AI and machine learning continue to be the bogeyman for many in the maritime industry.
Mariners have always relied on experience-honed skills and adaptability to maintain a safe watch. Adding AI to their toolkit signals a shift in skillset – something many in the sector are not comfortable with nor prepared for.
Today, however, these innovations are fast becoming the backbone of a digital sea change, transforming everything from voyage optimization to document processing. In the evolving maritime cyberscape, AI and machine learning are no longer looming threats – they're already part of the modern fabric of the industry.
From fleet-wide analytics to onboard collision avoidance, AI is rapidly integrating itself in every layer of maritime operations. But it may not be about replacing human judgment after all. It may be about empowering it, capitalizing on the shift from manual surveillance and fragmented intelligence to a future where trust in AI systems enables safer and more efficient operations.
And while buzzwords abound, the most successful innovators are those building AI not for its flash but for its function. Leading innovators like SailPlan and Marcura are charting different yet complementary courses in this new era, demonstrating how intelligent systems are enhancing safety, efficiency and trust across the industry.
These companies represent two of the industry's most forward-leaning players. Their work, while distinct in focus, converges on a future where maritime efficiency, compliance and collaboration are increasingly powered by intelligent systems rather than spreadsheets.
Unifying the Chaos
SailPlan tackles a fundamental challenge: broken, fragmented data systems.
“Each ship is a data silo, and even within a ship there are data silos,” says Founder & CEO Jacob Ruytenbeek. Its approach centers on consolidating telemetry, logs and sensor feeds into the SailPlan Cloud, creating a unified context for AI-powered optimization. “The opportunity we saw was to reduce fleet data complexity.”
Ruytenbeek emphasizes the importance of what he calls “explainable optimization” – enabling operators to understand why AI makes certain suggestions. This transparency helps educate mariners while building trust in automation.
SailPlan's core solution is deceptively simple: unify the chaos.
By centralizing disparate streams of data into the SailPlanCloud, the company enables a layer of intelligence to sit atop operations and integrate apps, digital services and machine-learning. This approach gives maritime stakeholders access to a scalable, enterprise-grade infrastructure for real-time fleet monitoring and optimization.
Complementing SailPlan's macro-level intelligence, Marcura embeds AI directly into daily maritime workflows. With more than 950 maritime customers and 25 years of domain history, Marcura brings a knowledge-rich foundation that continually trains and refines its AI systems and shapes the operational layer by deploying embedded AI agents across the voyage lifecycle.
“Our agentic AI is purpose-built to carry out a set of defined activities autonomously within a specific domain,” says Janani Yagnamurthy, Vice President of Analytics. “It understands context, retrieves documents, gathers surface insights, triggers workflows and can initiate next steps.”
Marcura's AI evolution began with document processing using OCR (optical character recognition) and has since expanded to deep workflow automation and risk detection, tallying several wins to demonstrate the validity of its expanded portfolio. Automated charter party checks saved a client potential losses of $120,000, and complex voyage instruction generation went from 2.5 months of manual labor to 40 seconds.
Its suite of tools – DA Desk, Claims, PortLog, MarTrust, ShipServ and VesselMan - addresses operations, compliance, procurement and drydocking. Each works independently, but their power compounds when integrated.
"What really distinguishes our approach is the knowledge infrastructure we've built,” says Yagnamurthy. “Experience trains our AI and informs our services.”
Human in the Loop
Despite all the talk of autonomy, both companies agree that human oversight remains absolutely essential to a better, safer future.
"AI agents can sift through large volumes of data and identify patterns, but it's the operator who makes the final call,” says Yagnamurthy. “This 'human-in-the-loop' model ensures critical judgments remain under human control.”
SailPlan echoes the sentiment. Its explainable AI framework is designed precisely to earn that human trust. “Ship operators struggle to understand why unifying their data matters – until they see how the cost of getting it wrong stacks up,” says Ruytenbeek.
Measuring Success
Effective AI and machine-learning systems minimize errors and failures. Success, therefore, is measured by...what, exactly?
Introducing a new tool into an industry built on a history of hard-won experience and institutional knowledge is challenging. Both companies acknowledge that legacy systems and cultural inertia remain formidable obstacles.
For Marcura, the main hurdles include integration complexity and customer skepticism. Through adaptable tools and close collaboration with users, however, Yagnamurthy believes that these challenges are instead learning opportunities. "Customer concerns tend to evaporate once they dip their toes into the water."
SailPlan sees the challenge a little farther upstream but approaches it with a similar philosophy. The company believes in educating customers on why their fragmented tools need a centralized backbone. "Eventually, operators realize a comprehensive solution is required," says Ruytenbeek. "Leading companies are getting ahead of these problems now."
Looking ahead, both companies envision more than just better tools. They envision a smarter operating system – and operators – across the entire industry.
The Trouble With Standards – And Why That's Okay
Their shared philosophy positions both companies as proponents of "augmented” rather than “automated" decision-making, an approach likely to resonate across a cautious industry governed by a regulatory process that can be glacial in comparison to innovation.
This disparity in evolutionary pace highlights an important tension in maritime innovation – balancing speed with compliance. Both companies are finding different paths to success in this environment, SailPlan by sidestepping bureaucracy while Marcura preempts it.
"Standards bodies serve to slow down industry progress in many cases,” Ruytenbeek says bluntly. "We avoid them.”
But SailPlan is confident that the industry will evolve. While the Internet forced a data revolution across other terrestrial industries, “the Internet didn't really reach ships for a long time. But that's changed," Ruytenbeek explains.
Marcura, on the other hand, sees value in developing internal frameworks ahead of lagging regulation. “Rather than waiting for standards to emerge, we've built our own robust privacy and security frameworks,” says Yagnamurthy. These include client-specific environments, role-based access and secure AI pipelines.
Enhanced Decision-Making
In an índustry often slow to change, these two companies aren't just keeping pace with innovation, they're setting it.
The maritime sector has always required a combination of expertise, adaptability and endurance. What SailPlan and Marcura are proving is that AI doesn't replace those traits – it enhances them. Whether they're unifying shipboard data, embedding AI agents into workflows or building entire ecosystems from scratch, the goal is clear: to turn maritime's mountains of information into meaningful, timely and trustworthy decisions.
Most importantly, the safe seas of the future will be navigated by mariners embracing AI as a means of perfecting their skills one data point, one algorithm and one integrated system at a time. – MarEx
Chad Fuhrmann is a Senior Consultant at Core Group Resources.
The opinions expressed herein are the author's and not necessarily those of The Maritime Executive.
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