AI Fitness Summaries: Are They Really Helpful?

Fitness apps are now packed with AI summaries. These summaries are supposed to make sense of all the data collected from wearables. But do they really help?

Examples of AI Summaries in Fitness Apps

• Strava's Athlete Intelligence: Takes workout data and tries to explain it in simple terms.
• Whoop's Whoop Coach: Gives daily reports and workout suggestions.
• Oura's Oura Advisor: Summarizes data and points out long-term trends.
• Smart Beds: Greet users with summaries of their sleep.

The Problem with AI Summaries

Sleep Summaries

• Example: "You slept 7 hours with a resting heart rate of 60 bpm."
• Issue: This information is already visible in the charts. The summary doesn't add much.

Workout Summaries

• Example: "Intense run with high heart rate zones."
• Issue: Doesn't consider important factors like weather, recent injuries, or workout history.

Limitations of Current AI Features

• Lack of Holistic Insights: Can't provide personalized insights because they don't have access to all necessary health data.
• Balance of Factors: Have to balance speed, cost, data privacy, and legal liability.
• Repackaged Data: Often just repackaged data without adding real value.

Chatbots in Fitness Apps

• Whoop Coach: Might not respond to injury-related questions.
• Oura Advisor: Provides more helpful responses but requires user guidance.

Conclusion

Current AI features in fitness apps are not very useful. They are more like book reports written by a fourth-grader relying on a Wikipedia summary. They are not worth paying extra for. Maybe one day, these AI insights will be truly helpful. But that day is not today.