The AI Coaching Hype Cycle
AI doesn't do a good job of coaching, ignore what the direct-to-athlete platforms tell you about it. They are talking their own book. They won’t replace good coaches any time soon, if ever. Right now, they are just a much better version of a generic training plan. All tech goes through a hype cycle, AI is no different and the AI hype cycle is probably going to be the most extreme tech hype cycle we’ve ever had. I’ve already seen signs of athletes who were initially very excited, begin to lose interest. Boring repetitive workoutsWorkouts that are consistently too hard or too easyRandom workouts showing up in their calendarThe funny thing is, this can just as easily happen when you have a coach, but you can have a conversation with your coach and resolve these pretty quickly and move forward. A coach can explain to the athlete that sometimes workouts should be repetative to get the best results, and above all else, the human connection with a coach makes boring repetitive training a lot more fun, to the point where athletes might not even notice that it’s boring. That’s what humans can do for each other. Let’s dig in a bit more to how I think things will play out. I’ll use the typical tech ”Hype Cycle” framework to make a bit of a prediction. The stages are the “Innovation Trigger”, “Peak of Inflated Expectations”, my favorite, the “Trough of Disillusionment”, the “Slope of Enlightenment”, and finally we settle on the “Plateau of Productivity” Innovation Trigger AI-driven platforms launch, claiming to offer personalized coaching without the need for a human coach. It sounds great—tailored workouts, data analysis, and 24/7 availability. Athletes are excited to try it, especially with the promise of performance improvement, paired with cutting out the cost of a coach. Peak of Inflated Expectations This is where the platforms really crank up the hype. They start pushing the idea that AI can handle everything a coach does. It’s marketed as a perfect substitute, capable of customizing workouts, adjusting on the fly, and reading athletes' needs based on data alone. Athletes jump on board, expecting AI to deliver. But the cracks start showing pretty quickly. Trough of Disillusionment Once athletes start using these platforms, they realize AI has some big limitations. It’s not the game-changer they were expecting. Repetitive workouts: AI lacks variety. After a while, the workouts get boring because they don’t adapt the way a human coach would.Workouts that don’t fit: Athletes start noticing that the training is either too easy or too hard, and the AI doesn’t seem to adjust well to their personal progress or life context, much of which doesn’t show up in the data.Random, unrelated workouts: Sometimes the AI throws in sessions that don’t make sense or aren’t aligned with the athlete’s goals, making the whole experience feel disconnected.At this point, athletes start losing interest, realizing that AI just can’t replace the personal touch and expertise of a human coach. Slope of Enlightenment After the initial excitement fades, it becomes clear that AI isn’t a full-on coach replacement—it’s a tool, or more like an assistant. AI can help with some of the workload—tracking progress, organizing data, or automating simple tasks—but it still needs a coach to provide the real guidance, creativity, and adjustments that athletes need. Athletes and coaches start seeing that AI works best when paired with a coach, not as a standalone solution. Plateau of Productivity Eventually, AI finds its place. It becomes a useful tool to help coaches with the day-to-day stuff, but it’s not trying to take over the relationship. The hype settles down, and AI proves to be a supportive piece of the coaching puzzle, rather than the whole thing. This cycle has played out over and over again with all technology and likely will be very similar with AI coaching. Conclusion AI can assist with crea
