The fitness app on your phone almost certainly knows more about you than your GP does. Sleep stages, stress load, energy levels, calories in, calories out, HRV trends, step streaks, hydration logs – most platforms have spent the last few years competing to track more of you, not less. Thanks to that, the average gym-goer has access to more granular data about their own body than an Olympic athlete had a decade ago.

The newest trend in the category is the “super app,” one dashboard merging workouts, food, sleep and mental health so that, in theory, every part of your routine talks to every other part. And despite having all this information at our disposal, by most accounts, we feel worse about our training and more stressed about our health than ever.

So what’s so wrong with tracking fitness data, and is there a smarter way to keep your fitness in check?

Is fitness data actually helping you?

In a recent medical study, which covered a sample of 500 smartwatch users, people reported feeling anxious when their physiological data looked abnormal – even when nothing was actually wrong. One example mentioned is that of a hiker whose heart rate spiked to 130bpm on his watch after a long walk; he went from feeling perfectly fine to feeling awful, purely because of the reading, before realising thirty minutes later that altitude was the cause.

Researchers have also found similar patterns among people with atrial fibrillation, where heart rate trackers were linked to more frequent symptom-checking and higher anxiety than those without one.

It tracks (sorry) with what Liam Hogan, Performance Coach and Head of Fitness at VEYR, sees constantly in everyday training. “Many users obsess over calories, recovery scores, or daily metrics while ignoring consistency, sleep, stress, and lifestyle habits,” he says. The irony is that the people most fixated on the numbers are often the ones getting the worst results from them because they’re using the data as verdict rather than a clue.

What’s the cure for data overwhelm?

the data you see on your smartwatch doesn’t always sync with how you’re actually feeling. But what are you supposed to do when your app says one thing and your body says another?

According to Hogan, AI and wearable data should be “guidance, not as something to rely on completely” – useful for spotting patterns, not for overruling how you actually feel.

“If you feel good but your watch says otherwise, trust your body too. The goal is to use technology to improve consistency and understanding, not to become controlled by every score or notification.”

Anxiety specialists have pointed out that “the more we attend to something, the more we’re training the brain to worry about it,” which is more or less the mechanism by which a useful data point turns into a compulsive checking habit.

So, if you’ve hit the point of dreading your own sleep score, Hogan recommends “consistent sleep, regular movement, proper recovery, stress management, and nutrition will always matter more than chasing perfect scores,” he says.

Wearables, in Hogan’s view, are built for spotting long-term patterns – not for reacting to daily fluctuations as though each one is a crisis.

How AI can help you train smarter

Apps that integrate with wearables can read heart rate variability, sleep quality and recovery data, then recommend pushing harder on the days you’re ready and pulling back on the days you’re not – doing the interpreting for you instead of leaving you to stare at five separate numbers and guess.

Form analysis has improved sharply too: computer vision can now watch a squat or a plank through a phone camera and flag depth or alignment issues before they become an injury habit, a job that used to need a trainer in the room.

And rather than locking someone into a rigid twelve-week block regardless of how it’s actually going, the better systems extend a phase when more work is needed or accelerate it when someone’s ahead of schedule, responding to real performance.

The new AI fitness apps on the block

VEYR is built around the Fitness Intelligence Engine™ and a Training Intelligence Graph, a proprietary AI system that learns from a user’s behaviour, workout decisions and contextual data to deliver personalised fitness guidance, with every workout generated uniquely for each individual.

The Engine continuously learns from your behaviour, preferences and feedback to refine future sessions. Meanwhile, the Training Intelligence Graph maps how your choices, preferences and history connect over time, so the system builds on what it’s learned about you session after session.

“People are becoming far more intentional with how they train,” Hogan says. And the next phase of AI has all to do with timing. He expects AI to become “more proactive in helping people spot unhealthy patterns before they become bigger problems,” shifting fitness tech away from reactive scorekeeping and toward something closer to an early warning system.

The winning tools, he says, will be the ones that pair smart technology “with a human understanding of behaviour and wellbeing.”

Does AI fitness coaching actually work?

A scoping review of AI in exercise-based health interventions found genuine improvements in things like blood pressure, adherence and step counts across the small number of trials available – but the review’s own authors were careful to note the evidence base remains preliminary.

German sports scientist Alexander Asteroth, who has studied digital training tools, doesn’t believe trainers can be fundamentally replaced, and argues that artificial intelligence should provide tools to support trainers rather than operate as a fully automated system, because “we are dealing with people.” His point isn’t that the technology is useless – it’s that you always have to critically question what the AI is suggesting, and that requires expertise a real trainer usually brings to the table.

Is an AI fitness app for me?

Probably, if you’re the kind of person who’s never had a coach and wouldn’t otherwise have a plan at all. The clearest win from the research is the cold-start problem: going from nothing to a reasonable, structured programme. If your alternative is no training plan, or recycling the same five exercises out of habit, an AI-generated one is a real improvement.

It’s also a good fit if your main obstacle is logistics rather than expertise. If you travel a lot, train at irregular times, or only ever have twenty minutes and whatever equipment happens to be around, the adaptability could be useful.

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