The MASS Code Is a Less Than Decade Away. Here Is Where the ROI Is Right Now.
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The MASS Code Is a Less Than Decade Away. Here Is Where the ROI Is Right Now.
By : Pratul Joshi | July - 2026
The future of autonomous and remotely managed marine vessels took a step forward in May 2026 when the IMO approved the non-mandatory Maritime Autonomous Surface Ships (MASS) Code. It establishes risk assessments, system redundancies, and remote operations requirements while clarifying that a human master will be ultimately responsible for such vessels.
The non-mandatory code comes into effect on July 1, 2026, launching an "Experience-Building Phase" (EBP) to test operational practices. Even though the fully mandatory MASS Code is not expected before 2032, the question fleet operators face is: What should they invest in today?
For many shipping companies, autonomy is now a component of business planning. Boardrooms evaluate AI roadmaps, technology providers showcase the sophisticated capabilities of the models they develop, and discussions around autonomous vessels are gaining global momentum.
The commercial realities of fleet operations, however, remain rooted in the present. Vessels need to reduce fuel consumption, avoid unplanned off-hire, comply with environmental regulations, and keep both crew and cargo safe each day.
This is why the most valuable AI investments today are those solving the operational challenges fleets face now. They must build the groundwork that next-generation vessels in the 2030s will eventually depend on.
Separating Tomorrow's Vision from Today's Return
Every technology cycle creates a familiar temptation to invest in the destination even if the journey towards it is long and challenging.
The maritime industry has seen it before. Digital twins, blockchain, alternative fuels, and now autonomous ships are generating interest in what the industry could become in the near future. But fruitful investment decisions cannot be driven by ambition alone. They have to consider what problem a new system integration solves for our vessels today.
This difference is being recognised in the sector. In a recent paper on maritime revolution, Orca AI states that the vision of highly automated vessels is clear, but the path to them will depend on gradual, step-by-step advances in AI-assisted operations. We cannot accelerate the transition to high levels of automation because such navigation depends on a broader ecosystem that extends well beyond onboard technology. Regulatory frameworks, liability models, insurance practices, port infrastructure, and stakeholder acceptance must also evolve before autonomy can be deployed at scale.
By contrast, certain AI-assisted operations are already delivering measurable value for vessels today. Continuous machinery monitoring helps identify emerging equipment issues before they disrupt a voyage. Predictive diagnostics support maintenance planning. Shore teams gain a clearer understanding of fleet operations, while voyage planning can be refined based on real-time operational data rather than waiting for periodic reports.
For fleet directors, this affects the AI investment decisions. Instead of focusing on systems for future capabilities whose governance frameworks are not decided yet, they can invest in tools that improve operational resilience and commercial performance from the moment they are deployed. These in-use technologies will also strengthen the data foundation the industry needs for autonomous ships in the years ahead.
Where AI is Already Delivering Returns
The value of AI is most evident when viewed through the lens of routine fleet operations. The strongest business cases in the industry stem from technologies that enable operators to make more informed decisions during a voyage and improve visibility across a fleet.
These outcomes are measurable and commercially relevant by:
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Avoiding Unplanned Downtime
Unexpected machinery failure is an expensive operational disruption. Unplanned dry docking, off-hire, schedule changes, and the knock-out impact on subsequent voyages can quickly outweigh the cost of preventive action. AI-enabled condition monitoring gives teams earlier awareness of changes in machinery behaviour, so maintenance can be planned around operational requirements before equipment failure. The commercial benefit is measured as much in avoided disruption as in repair costs
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Supporting Better Voyage Decisions
Voyages do not always unfold as planned. Weather changes, fuel consumption is erratic, and operational priorities keep evolving. Planning with AI gives crews and shore teams greater agility to take action based on live operational data rather than relying on assumptions made before departure. They can make informed decisions about routing, speed, and fuel management while there is time to affect the outcome of a voyage.
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Strengthening Shoreside Decision-Making
Fleet management requires a knowledge of what is happening across multiple vessels at any given moment. If they have continuous operational visibility, shore teams can monitor machinery health, vessel condition, and voyage progress from a unified operational view. They can identify the emerging trends that cannot be detected from isolated reports and prioritise support where it is needed most.
The returns from these capabilities are better day-to-day fleet operations and a richer operational data foundation that supports critical decisions.
Building the Infrastructure the Future Will Depend On
Autonomous shipping will emerge through years of operational data, validated processes, and trust in the decisions made both onshore and ashore. The companies best placed to adopt autonomy on their vessels will be those that build on operational discipline by leveraging the technologies they can use now.
The foundation is being built by:
- High-frequency data — Decisions are more dependable when they are based on accurate, continuously updated information and not periodic or siloed reports.
- Continuous sensor intelligence — Reliable streams of onboard data provide a far clearer picture of how vessels and machinery behave under changing operating conditions.
- Comprehensive vessel oversight — With constant visibility, operators understand how long-term operating patterns affect their fleets.
- Validated performance history — Consistent operational records allow trends, anomalies, and maintenance decisions to be assessed with greater confidence over time.
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Decision support systems — AI complements human judgement by presenting timely operational insights that help crews and shore teams respond more effectively.
These technologies deliver tangible value today and will progressively shape the autonomy envisaged for tomorrow's vessels.
Invest for the Next Voyage Before Planning About the Next Decade
Sea journeys have evolved through steady operational progress. New tools and systems are launched, regulations mature, and commercial priorities change, but the strongest investment decisions are those that address the challenges at hand and remain valuable as the industry transforms.
The discussions around AI should not start with autonomy. They must emphasise safer voyages, more reliable operations, and fewer costly disruptions. The outcomes they intend to bring stand on their own commercial merit, regardless of when the next phase of autonomous shipping arrives.
In the years ahead, the technologies with real-world value will be the ones that improve the way fleets operate every day, while also providing the operational insight and data maturity to support whatever comes next.
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