AI adoption shifts tanker operations and oversight

Artificial Intelligence is starting to alter the day-to-day operation of tankers in meaningful and measurable ways, particularly in areas such as voyage optimisation, predictive maintenance and decision-support systems.

Interviewed ahead of Riviera’s upcoming webinar How will AI transform tanker operations?, Navig8 Group head of HSSEQ Srini Mullur outlined where AI is already proving its worth and what challenges remain for its effective integration.

Captain Mullur is a Master Mariner and at Navig8 Group, he leads strategic operations, optimises asset performance, and drives digital transformation across the fleet.

“In voyage optimisation, real-time data inputs are used to reduce fuel consumption and emissions,” said Capt Mullur.

He noted machine learning models are being trained to identify component wear before failure occurs, enabling planned intervention and reducing unplanned downtime. Safety monitoring is also undergoing change through the deployment of AI-enabled surveillance and anomaly detection systems. These systems are already being designed to detect operational risks earlier than conventional methods, enhancing the scope for proactive management.

But the introduction of artificial intelligence into operational workflows is not without its constraints. Chief among them is the issue of legacy system integration, “One key lesson would be to identify the importance of interoperability,” said Capt Mullur.

Many AI tools are designed for open data architectures, whereas tanker systems have evolved around proprietary, siloed data formats. Successful deployments have focused on normalising that data and implementing middleware to connect systems, “Human oversight remains critical during the transition phase to validate AI-generated outputs,” he said.

Crew and office personnel roles are also evolving and Capt Mullur observed AI is reshaping traditional workflows by promoting faster, data-driven decision-making, “The crew’s role will shift from execution to supervision,” he explained.

Onboard personnel will increasingly be asked to validate the recommendations made by AI tools, while shore-based staff take a more strategic role across fleet operations.

Capt Mullur emphasised these developments underscore the need for continuous training, so seafarers remain equipped to interpret and question AI insights.

One of the most persistent barriers to wider AI use in tanker operations is data integrity.

According to Capt Mullur, “The biggest hurdle is data standardisation – vessels often generate inconsistent formats across systems and manufacturers.”

Sensor quality and poor connectivity further affect data availability and reliability. These limitations in turn restrict the usefulness of AI models, which depend on accurate input to generate actionable output, “Without high-integrity data, AI models struggle to deliver accurate results,” he said.

As tanker companies explore AI-based systems, they are increasingly being called upon to address regulatory and ethical considerations.

Capt Mullur said many operators are aligning with emerging digital governance frameworks to ensure their AI tools comply with safety and cyber-security rules.

He also identified a need for ethical transparency, “Operators are increasingly ensuring human accountability in all safety-critical operations,” including the ability to clearly explain how and why an AI tool has recommended a course of action.

Looking ahead, Capt Mullur expects tangible improvements in safety and commercial performance through the deployment of unmanned bridge watch systems for temporary navigation, AI-assisted compliance tracking and energy efficiency optimisation. These technologies, he said, can enhance safety while also reducing emissions and operational costs.