Hull, Crew, Voyage: The Three Experience Layers of AI Adoption at Sea

Maritime AI succeeds when the hull is sound, the crew is prepared, and the voyage delivers measurable value for guests, clients and operators alike.

By Steve Hemmings │ Client CTO, Insight │ Maritime Hub, Issue 4

By mid-2026, MSC Cruises had an AI concierge live right across its fleet. More than one million guest messages handled, and a 93% satisfaction score to show for it.¹ Virgin Voyages went from 50 AI agents to over 1,500 in under four months, crediting the technology with record sales and revenue growth.² And yet, in the very same industry, research from Thetius finds that 81% of maritime organisations are still stuck in pilot mode, unable to move AI from experiment to operational reality.³

The difference isn’t the technology. It’s whether the hull is sound, the crew is prepared, and the voyage is worth making.

That gap is not a technology problem. It’s a structural one. AI adoption has to work across three connected layers at once: the hull that keeps the ship seaworthy, the crew that makes it operational, and the voyage that decides whether the journey was worthwhile. Treat AI as a procurement line item and you’ll stall in the harbour. Treat it as an organisational shift across all three layers, and you will sail.

Lloyd’s Register’s Digital Maturity Index, extended in April 2026 to include a dedicated AI maturity assessment, tells the same story. AI driven analytics scores just 1.73 out of 4 across the sector, and the real barriers aren’t technical. They’re cultural, operational and architectural.⁴ The maritime AI market is now worth $4.13 billion and growing at 23% a year, yet only around a third of organisations have moved beyond pilots into live deployment.⁴

At Insight, we frame AI adoption through three connected experience layers: Hull, Crew and Voyage. Each is essential. None are sufficient on their own. Here’s what that means in practice.

HULL: The Digital Experience That Keeps AI Seaworthy

The client problem: “We bought the model, ran the pilot, and it still doesn’t work at sea.” Nine times out of ten, the culprit isn’t the algorithm. It’s the foundation underneath it.

Ask a shipping CIO why an AI project stalled and you rarely hear “the model was wrong.” You hear that the data was siloed, the ship to shore link dropped, or nobody could prove where a decision came from. As one shipping CIO put it to Thetius researchers: “Most problems are data problems, not AI problems.”³

That’s the hull: the digital experience. It’s the infrastructure, connectivity, security and the data platforms an operator needs to run. Get it right and everything above the waterline becomes possible. Get it wrong and AI simply amplifies the mess. DNV’s Veracity data platform and Kongsberg’s Vessel Insight show what “seaworthy” looks like: cloud native data lakes on Azure, workspace isolation for compliance, role-based access, and semantic layers that make sure data means the same thing to every system that touches it.

This is where Insight’s ship to shore capability demonstrates real value. We don’t just deploy hardware. We architect the data pathways, governance frameworks and secure connectivity that let AI operate across vessel and shore without opening new gaps. It’s the outcome the client actually buys: AI they can trust, running on data they can defend.

CREW: The Human Experience That Determines Adoption

The best vessel still fails with an unprepared crew. The crew layer is the human experience, covering skills, trust, adoption and governance, and it’s where most AI initiatives quietly die. The fix isn’t more technology. It is tools designed around the people who use them, with round the clock support and design that reduces fatigue, rather than adding to it.

The clearest industry example is Odfjell’s ODI chatbot (“Odfjell Digital Intelligence”). Built to help crew and shore teams navigate hundreds of procedures and compliance documents, it now draws more than 300 users a month and over 3,000 interactions, and it’s still growing.⁵ Its success isn’t technical, it’s human. As Alena Pedersen, Odfjell’s VP of Corporate IT and Digitalisation, puts it:

“People WILL embrace the digital solution when it makes their everyday life easier, and for that to be true, you have to start with a problem, not a solution.”

Alena Pedersen, Odfjell

Orca AI’s deployment lessons from bridge officers reinforce the point: AI must be anchored in existing seamanship, the system informs but the crew decides, and overrides must be welcomed, not penalised. Trust is built through transparency. Without it, even technically sound systems get “pushed into a corner,” as Cetasol’s research on crew training notes, delivering a fraction of their value.

Columbia Group shows what structured human experience design looks like at scale. Its Head of AI, Christina Orfanidou, is unequivocal:

“AI is a tool to support our people, not replace them.”

