Once connected, you can ask questions like:
"Can you give me a detailed analysis of how I performed in my last race?"
Some important context here: Strava's AI "insights" have sort of sucked, and annoyed me, in the past. Athlete Intelligence (conveniently abbreviated as AI) is the Strava feature that writes text responses to your workouts. Strava calls these "insights," but as far as I can tell they mostly regurgitate the information from the workout description, sometimes with added errors. I've found AI fitness summaries largely useless, and Strava's version checks every box: It doesn't use enough context to understand what's going on, it presents generic advice as if it were personal, and it's overconfident in incomplete data. So, skeptical as I am, I gave Strava's latest Google Gemini integration a whirl. Here's what it does, how to set it up, and whether it's worth it.
The connection is optional and read-only. You choose whether to connect, and you can disconnect at any time from Connected Apps in Gemini. Worth knowing: The consent screen says Gemini will access workout activities, performance metrics, training plans, gear, clubs, and profile info, and that parts of your conversation, plus your name and email, may be shared with Strava and used according to its Privacy Policy.
How Google Gemini interprets Strava data
The first question I asked was one of Strava’s examples, "Am I getting faster at the same heart rate?" Gemini said yes, I was seeing solid efficiency gains. Like many AI tools, it told me what I wanted to hear. I had to point out that heat and temperature are huge variables. When I steered the chat in that direction, Gemini, of course, agreed immediately ("you hit the nail on the head") and explained that my mid-September long runs happened in 75–84°F weather with higher humidity, which inflates heart rate, while October's cooler temperatures made the same effort look better. That's an important caveat the first answer left out entirely.
Credit: Meredith DietzUnfortunately, the results weren't reliable at first. When I asked for a detailed analysis of every marathon-distance effort since 2019, Gemini said I had exactly one, the Marine Corps Marathon on October 25, 2026. In reality, I've logged at least eight. When I asked why it couldn't see them, it explained that its access is limited to my recent history, roughly summer 2026 onward, because of how pagination limits the number of past activities returned at once. It also offered a workaround: Give it specific dates and locations.
I then asked "What am I doing right and what am I doing wrong as a runner?" After knowing the queries need to be so specific, I intentionally wanted to test a vague, simplistic question. The answer was, true to form, overly flattering—though I didn't disagree with the guidance itself. I need more speed workouts! I know this! I didn't need a chatbot to tell me, though maybe some other Strava user does. Gemini's suggestions (polarize training, add one dedicated threshold day) are sound, yes, but they’re also generic. Most recreational runners could glance at my Strava and spot the same strengths and weaknesses. Similarly, Gemini then set itself up for a slam dunk by prompting me to ask whether my easy runs were too fast. The answer: My easy days were happening at nearly my marathon pace (about 9:43/mi), and I should slow down by 45–90 seconds per mile, to roughly 10:30–11:15/mi. I completely agree. That being said, my big takeaway here remains the same: Don't confuse AI-generated advice as some newfound, personalized insight. It’s often the same conventional wisdom you already know, or could figure out with a tiny bit of research from a real, human source.
Credit: Meredith DietzThe bottom line
For many users, the smartest approach may be to skip AI summaries and focus on raw data. After all, your training load, sleep duration, and heart rate trends are already perfectly actionable.
If you do use Google Gemini to analyze your Strava data:
Push back. Ask about weather, terrain, and fatigue before accepting a flattering conclusion.
And if the well-documented yet still murky privacy risks are worth it for you, that's your prerogative.
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