AI is becoming part of everyday maritime leadership. In our Senior Maritime Executive Report,AI usage rose from 26% in 2023 to 68% in 2025. The same report shows that only 10% of executives feel very confident in their organisation’s AI strategy.
AI is already being applied in commercial analysis, fleet performance, HSSEQ reporting, crewing, and ship–to–shore communications. In 2026, AI literacy refers to the ability to use these tools confidently and responsibly, enabling them to improve decision quality and capability, while understanding and managing associated risks.
So what does “AI-literate” actually mean at the leadership level?
AI literacy as a maritime leadership capability
Leaders don’t necessarily need deep technical skills to be effective. They do need to question AI-driven recommendations, communicate AI-enabled changes clearly, and treat ethics, bias, safety and fairness as leadership responsibilities.
A practical way to define AI literacy for a maritime leader in 2026 is to frame it as three capabilities:
Judgement over outputs: Understanding what the tool has produced, spotting risks, and making accountable decisions when AI informs the work.
Translation and adoption: Setting expectations for teams, embedding AI into ways of working, and making sure people understand how to use it responsibly.
Trust and responsibility: Giving sustained attention to safety, fairness, and accountability as AI becomes more embedded across roles and functions.
Leaders are already prioritising this. 61% of senior maritime executives named knowledge of AI as their number one development priority.
From AI adoption to leadership capability
AI adoption is being driven by practical goals. Maritime executives report using AI to improve decision-making, automate repetitive tasks and improve productivity, with only a small proportion reporting that AI has replaced jobs so far.
That puts leadership attention on two things at once: the quality of decisions and the health of the workforce. Our 2026 forecast describes the move towards a human-plus workforce, where AI supports people to work more effectively, while organisations redesign work so that capability continues to build across the career pipeline.
Five behaviours of an AI-literate maritime leader in 2026
1) You ask better questions of AI
AI-literate leaders treat AI output as decision support. Useful questions include:
What data is this based on?
What assumptions is it making?
What’s missing?
Where could this be wrong?
Who is accountable for the final decision?
This reflects the emphasis on leaders being able to question AI-driven recommendations.
2) You treat AI as a work-design topic
As AI use spreads, work changes. AI-literate leaders make intentional choices about how AI fits into workflows, rather than letting each team invent its own rules. A simple approach is to agree on three boundaries:
Where automation is appropriate (for example, first-draft reporting or data collation),
Where human review is non-negotiable (for example, safety-critical or compliance outputs),
Where work remains people-led because it builds judgement (for example, incident learning reviews and operational trade-offs).
Could your teams explain, in plain language, when they should not use AI, and what “good validation” looks like in their role?
3) You protect the maritime leadership pipeline and avoid a ‘hollow middle’
The risk of a ‘hollow middle’: fewer mid-level development roles and fewer opportunities to build the experience that feeds future leaders.
AI-literate leaders take intentional action here by identifying which tasks are being absorbed by AI and ensuring roles still include learning-rich work: ownership, decision-making exposure, stakeholder management, and operational problem solving.
4) You lead tech-enabled, distributed teams with clarity
Our 2026 forecast sets expectations for leaders to manage distributed, diverse, tech-enabled teams, combining human judgement and machine insight.
AI literacy shows up in day-to-day leadership standards:
How decisions are made and documented
How outputs are checked and validated
How accountability is defined when AI contributes
How teams stay aligned across locations and functions
5) You convert efficiency into coaching time
2026 will need a leadership shift: leveraging AI-enabled efficiency to create time for coaching, feedback, and capability development.
AI-literate leaders make this visible through routines: coaching cadences, regular reviews of decision quality, structured learning, and clear expectations around responsible tool use.
A simple maritime boardroom checklist for 2026
AI literacy becomes operational when it’s reflected in talent decisions, leadership expectations and day-to-day management. Our checklist prompts a useful set of questions:
Are we assessing for learning agility, leadership potential and AI-readiness, alongside experience?
Are leaders equipped to manage distributed, diverse, tech-enabled teams effectively?
Are we redesigning work so people continue to learn with AI, supporting long-term capability and progression?
In 2026, AI literacy will be visible in leadership behaviours: how decisions are challenged and made, how teams are supported through change, and how future leaders are developed in an AI-enabled workplace.
