{"id":1911475,"date":"2026-04-29T12:32:53","date_gmt":"2026-04-29T09:32:53","guid":{"rendered":"https:\/\/analyse.optim.biz\/?p=1911475"},"modified":"2026-04-29T12:32:53","modified_gmt":"2026-04-29T09:32:53","slug":"ai-is-already-transforming-pro-cycling-heres-how-top-teams-and-riders-are-using-the-tech-to-get-faster","status":"publish","type":"post","link":"https:\/\/analyse.optim.biz\/?p=1911475","title":{"rendered":"AI Is Already Transforming Pro Cycling. Here’s How Top Teams and Riders Are Using the Tech to Get Faster."},"content":{"rendered":"
Pro racing is on the precipice of an AI revolution, and you\u2019d better get used to it.<\/p>\n
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After years of dabbling at the margins, the way the world\u2019s elite trains, fuels, and races is set to be transformed by both DIY programs and multinational data partners.<\/p>\n
And all of us weekend warriors will feel the trickle down, no matter where we land in the \u201crobot vs human\u201d debate.<\/p>\n
Cycling was pushed a few inches closer to the AI precipice in the past week.<\/p>\n
Team Ineos confirmed a five-year partnership with AI giant Netcompany in a deal it hailed \u201cone of the most significant technological and commercial partnerships in professional cycling.\u201d<\/p>\n
The tech giant\u2019s systems will \u2013 apparently \u2013 fast-track the team back to the top of the Tour de France by streamlining and optimizing its performance structures.<\/p>\n
Only one week earlier, USA\u2019s Olympic superstar Kristen Faulkner revealed she\u2019s coded herself a system which \u201cbuilds personal models of [her] physiology.\u201d<\/p>\n
The Harvard computer science graduate correlated data points from 4,400 hours of training that span as far as watts and HRV to menstrual phase and blood markers.<\/p>\n
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The result?<\/p>\n
A pinpoint program that brought her to a 20-minute power PB at the PanAM Championships.<\/p>\n
Netcompany-Ineos goes big on the data boom<\/h2>\nDanish AI giant Netcompany joined Ineos as new co-title sponsor. <\/span> (Photo: Gruber Images)<\/figcaption><\/figure>\n
Ineos got a significant boost to its hopes of leveling with the superteams in its long-term deal with Netcompany.<\/p>\n
The partnership is reportedly worth a whopper \u20ac100 million over five years. But perhaps equally significantly, the team will use Netcompany\u2019s \u201cPulse\u201d system to cut through the hot mess of data that surrounds all professional sport.<\/p>\n
The tie-up makes the snappily named Netcompany-Ineos the latest big-money squad to put its faith in big data.<\/p>\n
Visma-Lease a Bike and UAE Emirates-XRG have been working with Mistral and Analog, respectively, for some time.<\/p>\n
Rival WorldTour heavyweights Red Bull, Lidl-Trek, and Decathlon have not publicly discussed using similar systems, but it seems unthinkable that they wouldn\u2019t be.<\/p>\n
There are gains that are more than marginal to be had.<\/p>\n
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Too much data and too many decisions<\/h2>\nFaulkner said she was building her AI platform for up to 10 hours a day during the off-season.<\/span> (Photo: Gruber Images)<\/figcaption><\/figure>\n
Why does all this matter for the pros, and for us?<\/p>\n
In theory, a bunch of very complicated algorithms will help athletes and staff see the bigger picture.<\/p>\n
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Because an average WorldTour pro gathers dozens of metrics on any given day. Even a 10-hour-a-week Average Joe with a smart watch and a power meter will collect more data than they can make sense of.<\/p>\n
Watts, beats per minute, kilojoules, TSS, temperature, and humidity get spat out of bike computers.<\/p>\n
HRV, resting heart rate, bodyweight, hydration status, and sleep scores are recorded by a toolbox of wearables, scales, and questionnaires that are poured over by coaches every day.<\/p>\n
But while popular platforms like TrainingPeaks can collect all the data into one place, it has largely remained unreconciled.<\/p>\n
Until now.<\/p>\n
Platforms like those now being used by Faulkner and the WorldTour superteams can synthesize billions of bits of training information.<\/p>\n
They\u2019ve got the computing power to spit out micro-insights that inform \u2013 or automatically adjust \u2013 training programs, race schedules, and tactical planning.<\/p>\n
As a back-of-a-napkin example: \u201cWhich rider goes well on X percent grades at Y degrees centigrade when their training load is Z?\u201d \u201cSend them to this or that race.\u201d<\/p>\n
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Those concerned power meters and race radios are stealing the humanity from cycling have a sizeable new problem to stress about.<\/p>\n
Why the growth of AI in cycling accelerated<\/h2>\nPro cycling has more data than it can make sense of. (Photo: Gruber Images)<\/span><\/figcaption><\/figure>\n
Cycling\u2019s AI revolution has moved fast in recent months.<\/p>\n
Performance directors talked about it in the very future tense when we investigated the AI arms race little more than one year ago.<\/p>\n
\u201cIt would be a huge next step if we could bring together all this data we collect that lives in different places,\u201d Red Bull\u2019s outgoing lead coach Dan Lorang told Velo<\/em> last winter. \u201cIt could change our entire approach.\u201d<\/p>\n
For many inside the sport, the new AI acceleration has been too long coming.<\/p>\n
Performance leads at Jayco-AlUla and Tudor have long been telling us that the future of elite performance lies in using data to make hyper-specific, micro-programmed training schedules.<\/p>\n
