Like with every other corner of our lives, AI has flooded popular fitness apps and wearables. From Strava’s Athlete “Intelligence,” to Garmin’s underwhelming Connect+ subscription, to Whoop’s recovery recommendations, these AI-powered features claim to transform raw data into actionable wisdom. The reality? Most of these AI summaries are expensive digital fortune cookies that tell you what you already know, while often missing what actually matters.
This matters not just because I’m a hater, but because users are losing money here. Many of these AI features are locked behind premium subscriptions, creating a sort of artificial scarcity around what is basic data interpretation. Here’s why most AI fitness summaries are garbage, and which ones you can maybe trust.
Lack of context
AI fitness systems operate in a data vacuum. They can tell you your heart rate variability dropped, but they can’t account for the work presentation that kept you up, the argument with your partner, or the glass of wine you had with dinner. Human performance is influenced by countless variables that these systems simply cannot access or interpret.
I’m not saying I want these tools to have access to my calendar and lifestyle, but a more useful system would note “your performance declined likely due to the three consecutive days of poor sleep coinciding with your business trip.”
Generic advice disguised as personalization
This is the one that makes my eyebrows shoot up to the sky. These systems excel at repackaging your existing data with generic health advice, creating the illusion of personalized coaching while delivering one-size-fits-all platitudes. Strava’s AI is notorious for restating the data from the run description. Take this example from one of my runs earlier this week, where Strava’s AI clearly just pulls from what I already wrote about my experience and runs it through a thesaurus. Plus, “varied elevation changes” sounds smart, but what that describes is…well, running on most roads.
Credit: Meredith Dietz
And this doesn’t even get into how wildly inaccurate that calorie count is.
True personalization would require understanding your specific goals, training history, injury patterns, and lifestyle constraints—information these systems rarely have access to. Instead, most AI fitness summaries draw from the same pool of conventional fitness wisdom. My colleague Beth Skwarecki shares some fun examples of Garmin’s AI being wildly inaccurate in her piece here, and also sent me some more below. Check out the inane platitudes and straight-up inaccuracies.
Credit: Beth Skwarecki
Useful AI would be predictive insights, rather than reactive summaries. I’d be interested in seeing when I’m heading toward overtraining, identify optimal training windows based on recovery patterns, or suggest specific adjustments to prevent injury.
Overconfidence in incomplete data
Fitness trackers are notoriously inaccurate for many metrics, particularly calories burned, sleep stages, and stress levels. AI summaries compound this problem by presenting conclusions that aren’t necessarily true. This week I went on an extremely challenging run in 85% humidity, pushing through foot pain. Imagine my frustration when this was Strava’s interpretation of my experience:
Credit: Meredith Dietz
How to make the most of AI fitness summaries
Strava is my go-to fitness app, and Garmin is my go-to watch. But when it comes to Strava’s “Athlete Intelligence” and Garmin Connect+, user reactions have been mixed at best. I’ve personally received summaries like “Your heart rate was elevated during your run” or “You covered more distance than your previous workout.” These insights are immediately visible in the raw data and don’t require AI processing to understand. And again, the core issue here is cost.
As a user in r/Garmin puts it, these “insights” are just “the most basic summary of your workouts possible…I was really hoping that it would be an actual chatbot that you could discuss training with etc to create plans.” On that front, your best bets on the market right now are Whoop and Oura. Their AI-driven insights have been positively received, even if their value proposition is increasingly questionable. Compared to the generic summaries on other apps, these insights operate as chatbots. This way, when you ask specific questions (already using your brain more than merely reading a summary), you’ll receive articles that go into more (human-written) detail.
Another app that does a decent job at adding much-needed context is Runna. Its insights actually pull data from weather and your training calendar. Here’s another screenshot from Beth, showing how Runna does more than simply restate the data you personally entered.
Credit: Beth Skwarecki
Plus, in Runna, you don’t get it until you rate your workout, and you can skip the rating without affecting anything else about how the app works. Which brings me to one the main takeaways here: AI doesn’t have to be an all or nothing commitment. If you’re already paying for a subscription that includes AI fitness summaries, here are some of your options.
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Ignore the summaries completely. For most users, the smartest approach is to disable AI summaries entirely and focus on raw data. Your training load, sleep duration, and heart rate trends provide perfectly actionable information.
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Cherry-pick useful data points. If you choose to engage with AI summaries, treat them as starting points for your own analysis, rather than definitive guidance. Look for patterns and trends, while ignoring specific recommendations.
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Disable the summaries altogether. In Garmin Connect+ and Strava, you can go to your settings and simply opt out of AI summaries. In Oura and Whoop, you don’t get the AI unless you start a conversation with the bot.
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Invest in human expertise instead. Hey, maybe the subscription cost of multiple AI fitness platforms could fund periodic consultations with qualified sports scientists, nutritionists, or coaches. These people can provide genuinely personalized guidance based on your specific situation and goals.
The bottom line
If you ask me, your fitness tracker already provides the data you need to make informed decisions about your training and recovery. Learning to interpret that data yourself will serve you better than waiting for AI to do it for you—and it won’t cost you an additional monthly subscription fee. The technology exists to create genuinely useful fitness AI, but for the time being, my fitness summaries are just expensive digital noise.
