The data behind greener shipping
Wind is returning to cargo ships, and it makes for a striking image: tall rigid wings and spinning rotors on vessels carrying grain and steel across the same oceans that sailing ships once crossed. It is easy to look at those sails and assume that is what decarbonisation looks like.
But the sails are only the visible part of the story. A great deal of the progress in greener shipping is far quieter, and far less photogenic. It comes down to data.
Reducing emissions in shipping is often imagined as a hardware problem: new fuels, new engines, wind assistance, cleaner technology fitted to the ship. All of that matters. Yet a significant share of the savings available today comes not from new equipment at all, but from operating the ships we already have more intelligently. And operating intelligently is, at heart, a data problem.
Consider a few of the levers.
Weather routing is one of the oldest ideas in seafaring, made newly powerful by better information. Choosing a route and a timing that work with the wind, waves and currents rather than against them can cut fuel use meaningfully over a voyage, with no change to the ship itself. The difference between a good route and an indifferent one is a question of data, well used.
Speed and voyage planning is another. Fuel consumption rises steeply as a ship goes faster, so even a modest reduction in speed can save a surprising amount of fuel. The catch is that slowing down only helps if the whole voyage is coordinated. There is little point steaming hard to reach a port, only to sit at anchor for two days waiting for a berth. Arriving "just in time" rather than "as fast as possible" saves fuel, but it depends on information flowing between the ship, the port and the charterer.
Performance monitoring is quieter still. A ship loses efficiency gradually as its hull fouls and its machinery drifts from peak condition. Left unwatched, that decline is invisible until it shows up on the fuel bill. Watched properly, the data tells you when a hull clean or an adjustment will genuinely pay for itself.
And then there is the most honest lever of all: measuring what actually works. Wind assistance, hull coatings, fuel additives and routing tools are all sold with impressive savings figures. The difficulty is that a saving demonstrated on one ship, one route and one set of conditions may look very different on yours. Without good measurement, it is almost impossible to tell which investments are earning their keep and which are simply expensive. Reliable measurement is also, increasingly, what regulators and customers expect you to be able to show.
This is where data and AI genuinely help, though not in the way the marketing suggests. AI does not replace the naval architect or the judgement of an experienced captain. What it does well is make sense of large, continuous and often messy streams of information: optimising routing and speed against live conditions, spotting performance drift early, and separating a real saving from ordinary variation. It turns data that ships already produce into decisions that people can act on.
There is a common thread here with everything else in responsible AI adoption. The value is not in chasing every promising new solution. It is in knowing, honestly and specifically, what moves the needle for your fleet, your routes and your cargoes. Good measurement is what keeps that honest.
Greener shipping will certainly be built on new fuels and new hardware, and the wind is a welcome sight back on the water. But a great deal of it will also be built on something far less glamorous: the steady discipline of using data well, and staying clear-eyed about what actually delivers.
If you are weighing up where to focus your own efficiency efforts, and how to tell which of them are truly working, that is exactly the kind of conversation we enjoy having.
