Artificial Intelligence (AI) is everywhere in my daily life. It’s writing emails, predicting patterns, and optimising everything from logistics to advertising. However, the one area I don’t hear about it is rowing. But why? For a sport with a deep focus on efficiency, AI has been left sitting on the bank, watching the boats clunk past.
Rowing’s obsession with tradition
Rowing is one of the most tradition-bound sports in existence. The training model is consistent over many years: long hours on the water, relentless erg sessions, and a deep-seated belief that success comes from pure, unfiltered graft.
There’s nothing inherently wrong with that. Resilience is part of what makes rowers great and a key reason why I enjoy the sport. But other endurance sports have shown that raw effort alone isn’t enough. Smart training, powered by data, is how you get the best results.
Rowing, for the most part, has resisted this shift. Coaches still write training plans based on experience with only a small influx of data-driven decision-making. Athletes still grind through endless steady-state work without knowing if it’s the most efficient way to improve. AI could change all of that.
Smarter training schedules
One of AI’s biggest advantages is its ability to optimise training loads.
Right now, most rowing training follows a rough template for the entirety of a squad: a mix of endurance, power, and technique work structured around the coach’s philosophy. But is it always the best approach?
AI could analyse an athlete’s physiological data, heart rate, stroke efficiency, power output, and recovery and adapt training in real-time. If a rower is fatigued, it could automatically scale back intensity to prevent overtraining. If an athlete is recovering quickly, it could push them harder.
Instead of a rigid training schedule, AI could create a dynamic, evolving programme that adapts daily, ensuring every session is the correct session. No wasted miles. No overtraining. Just efficient, personalised improvement.
Precision target splits
Right now, rowers rely on trial and error to figure out their ideal race pace. Coaches might set target splits based on past performance or gut feeling. But AI could take the guesswork out of the equation.
By analysing historical data, AI could predict exactly what an athlete’s optimal split should be for any given distance, under any given conditions, not just based on what they’ve done before, but what they’re capable of.
It could also adjust targets dynamically. If a rower performs above expectations during a session, AI could nudge their split target down slightly, encouraging them to push harder. If they’re struggling, it could adjust expectations to keep them from blowing up.
This kind of real-time data-driven pacing has transformed marathon running, for example in Eliud Kipchoge’s sub-two-hour attempt. There’s no reason it couldn’t do the same for rowing.
Rowing’s Kodak moment: the cost of falling behind
Kodak famously owned the digital photography industry before it even existed. They held the patents, they had the technology, and they saw the future. But they refused to embrace it, fearing it would cannibalise their lucrative film business. Instead of leading the revolution, they clung to tradition. By the time they realised their mistake, it was too late. Kodak faded into irrelevance, while others took the market they should have owned.
The sport isn’t short on talent or dedication. It’s just stubbornly clinging to an outdated way of thinking. The cost of this resistance isn’t just financial; it’s lost opportunities, wasted training hours, and an inability to gain the marginal improvements that separate silver from gold.
The cost of sticking with the old ways
The real expense isn’t in adopting AI, it’s in not adopting it. Right now, rowers are grinding through training programmes that are based on tradition rather than optimisation. They’re spending endless hours on the erg, often with no guarantee that the workload is precisely what they need. Coaches are making educated guesses about training loads, recovery times, and race strategies when AI could provide exact answers.
The first to move will win
The first teams to fully integrate AI will see immediate gains, more efficient training schedules, precisely targeted splits, and live feedback that corrects technique in real time. They’ll cut out wasted effort and optimise every single stroke. Once one crew wins Olympic gold with AI-driven training, the debate won’t be about whether AI belongs in rowing. It’ll be about why it took so long to get there.
About The Author
Discover more from JRN
Subscribe to get the latest posts sent to your email.
