The Human, The Machine and the Story Between
Every now and then a new technology comes along that promises to change everything. Carbon fibre transformed bicycle design. Power meters changed the way athletes train. Electronic shifting brought new levels of precision and reliability. Now Artificial Intelligence is beginning to influence almost every industry, and cycling is no exception.
Some people see AI as a threat to traditional expertise. I see it differently. As a bike fitter, my job has always been about gathering information, understanding the rider and making informed decisions. AI doesn’t replace that process; it enhances it. It gives us the ability to process more information, identify patterns more quickly and spend less time on administration so we can spend more time helping cyclists achieve their goals.
At its core, bike fitting is about understanding people. Every rider arrives with a unique history, a different body and a different reason for riding. Some are chasing performance. Some are managing injuries. Others simply want to ride further and more comfortably. The fitter’s role is to collect all of those pieces and build a complete picture. The better the information, the better the decisions, and AI is becoming an incredibly useful tool in helping us manage that information.
Where We Are Today
Artificial Intelligence is already deeply embedded in our everyday lives. It helps doctors analyse medical images, assists engineers in designing complex systems and allows athletes to better understand their training and recovery. In cycling, AI is increasingly being used by coaches, sports scientists and product designers to gain deeper insights from vast amounts of data.
Bike fitting is following a similar path. Modern fitting systems can track movement, measure joint angles and record large amounts of positional data. Cameras and sensors can capture information that would have taken hours to collect manually only a decade ago. Yet despite these advances, the most important component of any bike fit remains the rider sitting in front of us.
Technology can tell me that a rider’s knee is moving a certain way. It cannot tell me about the crash that changed their confidence descending mountains. It cannot explain why numb hands have stopped them enjoying weekend rides with friends. It cannot understand the excitement of preparing for a dream cycling holiday. Those conversations still matter, and they always will.
What I Am Doing Today
At Fusion Peak, I have embraced AI in a way that strengthens the human side of bike fitting rather than replacing it. One of the most valuable tools I use is voice recording throughout my fitting sessions. This allows me to capture a far greater level of detail than would otherwise be possible, preserving important information about injuries, goals, equipment history, riding habits and observations made throughout the session.
For many cyclists, riding is much more than exercise. It is their social connection, their adventure, their challenge and often a significant part of their identity. Every rider has a story. By recording and organising this information, AI helps me preserve those stories with greater accuracy and provides a valuable reference point for future sessions.
After the fit, I use AI to help review measurements, cross-reference notes and ensure consistency throughout the data collected. Rather than relying solely on memory or handwritten notes, I can revisit every important detail and build a more complete understanding of the rider’s needs. The result is better continuity, better reporting and ultimately better outcomes for my clients.
Checking the Numbers
One of the areas where AI has become particularly useful is quality control. Every bike fit generates a substantial amount of data, including body measurements, bicycle dimensions, positional coordinates and frame geometry calculations. Accuracy matters because small errors can have significant consequences when selecting equipment or designing a custom bicycle.
To help verify my work, I use AI to compare bike fit measurements against the CAD drawings I produce during the fitting process. It acts as a second set of eyes, reviewing dimensions, checking relationships between measurements and helping identify inconsistencies that might otherwise be overlooked. As with any engineering process, independent verification increases confidence in the final result.
This does not replace professional judgement. It simply allows me to work with a higher level of accuracy and consistency. The technology helps reduce the possibility of human error while allowing me to focus on interpreting the information and making decisions that best serve the rider.
