emotional storytelling and educational content, these campaigns can inspire urgency and responsibility, fostering innovation and driving economic growth within the ocean sector.

Opportunity #2: Foster Industry Collaboration & Standardization

Building a supportive community and cultivating collaboration networks is vital for overcoming barriers to AI adoption in the ocean sector. By connecting various stakeholders, organizations promote collaborative AI initiatives and accelerate innovation. This could involve establishing a Data Registry, for example, to facilitate secure and efficient data sharing, thereby enhancing collaboration among businesses, their clients, and other sector players. Encouraging participation in open data initiatives, such as making non-sensitive marine data available for collaborative projects, can also have a profound impact. Open Ocean Data Initiatives enable wider access to valuable information, fostering innovation and collaboration across the industry.

Additionally, establishing industry standards for data best practices is crucial. Standardizing data processes can streamline data preparation, reduce redundancy, and mitigate some of the financial challenges associated with AI development and implementation. This harmonization enables organizations, both large and small, to work together more effectively, leveraging shared resources and insights to drive innovation and progress across the industry. These standards can ensure consistency and reliability in data collection, sharing, and utilization, further enhancing the sector's ability to effectively integrate AI technologies.

Opportunity #3: Provide the Proper Type of Investment

Providing the ocean industry with the proper types of investments is key to promoting the growth of AI within the industry. Government grants, for example, can provide the necessary financial support for AI projects through various means, such as tax incentives, R&D programs, and specific initiatives for innovation, disruption, and internationalization. Another significant source of funding is leveraging the private sector, either through direct relationships, or through public-private partnerships. Leading technology companies like Google (GCP), Amazon (AWS), and Microsoft (Azure) offer credits to offset initial expenses for cloud computing and services. These companies provide up to $200,000 in cloud credits to support the costs of operationalizing infrastructure. Additionally, they offer support from premium partners during the conceptualization and implementation phases, with most fees covered by the chosen technology partner. This support brings deep expertise and speed in setting up data lakes, pipelines, models, and other related capabilities.

The Business Development Bank of Canada (BDC), on the other hand, offers diverse funds and specific financial products such as venture debt and cash flow financing. They will also lead or co-lead investments and will connect businesses with a broad network of incubators, accelerators, and venture capitalists. These partnerships can attract investors and provide the necessary capital for AI projects.

Gearing up for the Future

As we stand on the brink of a new era in the ocean sector, the transformative potential of AI cannot be overstated. To fully realize AI’s potential, addressing the AI knowledge gap through targeted educational programs and continuous professional development is crucial. By investing in skill-building initiatives, the workforce can be equipped with the expertise needed to drive AI adoption and innovation. Launching awareness campaigns and creating mentorship opportunities will further enhance understanding and engagement across the sector.

Fostering cooperation remains a cornerstone of progress. Encouraging interdisciplinary collaboration across different Canadian industries can lead to innovative solutions that extend beyond the ocean sector, benefiting retail, healthcare, transportation, and more.

Investment, both financial and strategic, is essential for sustaining momentum. Removing red tape to streamline funding applications and leveraging private investment sources can have a significant impact on the ocean sector’s ability to implement AI solutions. Specialized funding initiatives tailored to the unique needs of the ocean sector will ensure that even the most groundbreaking ideas have the resources they need to thrive.

By leveraging AI’s capabilities, the ocean sector can address critical challenges, drive economic growth, and promote sustainable practices. By embracing the opportunities outlined —bridging the skills gap, fostering collaboration, and ensuring proper investment— Canada’s ocean sector can position itself strategically, keeping pace with technological advancements, while also being a leader in setting new standards for innovation and sustainability. The journey ahead is filled with promise, and with continued dedication, the ocean sector can achieve remarkable growth and impact.

Article Summary

Trampoline conducted 14 expert interviews and surveyed 98 stakeholders to assess AI adoption, challenges, and opportunities in the ocean sector.
Through our research, Trampoline pinpointed three barriers within the Ocean Sector: the AI knowledge gap, outdated digital infrastructure, and financial constraints limiting AI investment.
To address the gaps within the ocean sector, Trampoline proposed three actionable solutions: upskilling talent, fostering industry collaboration, and unlocking investment through funding and partnerships.
In conclusion, Trampoline firmly believes that the ocean sector is rife with potential in terms of the application of AI tools within the industry.