Artificial intelligence has quietly moved into nearly every aspect of modern life, and running is no exception. What was once the domain of experienced coaches and carefully structured training logs is now increasingly being handed over to algorithms, apps, and automated feedback systems. AI running coaching platforms promise a future where your watch, your phone, and a machine-learning model can guide you to your next personal best. It sounds efficient, scientific, and undeniably appealing.
Is AI Running Coaching Really Coaching?
Beneath the surface, an important question remains: are these platforms truly coaching, or are they simply repackaging generic training plans with a layer of technology?
To understand this shift, it is necessary to look at how these AI platforms actually function. Most systems rely on a combination of user inputs and wearable data. A runner enters their goal race, current fitness level, and availability, and the platform produces a structured programme. Over time, that programme is adjusted based on incoming data such as pace, heart rate, and estimated VO₂ max, typically pulled from devices like Garmin watches.
One of the most prominent platforms in this space is Runna, which has seen rapid global growth. Marketed as an AI coach, Runna gives the impression of intelligent, adaptive training. However, a closer examination reveals that its foundation is built on structured programmes designed by human coaches. The “AI” component largely sits on top of these templates, making rule-based adjustments rather than deeply learning the athlete in a dynamic or intuitive way. Research and industry analysis, such as that discussed by TechRadar , suggests that many of these platforms are better described as automated programme generators rather than AI or true coaching systems.
Other platforms, such as Garmin Coach and TrainAsOne, attempt to go a step further by continuously adapting training based on performance metrics. These systems use increasingly sophisticated models to adjust load and intensity, giving the impression of a living, responsive coach. Yet even the most advanced systems share a common dependency: they are only as good as the data they receive.
Accuracy of Data
This is where the cracks begin to show. Wearable technology, particularly GPS-based devices, is far from perfect. We only need to turn to social media to see fellow runners complaining about the unreliability of their running watches telling them that they are in dire need of rest and recovery or that they are merely maintaining fitness and not increasing as per their training. A study published on ResearchGate examining the accuracy of Garmin GPS running watches found consistent measurement errors in distance and pace, even when tested repeatedly on the same route. These discrepancies are caused by satellite positioning issues, environmental interference, and device limitations. Another study available through the National Institutes of Health highlights that while smartwatch-derived predictions can correlate with performance, meaningful error margins still exist, particularly over longer distances. In a previous article we discuss the inaccuracies with wrist-based heart rate monitor technology (PPT).
In practical terms, this means that an AI system could be adjusting your training based on flawed inputs or inputs that are suited to the ‘average’ runner and not to the individual. A slightly inaccurate pace reading or an overestimated distance might seem insignificant in isolation, but when fed into an algorithm that is constantly recalibrating your programme, those small errors can compound into meaningful training miscalculations. The principle is simple and unavoidable: if the input data is flawed, it follows that the output will be flawed as well.
This concern is not limited to academic research. Across social media and running communities, many runners openly question the reliability of their devices. Reports of watches overestimating distance, producing erratic pace spikes, or generating inconsistent heart rate data are common. When those same data streams are used to drive AI-generated training plans, the risk is that the programme begins to drift away from the athlete’s actual physiological reality.
The Real Difference Between Computers and Coaches
Yet the most significant limitation of AI coaching lies not in the technology itself, but in what it fundamentally cannot understand. Running is not purely a numbers game. It is shaped by fatigue, stress, motivation, lifestyle, and emotion. An algorithm cannot truly interpret the difference between a tough session caused by poor sleep, a demanding work week, or the early signs of illness. It cannot sense when an athlete is mentally drained or when they need encouragement rather than intensity. Even the most advanced system lacks the ability to contextualise the human experience behind the data.
“AI is a tool. Running is you, your training, your mood, psychological state and more. It’s not an algorithm. A computer can only work with the numbers fed to it by wearable tech. The most important metrics, it cannot make sense of.”
-David Ashworth
This is where the value of a human coach becomes undeniable. A coach does not simply analyse numbers; they interpret meaning. They recognise patterns that extend beyond metrics and adjust training based on a holistic understanding of the athlete. They know when to push and when to hold back, when to adapt a session and when to scrap it entirely. Perhaps most importantly, they provide accountability, reassurance, and belief—elements that no algorithm can replicate. A coach often is someone who has been there themselves and experience what you are experiencing. AI can never share true experience and understanding with an athlete.
There is also the matter of long-term development. AI platforms tend to optimise for short-term outputs, focusing on the immediate goal race or performance metric. A human coach, on the other hand, builds an athlete over months and years, layering fitness, resilience, and experience in a way that supports sustained progression.
Computers RUNNING Your Life
None of this is to suggest that AI has no place in running. On the contrary, it is a powerful tool. Data tracking, trend analysis, and performance monitoring have never been more accessible, and when used correctly, they can significantly enhance the coaching process. The future of endurance training is not a choice between AI and human coaching, but rather a combination of both. Technology can inform decisions, but it should not make them in isolation.
For runners who are serious about improving performance, avoiding injury, and reaching their full potential, the conclusion is clear. AI coaching platforms offer convenience and accessibility, but they fall short where it matters most. They lack context, nuance, and human understanding. They are efficient, but not intuitive. They are structured, but not truly personalised.
“AI is real cute. But you are not a Tamagotchi. You still need to put in the training! Running is, and always has been a physical extension of our emotions, and not of our computers.”
-David Ashworth
At A-Team Coaching, the approach is fundamentally different. Technology is embraced, but never relied upon blindly. Data is analysed, but always interpreted through the lens of experience. Training is not generated by an algorithm, but shaped by expert coaches who understand the complexities of performance.
The result is a coaching experience that goes beyond numbers. It is personal, adaptive, and built around the individual, not just their data.