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Faulkner builds an AI future for female performance<\/h2>\nFaulkner believes AI could have an outsize impact on the under-researched world of female performance.<\/span> (Photo: Gruber Images)<\/figcaption><\/figure>\n
Faulkner told Velo<\/em> that embracing AI systems like hers could be a crucial next step in the chronically underexplored world of female strength and endurance.<\/p>\n
\u201cThere is a real need for better tools in this area,\u201d Faulkner told Velo<\/em>. \u201cMost sports science research has historically been conducted on men. But so many generalized training models do not fully reflect women\u2019s physiology.\u201d<\/p>\n
Elite women have been pushing for more specific guidance since well before Stacey Sims began a paradigm shift in the 2010s with her philosophy, \u201cwomen are not small men.\u201d<\/p>\n
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\u201cMenstrual cycle phases, hormonal shifts, recovery patterns, metabolism, and even how heat or sleep interact with those variables can all matter,\u201d Faulkner said.<\/p>\n
\u201cThat does not mean there is one universal formula for women athletes, but it does mean there is a real opportunity to build more individualized, evidence-driven systems that take those factors seriously,\u201d she said.<\/p>\n
Faulkner, who races with EF Education-Oatly, wants her model to inspire other organizations to invest in tools and innovation built specifically for women.<\/p>\n
She\u2019s so confident in her program she\u2019s even putting it through beta testing with external users and considering a wider rollout.<\/p>\n
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The research I needed about my own body did not exist. So I built it with AI.https:\/\/t.co\/fvX09qFXuZ<\/p>\n
\u2014 Kristen Faulkner (@FaulknerKristen) April 22, 2026<\/p><\/blockquote>\n<\/div>\n
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But isn\u2019t AI already here?<\/h2>\n
So what of mass-market AI-driven platforms like Vekta, TrainerRoad, Hexis, and FoodCoach, you ask?<\/p>\n
We weren\u2019t talking about an \u201cAI revolution\u201d when they landed into our App Stores several years ago.<\/p>\n
The difference is that systems like Netcompany\u2019s or Faulkner\u2019s significantly expand the scope.<\/p>\n
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Totally disparate datasets are being distilled in this next wave of artificial intelligence in cycling. For example, beyond just training and nutrition and to the inclusion of weather, biomarkers, and menstrual status.<\/p>\n
The future of AI in cycling? To \u2018help\u2019 but not \u2018replace\u2019<\/h2>\nPractitioners said AI should inform how users make decisions, but not have the ultimate say in how they act.<\/span> (Photo: Gruber Images)<\/figcaption><\/figure>\n
It will only be a matter of time before the findings from pro cycling\u2019s dive into all-dimensional datasets trickle into mass-market performance platforms.<\/p>\n
But is this all a good thing?<\/p>\n
The world has been grappling for years with the apocalyptic idea that robo brains will replace human practitioners.<\/p>\n
Many leading sport scientists believe it\u2019s on real-life staff to accept where they can be outperformed by the endless capacity of AI, but to be cognizant of where machines can fail.<\/p>\n
Nuance, uncertainty, and context can be lost by even the most robust computer program.<\/p>\n
Faulkner \u2013 somebody who\u2019s more invested in data than most \u2013 applied similar caution. AI should help athletes and performance experts, not lead or replace them.<\/p>\n
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\u201cI do not use AI to tell me what I\u2019m feeling. I use it to help explain why I might feel a certain way and what I can do about it,\u201d she told Velo<\/em>.<\/p>\n
\u201cTechnology and data should bring us more in tune with our bodies, not further from them,\u201d she said. \u201cThat\u2019s how I use it, and that\u2019s the direction I hope this technology moves in.\u201d<\/p>\n
That\u2019s why AI training and nutrition plans will never be faultless.<\/p>\n
The experience and sense of the end-user is what ultimately counts.<\/p>\n
[analyse_image type=”featured” src=”https:\/\/velo-cdn.outsideonline.com\/wp-content\/uploads\/2026\/04\/Copy-of-redbull.jpg”] Jim Cotton Updated April 30, 2026 10:49AM Pro racing is on the precipice of an AI revolution, and you\u2019d better get used to it. After years of dabbling at the margins, the way the world\u2019s elite trains, fuels, and races is set to be transformed by both DIY programs and multinational data […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[226,71],"class_list":["post-1911475","post","type-post","status-publish","format-standard","hentry","category-politics","tag-crawlmanager","tag-velo-outsideonline-com"],"_links":{"self":[{"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=\/wp\/v2\/posts\/1911475","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1911475"}],"version-history":[{"count":0,"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=\/wp\/v2\/posts\/1911475\/revisions"}],"wp:attachment":[{"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1911475"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1911475"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/analyse.optim.biz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1911475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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