Fitness Apps Lag Behind AI Era, Drawing Sharp Critique from Tech Visionary

London, UK – Martin Varsavsky, a prominent tech entrepreneur and founder, has publicly lambasted the current state of popular fitness applications, asserting that their functionality remains stuck in an outdated "2010" paradigm despite the rapid advancements in artificial intelligence. His critique, shared via a recent tweet, highlights persistent issues across major platforms like Strava, Apple Health, Garmin, Whoop, Oura, MyFitnessPal, Peloton, and Zwift, calling for a fundamental shift from mere data recording to intelligent interpretation.

Varsavsky's tweet detailed several common frustrations: "Strava: Forget to stop recording, get in a car → suddenly you’re 'running' 100 km/h. Record with Apple Watch + iPhone → it shows two rides instead of merging." He further noted that Strava splits segment medals for identical passes and counts chairlifts as descents in ski mode. Users of Apple Health and Watch reportedly experience single nights of sleep broken into multiple "sessions," while Garmin devices count "stroller-pushing or brushing teeth as 'steps.'"

The entrepreneur also pointed out that Whoop and Oura often confuse meditation with naps, leading to inaccurate "bad sleep scores" after long flights. MyFitnessPal requires repetitive daily food entries, and platforms like Peloton and Zwift fail to integrate outdoor and indoor workouts for a unified training load. Varsavsky emphasized, "In 2025, this isn’t acceptable. Fitness Apps must stop being dumb recorders and start being smart interpreters."

He proposed clear applications for AI to resolve these shortcomings: "AI should: Detect impossible speeds (car vs. run). Merge duplicate recordings across devices. Consolidate segment medals. Distinguish sleep, naps, and meditation. Learn daily meals instead of making you re-log them forever." Varsavsky concluded his argument by stating, "If AI can write code and analyze genomes, it can definitely refine fitness data recording."

While the issues raised by Varsavsky resonate with many users, the integration of advanced AI solutions faces complex challenges. Strava, for instance, explicitly prohibits third-party applications from using its data for AI model training or extensive analytics, as outlined in its updated API terms. This policy hinders external developers from creating the very AI-driven improvements Varsavsky advocates for using Strava's ecosystem. The company has stated these changes are for "enhanced privacy and user control," aiming to prevent unexpected data surfacing.

Despite these hurdles, the broader fitness technology industry is increasingly exploring AI. Companies like FitnessAI and Dr. Muscle already leverage AI for personalized workout plans and adaptive training. The market for AI fitness apps is projected to grow significantly, with revenue anticipated to reach $10.06 billion by 2029. This growth is driven by the demand for personalized insights, real-time feedback, and enhanced user engagement.

The debate underscores a critical juncture for fitness apps: balancing data privacy and control with the immense potential of AI to deliver a truly intelligent and seamless user experience. As AI continues to evolve, the pressure on major fitness platforms to move beyond basic tracking and embrace sophisticated data interpretation will only intensify.