AI Won't Replace Seafarers, Say Top Ship Managers-People Matter More

AI in Ship Management Isn't Coming for Your Jobs - It's Here to Support Them

AI will not replace seafarers. It will equip them. That was the clear message from senior leaders across the sector at the International Shipowning and Shipmanagement Summit in London.

"Technology will matter, but people will matter more," said Bjorn Hojgaard, CEO of Anglo-Eastern Univan Group. His team has already used technology to cut fuel consumption and emissions across its managed fleet.

Who said it - and why it matters

Executives from five major managers aligned on a crew-first view of AI: Wallem director Luis Benito, Anglo-Eastern CEO Bjorn Hojgaard, Columbia Shipmanagement CEO Mark O'Neil, Bernhard Schulte Shipmanagement CEO and Intermanager president Sebastian von Hardenberg, and V Group CEO Rene Kofod-Olsen.

Their stance is simple: AI is a decision aid, not a replacement for expertise. The value shows up in safer operations, lower fuel bills, and cleaner emissions - with masters and engineers firmly in control.

What this means for managers

• Keep humans in the loop. Define clear override policies and accountability. AI suggests; crews decide.
• Measure what matters. Track fuel per voyage, emissions intensity, off-hire, and schedule reliability. Publish results fleet-wide.
• Fix data before tools. Calibrated sensors, clean streaming data, and trusted baselines beat any new dashboard.
• Train by role. Masters, chiefs, and superintendents need different workflows and checklists, not generic seminars.
• Standardize SOPs. Update bridge and engine-room procedures so AI insights feed daily routines without friction.
• Mind compliance. Link AI projects to CII, EU ETS, and your decarbonization plan to justify budgets and timelines. See the IMO's decarbonization focus here and EU ETS maritime scope here.
• Reduce vendor risk. Prefer open data access, clear SLAs, and exit clauses. Avoid black box models that can't be audited.
• Secure the edge. Treat vessels as remote sites: patching, access control, and incident drills are non-negotiable.

Where AI is already delivering

• Voyage optimization: Weather and routing suggestions that cut fuel and steady ETAs.
• Machinery health: Early warnings from performance trends to plan maintenance around port calls.
• Emissions and reporting: Automated logs to support CII tracking and ETS submissions.
• Port call and paperwork: Document prep and checks that reduce rework and delays.
• Safety insights: Pattern spotting from incidents and near misses to improve drills and briefings.

A 90-day adoption plan

• Weeks 1-2: Pick two use cases with clear ROI (e.g., voyage optimization and main engine performance). Baseline KPIs.
• Weeks 3-6: Pilot on two to three vessels. Daily feedback from masters, chiefs, and superintendents. Keep a human override in every workflow.
• Weeks 7-10: Update SOPs, bridge/engine checklists, and reporting cadence. Validate data quality and audit trails.
• Weeks 11-12: Publish results and next steps. Scale to similar vessel classes. Negotiate pricing tied to savings.

Crew capability is the multiplier

Tools help, but crew confidence turns insights into action. Budget for training the same way you budget for fuel-saving tech. Short, role-specific sessions beat one-off lectures.

If your leaders need a fast way to get fluent in practical AI use cases, explore focused learning paths for managers here.

Bottom line

AI is a lever. People are the force. The managers on stage agree: invest in your crews, clean up your data, and let technology do what it does best - inform better decisions at sea and on shore.