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Manish Singh from Aboutships writes about the future of maritime autonomy and delegation.
As businesses and societies are getting hands on with early applications of agentic artificial intelligence, I am increasingly being asked about what it means for the maritime world.
Unlike traditional automation onboard ships or general industries, agentic AI will become increasingly context-aware, autonomous in repetitive and iterative processes, and gradually capable of making consistent decisions on behalf of users to achieve defined goals.
So in a sector that is chronically grappling with workforce shortages, complex regulations, and rising operational demands, the implications seem profound. But are they?
Maritime operations involve a high volume of repetitive, compliance-heavy, and time-sensitive workflows. With the exponential gains in ship-shore connectivity, we now have fleets that benefit from always-on ship-to-shore data exchange. So we can now deploy AI agents that do more than analyse data—they can act on it.
Before we touch upon the obvious risks that come to mind – let us explore some agentic applications ranging from voyage planning to port call optimisation.
Guardrails and protection are the key issues, because from a ‘can tech do’ perspective, we can easily envisage application such as:
- Dynamically rerouting vessels to avoid weather or congestion.
- Automating compliance reporting across EU ETS, IMO, and FuelEU Maritime mandates.
- Triggering predictive maintenance based on sensor anomalies.
- Negotiating bunker purchasing windows for cost and carbon optimisation.
Before you shoot the messenger, I am just hypothesising here because these tasks taken by colleagues at sea and ashore today are reliant on fragmented information, tools and manual intervention. So one should expect with an ever smaller crew onboard, can we start selectively equipping our workforces with intelligent software agents that learn, iterate, and act independently within predefined guardrails.
Let’s look at what incremental gains may such agentic use bring to operators.
- Performance optimisation. Agentic systems could continuously monitor hull resistance, engine loads, and fuel quality to autonomously adjust speed and route—balancing fuel savings against ETAs and commercial requirements. Officers of the watch would monitor and override as needed.
- Emissions and ESG reporting. AI agents can help responsible personnel onboard and in shipmanagement teams ashore to maintain digital twins of voyage emissions and trigger auto-filing of compliance documentation. They can also flag deviations and propose corrective actions in real-time.
- Cargo and port logistics. Agents can interface with various operating systems and help crew and operators coordinate just-in-time arrivals, liaise with port systems, and even queue virtual slot bookings—reducing idle time and improving turnaround predictability.
- Cybersecurity and anomaly detection. Given an ever increasing burden for teams at sea and ashore to mitigate rising cyber risk, AI systems can baseline ship network behaviour and autonomously isolate anomalies or execute contingency protocols—without waiting for onshore input. Then shore-based cyber resilience teams or response centres can investigate and respond as needed.
- Workforce augmentation. This is already happening on an application by application basis to some extent. We will have agentic AI tools becoming part of onboard crew, to serve as digital assistants—managing logbooks, checklists, and regulatory alerts in natural language interfaces.
And these only seem to be a fraction of the use cases that could help solve real world immediate issues. But what risks would we be onboarding, if agentic AI was adopted in advance of appropriate risks mitigation and guardrails in place?
Delegating decisions at sea— touches safety of human life, marine environment and cargo and exposes considerable societal, compliance and financial exposure if things go wrong.
We will need to navigate complex challenges such as:
- Data reliability. AI actions are only as good as the data they ingest. Unclean or incomplete data can trigger suboptimal decisions. AI hallucinations could prove catastrophic if relied upon, especially in agentic applications.
- Accountability. Who will be liable if an autonomous system makes a wrong call? Regulatory and insurance frameworks are years behind, while technologists continue to push minimum viable products into the field.
- Cyber resilience. Agentic AI will be particularly fertile targets for malicious cyber attacks. As ships become smarter, they become more exposed.
- Crew trust. Much as we view AI with a mix of excitement and trepidation at home and work, so will our colleagues at sea and ashore. Acceptance will depend on explainability and ability to override. If it appears like ‘Black-box AI’, it will understandably be resisted.
So what do we do? Rejecting the approaching wave of agentic AI would be sheer denial. So early adopters must plan carefully structured deployment, with robust audit trails, user persona or role-based overrides, and hybrid human-AI decision models. Regulatory agencies like IMO and class societies are likely to mandate minimum standards of supervision, fallback logic, and cyber assurance.
In terms of our technology ethic the maritime industry must evolve from fragmented digitisation to orchestrated autonomy. This would mean embedding AI agents into integrated marine operating systems, not just standalone tools. It will be vital to proactively equip workforces with training to include human-AI collaboration frameworks. A key area of regulatory evolution will focus on establishing common standards for interoperability and safety assurance across maritime technologies.
So in summation, ships a decade from now can expect leading fleets to operate semi-autonomous technologies in data-rich, digitally governed, and agent-enhanced environments. Ships will sail with fewer colleagues onboard, but supported by agentic intelligence in code.
Agentic AI, if implemented wisely, won’t just automate tasks—it will amplify maritime workforce capabilities, reduce error, and reshape the economics of fleet management. It’s not the future of shipping—it’s the operating system of future-ready fleets.
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