Maritime recruitment is having its AI moment, and the loudest question in the room may be the wrong one. Captain Vinil Gupta, CEO and founder of COMPETIQ, writing for Splash247's SplashTech section, says the industry keeps arguing about whether machines will replace people. His counter-question is simpler: can technology make hiring fairer? For anyone booking ocean freight, that is not an HR footnote. The officers and ratings on the vessel carrying your containers were picked through a process that still runs heavily on referrals, manning-agent relationships and personal judgement.
What Happened
Gupta's piece lands in the trade press at a point where AI conversation in shipping has settled into two familiar camps: automation of onboard systems, and cost-cutting in shore-side administration. He argues both framings miss the part of the business where bias does the most damage, which is who gets shortlisted for a berth in the first place.
COMPETIQ, the company he founded, works in seafarer competency assessment. That gives the argument a commercial angle worth naming plainly. Even so, the underlying point is one crewing managers have raised for years. Selection today depends on which agency holds the file, which nationality a given owner prefers, and which candidate happens to be known to the superintendent. Structured competency data, applied consistently, is the alternative Gupta puts forward.
Impact on Freight Rates and Operations
Crewing does not move spot rates the way a blanked sailing does. It moves something slower and harder to price: schedule reliability. A vessel that cannot sail because a certificate lapsed or a relief officer never arrived becomes a missed berth window, and missed berth windows become the roll-over notices that land in your inbox two days before cut-off.
Manning costs also sit inside the operating expense base that carriers defend when spot rates soften. If fairer, faster screening shortens the time between a crew gap opening and a qualified officer joining, the operational benefit shows up as fewer off-hire days rather than a line item on your invoice. That is a quiet gain, and it is the kind shippers usually only notice when it disappears.
What Shippers Should Do
- Ask carriers about schedule reliability, not just rate. On tenders, request on-time arrival performance for the specific string you use rather than the trade lane average.
- Build crew-change ports into your risk map. Services routing through hubs with heavy crew rotation carry a different delay profile than direct strings, and your buffer should reflect that.
- Keep your own buffer honest. If your production plan assumes a fixed transit, model a delay scenario and cost it, so you know what a slipped week is actually worth before you have to argue about it.
- Watch which vendors publish their methodology. Assessment and screening tools that will not explain how they score candidates are the ones most likely to encode the bias they promise to remove.
Key Takeaway
The AI question worth asking in shipping is not how many jobs it removes, but whether it makes the selection of the people who move your cargo more consistent and more defensible.
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Source: Splash247