Christina Orfanidou, Head of AI, Columbia Group

Columbia kicked off upskilling for every member of staff, technical and non-technical, and rolled out an AI Governance toolbox before deploying production systems.⁶ Start small, focus on secure low risk productivity tools, and keep expertise, judgement and accountability firmly human. That is exactly where Insight’s role as orchestrator becomes tangible. We don’t just deliver platforms; we design the adoption pathways, from training and governance to feedback loops, that make crews and shore teams really trust the tools they’re asked to use.

VOYAGE: The Customer Experience That Proves the Value

A quick definition: “Voyage” isn’t a product on our price list. It’s the third experience layer in the model, and it maps directly to Insight’s Experience Enhancing Execution proposition. It answers one question: what do guests and clients truly get out of the hull and crew work beneath the surface?

A journey only matters if it arrives somewhere worthwhile. The voyage layer is the customer experience, and the value it delivers is specific and measurable: guest satisfaction, loyalty, repeat bookings, revenue per passenger, and protected crew time.

MSC Concierge is the clearest proof. Available in more than 90 languages, around the clock, with no paid internet package required, it handles bookings, account queries and entertainment recommendations, freeing crew for the high value, human moments. The pilot engaged over 170,000 guests exchanging more than a million messages, at 93% satisfaction.¹ The technology didn’t replace hospitality, it amplified it.

Virgin Voyages proves the same principle at enterprise scale, with more than 1,500 AI agents across marketing, revenue, sales, crew training and Sailor services. CEO Nirmal Saverimuttu describes the strategy as “removing the burden of mind numbing, repetitive work” so crew can focus on “innovation and true human connection.” The result: record sales, a 60% cut in content production time, and a workforce freed to deliver the experiences guests remember.²

And Seatrade Cruise’s analysis of AIDA Cruises’ digital boarding shows the operational edge. Automated document verification, biometric security and instant boarding passes don’t just speed embarkation; they redeploy crew from manual checks to welcoming guests. The scarcest resource on any cruise, passenger time, is protected. That is the outcome Insight enables: coherent services, from end to end, that turn internal capability into superior client outcomes.

The CIO’s Roadmap: One Model, Three Moves

For a CIO planning AI adoption across a fleet, Hull, Crew, Voyage is a practical sequence, not a slogan. Work it in order:

1. Start with the Hull
Audit data quality, ship to shore connectivity and governance. If your data is siloed, inconsistent, or trapped in spreadsheets, AI will amplify the problem, not solve it.

2. Prepare the Crew
Involve crews and shore teams in system design, build clear training pathways, and create feedback loops. As Thetius notes, “process compliance” cultures struggle because outputs go unchallenged, and trust requires transparency.

3. Measure the Voyage
Define the outcomes that matter, from guest satisfaction and crew retention to operational efficiency and compliance accuracy, then track whether AI really moves them. If capability isn’t translating into client value, the orchestration has failed somewhere between hull and crew.

For procurement leads weighing OPEX against CAPEX, the model clarifies priorities too. The hull is foundational. It’s a long-term strategic investment, not a discretionary spend. Crew readiness, covering training, change management and governance, is the difference between adoption and abandonment. And voyage metrics provide the business case that justifies scaling.

The hull keeps the ship moving. The crew keeps operations running. But the voyage decides whether the investment was worth it.

The sector is past debating whether AI will transform operations. The real question is whether organisations can bring hull, crew and voyage together into one system that delivers value at scale. Those who pour their investment below deck, into technology alone, stay stuck in pilot mode. The leaders make every layer work together. Insight orchestrates these layers; strengthening the hull through ship to shore infrastructure, preparing the crew through human-centric adoption, and making sure the voyage delivers for guests, crew and clients alike.

About the author

Steve Hemmings is Client CTO at Insight, where he leads complex technology transformations for enterprise and public sector clients across the UK and EMEA. A tenured enterprise architect with deep experience spanning cybersecurity, hybrid infrastructure, cloud platforms, and operational technology, Steve works at the intersection of strategy and delivery, helping organisations move beyond compliance into scalable, governed resilience. His current focus includes maritime cyber architecture, ship-to-shore security, and the operational challenges facing digitally maturing industries.

Further Reading:  From the Insight Maritime Hub and the Industry

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