CMT warns against AI dependence
07/07/2025
Condition Monitoring Technologies (CMT) has cautioned against placing sole reliance on artificial intelligence (AI) in ship condition monitoring, warning that human expertise remains essential to ensure safety and accuracy in maritime operations.
As the shipping industry rapidly adopts AI-driven systems for machinery testing and diagnostics, CMT acknowledges the growing potential of these technologies to process vast quantities of data and assist with condition monitoring tasks. However, the company insists that human engineers must remain ‘in the loop’ to validate, interpret and act upon technical data, particularly aboard increasingly complex and automated vessels.
The company currently does not embed AI in its own monitoring devices, relying instead on algorithms to provide reliable data interpretation.
The company suggests that in the future, AI and sensors will be relied upon to flag issues remotely; however, crucially, these alerts will still require expert human evaluation, often from shore-based engineers in contact with on-board or visiting crews. CMT envisions a likely shift towards a hybrid model where monitoring is continuous during voyages, with mobile maintenance teams dispatched to address problems in port.
“Ultimately, we anticipate a set-up similar to today’s engine manufacturer service models,” David continued. “Sensors might identify a fault mid-voyage and a flying repair team would meet the vessel at the next port, but without someone qualified to interpret those readings correctly, there is a serious risk of either false alarms or overlooked faults.”
The concern is compounded by the technical and financial burden of deploying high numbers of reliable sensors across all areas of a ship, especially if these systems themselves become points of failure. AI still lacks the ability to emulate the ‘gut feeling’ that seasoned engineers develop through years of experience, a critical quality when diagnosing nuanced mechanical issues.
“The shipboard engineer is effectively a multi-sensory detector,” David added. “They notice smells, vibrations, small changes in behaviour, things no current AI or sensor suite can reliably do.”
CMT stresses that rather than seeking to replace engineers, AI should be used to augment their abilities, enhancing maritime safety and efficiency through collaboration between people and machines.
While acknowledging the long-term potential of machine learning to replicate more sophisticated aspects of human reasoning, CMT warns that significant obstacles remain. Chief among them is the need for massive, diverse and highly contextual datasets to train such systems effectively, as well as the enormous energy requirements to power advanced neural networks, challenges that are yet to be resolved.
In the meantime, the company calls on industry stakeholders to adopt a balanced and pragmatic approach.
