How can the maritime industry benefit from applying AI?

Artificial intelligence (AI) is having a profound impact on the maritime industry, including search and rescue (SAR), enhanced vessel tracking, fleet management, and Uncrewed Surface Vessels (USVs). I expect its utility to become even more pronounced with greater adoption of AI-supported telematics. One USV example is the Mayflower Autonomous Ship (MAS), powered by IBM’s AI engine Watson—cleverly renamed AI Captain for the MAS voyage. The Iridium Connected™ Thales VesseLINK 700 terminal enables several important capabilities, including remote monitoring of the vessel’s navigation, power, and propulsion systems, and human command and control intervention (if required). AI Captain is also crucial for vessel tracking and fleet management, as well as analysing AIS (Automatic Identification System) and satellite imagery data to monitor global ship movements in near real time. AI can also help detect potential anomalies and improve logistics and scheduling by predicting arrival times and optimising routes based on weather and port conditions. The Viettel S-Tracking Vessel Monitoring System is a hybrid GPRS/Iridium Satellite system that allows users to track and monitor the activities of vessels online. The Global Maritime Distress Safety System (GMDSS) can benefit from AI by potentially early detection of distress or urgent safety matters onboard.

At Metis, we see artificial intelligence (AI) as a transformative enabler for the sector, offering significant advancements in efficiency, sustainability, safety, and decision-making. AI-driven analytics empower ship owners and operators to optimise fuel consumption through continuous monitoring of vessel performance and advanced voyage optimisation techniques. By factoring in weather forecasts, sea conditions, and real-time engine data, AI enables more efficient routeing and speed control, directly contributing to reduced emissions and substantial cost savings. Predictive maintenance is another critical application – machine learning algorithms can analyse sensor data to detect early signs of wear or malfunction, allowing technical teams to act before failures occur, thus minimising downtime and extending equipment life. Beyond operational efficiency, AI enhances onboard safety by supporting intelligent decision support systems that assist crews in complex navigation scenarios, collision avoidance, and emergency response. It also streamlines compliance and reporting through automated data collection and analysis, reducing the administrative burden on crew and ensuring accurate, timely reporting for regulatory bodies. At Metis, we integrate these AI capabilities into our digital platform, providing a holistic, data-driven ecosystem that empowers maritime stakeholders to make smarter decisions, optimise fleet performance, and accelerate their transition to more sustainable and resilient operations.

Artificial intelligence (AI) can play a significant role in reducing fuel usage and emissions. For example, AI-driven fleet optimisation platforms, such as Wärtsilä’s Fleet Optimisation Solution (FOS), can analyse vessel data to recommend optimal routes and speeds, enabling ship owners and operators to make fast, well-informed decisions. Further coordinated traffic management tools can then facilitate just-in-time arrivals, improve situational awareness and support ship-to-shore communication. What’s more, advanced AI-enabled reporting tools, such as SmartLog, can then automate the preparation of noon reports and greenhouse-gas intensity calculations. This automation ensures compliance with regulations and frees operational teams from paperwork. In combination, predictive maintenance, powered by AI, can improve asset reliability. By continuously monitoring engine and equipment metrics, ship owners and operators can forecast component wear and schedule servicing before failures occur. Moreover, digital twin technology, which uses machine learning, can be applied to create virtual replicas of vessels to simulate scenarios such as adverse weather, different cargo loads or alternative fuel types without risking real assets. AI is set to become a cornerstone of sustainable maritime operations. By integrating fleet optimisation, predictive maintenance, digital twins and automated compliance, shipowners can unlock gains in efficiency, reduce emissions and ensure fleets remain competitive.

Not all AI is created equal. For an industry as complex as maritime, distinctions matter more than most realise. Our recent research with Thetius reveals both the promise and the challenge. In the study, we found clear consensus on where AI delivers value: 97% pointed to reducing manual workflow inefficiencies, 87% to charter party contract analysis, and 85% to identifying risky voyage decisions. However, the study also revealed concerns. While 69% believe AI can handle some maritime complexity, they feel more work is needed before they are confident it won't miss critical red flags in contracts or voyage planning. Generic, plug-and-play AI models lack the context for contracts, port protocols, and voyage economics. Marcura AI is grounded in real-world use, and trained on maritime data, not general web content. The most powerful combination is an AI model paired with a human who knows the domain. Marcura AI agents are already delivering impact, from analysing charter party agreements, to flagging contradictory or missing clauses and showing where they occur. The impact extends into daily operations. Tasks like producing voyage handovers, which typically consume months of team time annually, can now be completed in under a minute. However, our goal is not to replace human expertise, but to augment it. Our AI handles the heavy lifting, but people remain in control.