Photo credit: Fernando Jorge on Unsplash

By Alberto Manfredini, DNV’s Head of London Cruise Centre

Running a cruise ship means getting a lot right, every day, all at once. Vessel safety, fuel efficiency, regulatory compliance, guest experience — the list is long, and none of it can be managed in isolation. That is why AI in cruise is such an interesting opportunity right now: it promises to bring everything together, offering benefits without obvious trade-offs. In my work with cruise operators across Europe, one question keeps coming up: where can AI genuinely add value, and where do we need to be careful?

Here’s what I’m hearing — and what we’re already seeing in practice.

Energy Efficiency: Finding the Right Balance
Predictive maintenance is one of the clearest early wins. By monitoring vibration, temperature, and performance data across critical equipment, AI can flag wear long before failures occur. That means better planning, fewer unplanned stoppages, and a real impact on operations with tight turnaround schedules.

On the hotel side, AI-driven HVAC systems are already delivering efficiency gains of up to 10%. Instead of relying on fixed settings, AI adjusts cooling and ventilation automatically based on occupancy patterns and external conditions. That number comes from our own COSSMOS research — and given that hotel loads represent a significant share of total energy use, it really matters.
But efficiency cannot be the only goal. Especially for systems that directly affect guests, optimisations must be designed with comfort as a fixed constraint. AI can help fine‑tune the balance, but only when deployed with that priority clearly in mind.

Decision Support: Better Information, Better Decisions
Alarm management is a practical example of AI improving day‑to‑day operations. Rather than working through dozens of alerts, crews can focus on what truly needs attention. Combined with anomaly detection across multiple ship systems, AI sorting can bring issues to the team’s attention earlier — before they escalate.

We’re also seeing growing interest in AI‑supported collision avoidance and navigation tools. Our maritime-schema initiative (from DNV) brings together structured data and AI to enhance situational awareness on the bridge — keeping the human firmly in command, but better informed.

This is something I feel strongly about: in safety‑critical systems, AI must remain limited. AI can support decisions, but it must not make them. On a cruise ship, the crew must remain in command. That cannot change.

Safety and Reliability: From Reacting to Anticipating
Two years ago, many operators were cautious about integrating AI into their maintenance regimes. Today, they are asking how to embed it. That shift tells us something: they see the operational value of getting ahead of failures rather than responding to them — and AI is helping unlock that shift.

Real‑time hazard awareness is another emerging area. AI systems that detect patterns across multiple data streams, rather than relying on individual sensor thresholds, can surface potential safety issues earlier and with greater detail.

So the question is no longer whether AI can do this — but whether it can do it consistently.

Assurance: Building Trust in the Technology
Cruise is one of the most complex environments in shipping. High‑value assets, strict regulations, and operations that combine engineering, hospitality, logistics, and passenger services into a single system. That complexity is what makes AI so useful — and what makes governance essential.

Through our AU Assurance work, we’re helping ensure that AI systems deployed in cruise are fit for purpose, transparent in behaviour, and aligned with safety obligations.

Today, the technology itself is no longer the hardest part. It’s identifying the opportunities, acknowledging the trade-offs and no‑go zones, and navigating them well.

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