Shipping Companies Face Data and Governance Gaps as AI Adoption Accelerates
Shipping executives racing to deploy artificial intelligence are discovering that technical capability matters far less than foundational infrastructure. A report from Veson Nautical identifies five critical gaps that separate companies ready to use AI from those merely experimenting with it.
The gaps center on data quality, system integration, and organizational readiness-not the AI tools themselves. Without addressing them, companies risk building intelligence systems on unstable ground.
The Five Foundational Questions
First: Are AI tools built for shipping? Generic AI systems identify patterns and generate text, but maritime operations demand understanding of voyage economics, laytime clauses, demurrage liabilities, and port interdependencies. Systems designed for shipping workflows will eventually outperform general-purpose AI applied to maritime tasks.
Second: Do you own quality operational data? Competitive advantage in shipping AI will come from proprietary operational data, not from public large language models. If voyage records, port call data, and commercial information sit scattered across systems or in spreadsheets, AI outputs become unreliable.
Third: Is AI woven into actual workflows? AI tools sitting apart from day-to-day operations stay in pilot mode indefinitely. Contract terms, cost projections, and voyage logic must flow automatically through systems in real time for AI to move from testing to routine use.
Fourth: Do you have a single system of record? Many shipping firms still operate multiple disconnected platforms and spreadsheets, creating conflicting versions of reality for voyages, contracts, and market positions. AI built on inconsistent data foundations amplifies confusion rather than reducing it.
Fifth: Can you scale beyond your own systems? AI systems improve with exposure to larger operational datasets. Platforms with bigger user bases and more extensive shipping data gain structural advantages over isolated internal deployments.
Governance and Regulation Are Catching Up
At last month's AI and Digitalisation session at Geneva Dry, industry leaders acknowledged a widening gap between technological readiness and organizational preparedness. Scott Bergeron of Oldendorff Carriers said most attendees are still figuring out how to deploy AI, with few thinking about governance.
The EU AI Act will be fully enforced later this year, imposing fines up to EUR 35 million or 7% of global annual turnover for firms unable to demonstrate AI governance. A hand count at the conference revealed nearly no one in the audience had heard of the regulation before that week.
Bergeron drew a parallel to radar adoption, noting that radar-assisted collisions still occur-so new technology alone doesn't eliminate risk. He raised a deeper concern: as subject matter experts retire, who will be available in a decade to challenge AI outputs when the technology itself remains opaque even to its creators?
Ingrid Kylstad of Klaveness Digital disagreed with the radar comparison, arguing that AI is more transformative because even its creators don't fully understand how it reasons or reaches conclusions. She cited her company's decision to forgo hiring a business analyst, relying instead on AI tools combined with skilled staff to handle the work.
Change Management Is Now as Critical as Technology
Alex Albertini, CEO of Marfin Management, cautioned against viewing AI as a headcount reduction tool. AI offers the chance to expand operations with existing workforce capacity.
He introduced the concept of saboteur syndrome: employees fearing job loss become primary internal barriers to AI adoption, actively sabotaging implementation. Change management, he said, is now as vital as the technology itself.
Alberto Perez of Lloyds Register offered a practical measure: possessing a tool differs from deriving value from it. His organization's Digital Maturity Index consistently shows that companies underestimate their AI maturity compared to peers-a gap between self-assessment and reality that operations teams need to close.
For operations professionals looking to understand AI implementation in maritime workflows, resources on AI for Operations and the AI Learning Path for Operations Managers address process optimization and workflow automation directly.
Next Steps
The SplashTech Digital Leaders Forum and AI, Digitalisation, And The Maritime Workforce panel will convene on September 24 at the inaugural Splash Singapore. The conference format-no presentations, no sales pitches, only senior figures in global shipping discussing key issues-reflects the industry's shift from technology evaluation to implementation reality.
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