Artificial intelligence (AI) can expand workforce access and support training, but in a safety-critical industry, its role must be clearly defined.
AI is increasingly present in education and workforce training, often framed as a solution to instructor shortages and growing demand for skilled workers. In the maritime and ocean economy, where technical knowledge is specialized and experienced trainers are already stretched thin, it is easy to see why AI appears attractive. The more useful question, however, is not whether AI can be used in workforce training, but how it should be used to strengthen, not dilute, workforce preparation.
The ocean economy faces a unique set of pressures. Shipyards, vessel operators, ports, offshore energy companies, and marine manufacturers all depend on a steady pipeline of skilled workers, yet many of the people best suited to train that workforce are busy keeping operations running. As technology evolves — think: automation, alternative fuels, digital navigation systems — education and training demands increase, even as instructor capacity remains limited.
In this context, AI offers clear potential benefits.
Used well, AI can help handle foundational educational tasks that otherwise consume scarce human time. It can support career awareness for students and families unfamiliar with maritime careers, help explain entry points and training pathways, and provide consistent information about skills, certifications, and progression. For learners in inland or rural regions, where exposure to the ocean economy is minimal, this type of access can help close awareness gaps that have nothing to do with ability or interest.
AI can also support educators and trainers who may not have deep maritime backgrounds. Rather than expecting every instructor to be an industry expert, AI tools can assist with translating complex maritime concepts into usable educational context, linking classroom instruction to real-world applications, and helping keep content current as technology changes. This lowers barriers for schools and training programs while preserving the role of human instructors as teachers, mentors, and evaluators.
At the same time, the maritime sector highlights why AI must be applied with care.
This is a safety-critical industry. Competence is not just about knowledge, but judgment, situational awareness, and accountability. AI cannot replace hands-on training, supervision, or the professional responsibility required to operate vessels, manage port infrastructure, or work in high-risk environments. Any use of AI in workforce training must be clearly bounded, supporting preparation and learning, not substituting for experience or certifying readiness.
There is also a cultural dimension to consider. Maritime careers are built on mentorship, apprenticeship, and shared responsibility, often passed down through close working relationships. If AI is used without intention, it risks weakening these connections by prioritizing efficiency over engagement. If used thoughtfully, however, it can reinforce them, freeing trainers from repetitive explanations and allowing more time for coaching, oversight, and real-world problem solving.
Knowledge preservation is another area where balance matters. As experienced workers retire, much of what keeps maritime operations safe and efficient exists outside formal curricula. AI can help capture and organize this expertise so it becomes accessible to more learners, but it cannot replace the context and judgment that come from applying that knowledge on the job. AI should complement mentorship, not replace it.
So how should AI be used in skilled workforce training?
The answer lies in purpose and governance. AI is most effective when it is clearly positioned as a support tool, one that expands access to information, assists educators, and prepares learners for human-led training. It becomes problematic when it is treated as a shortcut around investment in instructors, facilities, or experiential learning.
The workforce challenge is not simply a numbers problem; it is a capacity and quality problem. Addressing it requires expanding reach without compromising standards. AI can help do that, but only if its role is thoughtfully defined and continually evaluated.
In the ocean economy, the question is not whether artificial intelligence belongs in workforce training; it already does in various forms. The real challenge is ensuring it is used in ways that respect the complexity of the work, reinforce human expertise, and ultimately make the workforce stronger rather than merely larger.
