XMAR: Is Shipping Ready to Evolve with AI and Data-Driven Decision-Making?

Decades after other industries embraced digital transformation, shipping still relies on email chains, phone calls, and gut feel. But AI and data-driven decision-making are starting to challenge the status quo, forcing companies to rethink how they operate. 

Some shipowners and operators see AI as a buzzword. Others see it as an existential threat. The reality? AI is neither magic nor a job killer. It’s a tool that can finally bring logic, transparency, and efficiency to an industry that’s been built on relationships and intuition rather than data. 

The problem: decisions based on instinct, not intelligence 

Shipping has never been a data-led industry. Chartering managers, bunker buyers, and fleet operators make multi-million dollar decisions daily, often without real-time data or historical benchmarking. 

A bunker procurement manager, for example, might buy fuel based on a few WhatsApp quotes, comparing offers in their head rather than through a structured system. An operator might adjust a ship’s speed based on personal experience rather than predictive analytics. A charterer might pick a fixture based on the strength of their broker relationship rather than hard market data. 

These aren’t necessarily bad decisions, these are the best decisions people can make with the information they have. But that’s exactly the problem. Too many critical decisions are still being made with incomplete, outdated, or biased information. 

AI is already proving itself 

AI isn’t some futuristic concept, it’s already proving its value in shipping. Some of the most forward-thinking companies are using AI-driven routing models to cut fuel consumption, optimize speed, and avoid congestion. Others are applying machine learning to detect vessel performance anomalies before they turn into costly breakdowns. 

Take predictive maintenance. By analyzing engine performance and historical failure patterns, AI can tell shipowners when a part is likely to fail, long before it becomes a problem. This isn’t hypothetical. Maersk, for example, has been using AI to reduce unplanned maintenance and improve vessel uptime. 

Another clear use case is AI in chartering. Today, a human broker or charterer has access to a fraction of the data that AI can process in seconds. AI tools can scan thousands of past fixtures, market conditions, and vessel positions, flagging optimal deals that might have been missed in a manual search.

Why adoption is slow 

If AI is so effective, why isn’t every shipping company using it? The biggest barrier isn’t the technology, it’s the mindset. Many decision-makers are skeptical, seeing AI as a black box rather than a reliable tool. Others don’t want to change a system that has worked for them for years. 

Then there’s the data problem. AI is only as good as the data it’s trained on, and too many shipping companies still rely on fragmented, inconsistent, or outright inaccurate data. A 2022 survey by Splash247 found that 68% of shipping executives rated their internal data management as ‘poor’ or ‘very poor’. Without clean, structured data, AI can’t deliver reliable insights. 

And let’s be honest, there’s also resistance because AI threatens the way things have always been done. A charterer who’s built their career on instinct doesn’t want to be told that a machine can do their job better. A bunker trader who thrives on personal relationships doesn’t want full price transparency to erode their margins. 

The companies that embrace AI will win 

Despite the resistance, AI adoption isn’t a question of if, it’s a question of when. The companies that embrace AI now will gain a competitive edge, reducing costs, improving efficiency, and making smarter decisions. 

The best examples of AI adoption in shipping aren’t replacing humans—they’re empowering them. AI doesn’t remove the need for experienced operators or traders, but it gives them better tools to make better decisions. The smartest companies aren’t asking, ‘Will AI replace my team?’ They’re asking, ‘How can my team use AI to be 10 times more effective?’ 

As regulations tighten, margins shrink, and competition increases, the companies that embrace data-driven decision-making will outperform those that rely on outdated methods. AI isn’t here to replace people, it’s here to replace inefficiency. The only question is whether the industry is ready to accept it. 

Platforms like XMAR are already proving that AI and data-driven decision-making can transform bunker buying. By providing full price transparency, structured negotiations, and real-time insights, XMAR is helping shipping companies move away from outdated processes and toward smarter, more strategic fuel purchasing.

This article is sponsored by XMAR. For more information visit the company online.