Recap: From Ship to Shore – AI’s Role in the Evolving Maritime Industry
On March 10th, the Human Capital Council and the Innovation Council hosted an engaging seminar at Buccaneer Delft, where industry professionals gathered to explore the role of Artificial Intelligence (AI) in the maritime sector. The event featured keynotes from experts, interactive discussions, and a structured brainstorming session, where participants reflected on AI’s implications for their organizations.
The day started with a thought-provoking keynote by Floris Hoogenboom (Transformersgroup), followed by a discussion on the human capital aspects of AI, led by Audrey Rost-Ernst & Jan Smallegange (STC). After a short coffee break, Tobias van Dijk presented the AI Maritime Innovation Lab (AIC4NL). The seminar then moved into a structured brainstorming session, where participants tackled key questions regarding AI.
During the brainstorming session, three key questions were discussed, revealing valuable insights into how AI is perceived, where it can be applied, and what challenges organizations face in adopting it.
1. What is the first thing that comes to mind when you think of AI for your organization?
Participants shared a range of perspectives on AI, highlighting both its potential and its challenges and use of genAI such as ChatGPT, perplexity and Deepseek. Many associated AI with automation, efficiency, and data-driven decision-making, seeing it as a tool to optimize processes and reduce human workload. Others emphasized AI’s role in predictive analytics, helping to anticipate maintenance needs and improve operational planning.
However, concerns were also raised. Some participants felt that AI remains a complex and abstract concept, making it difficult to see concrete applications in their organizations. Data security, privacy, and transparency were also key concerns, particularly in critical maritime operations where trust in AI-driven decisions is essential. Additionally, there was a recognized cultural hesitation, with some employees perceiving AI as a disruptive force rather than an enabler.
To address these concerns, participants emphasized the need to start small, focusing on pilot projects that demonstrate tangible value before scaling up. It was also suggested that organizations should celebrate small successes, using early AI implementations as a way to build trust and confidence. Education and awareness were seen as key factors in overcoming resistance, ensuring that employees understand AI’s role as a support tool rather than a replacement for human expertise.
2. Which processes in your organization are resource-intensive or iterative and could therefore be suitable for AI?
Participants identified several areas where AI could improve efficiency, reduce manual workload, and enhance decision-making. Among the most commonly mentioned were:
· Predictive maintenance, using AI to detect wear and tear on vessels and equipment before failures occur.
· Data processing and reporting, where AI can automate administrative tasks, reducing human error and saving time.
· Operational planning and logistics, optimizing cargo handling, routing, and fuel efficiency.
· Crew scheduling and resource management, ensuring efficient workforce allocation based on AI-driven predictions.
Despite these promising applications, the discussion also highlighted key challenges. One of the biggest concerns was data quality and availability, without well-structured and standardized data, AI cannot function effectively. Additionally, integrating AI into existing workflows remains a challenge, as many maritime organizations still rely on traditional systems that are not AI-ready.
To overcome these barriers, organizations were encouraged to take an incremental approach, focusing on small, manageable AI applications before attempting large-scale transformations. A key takeaway was that AI should complement existing expertise rather than replace human decision-making, ensuring that AI solutions align with operational realities.
3. What is perceived as the biggest obstacle in your organization to implementing AI operationally?
When discussing barriers to AI adoption, several key challenges emerged. Lack of knowledge and expertise was frequently mentioned, as many maritime professionals are unfamiliar with how AI works and how to integrate it effectively. Data availability, reliability, and standardization were also identified as major concerns, given that AI relies on high-quality data to deliver accurate insights.
Another challenge was cultural resistance to AI adoption. Some employees are hesitant to embrace AI, either due to fear of job displacement or uncertainty about how AI will impact daily operations. Additionally, regulatory uncertainty remains a concern, as AI-driven innovations must align with strict maritime safety and compliance requirements.
To navigate these challenges, participants emphasized the importance of education and upskilling, ensuring that employees gain a clear understanding of AI’s capabilities and limitations. Organizations should also foster a culture of experimentation, where AI projects can be tested, refined, and expanded gradually. Encouraging collaboration between industry stakeholders, regulators, and technology providers was seen as
another crucial step in overcoming regulatory challenges and ensuring a smooth transition toward AI-powered operations. Next to that, questions were raised on how AI could be ‘checked’ in order to build trust between AI-tools and humans.