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AI running plans are guidebooks, not rulebooks, warns physiotherapist, as injuries spike due to below-standard AI training apps

 

From marathon first-timers to experienced club runners, AI-powered coaching apps have become an increasingly popular part of training routines across the UK. However, recent news has highlighted that AI apps are actually causing more injuries. 

 

A record-breaking 1.1 million people applied for the ballot to enter the 2026 TCS London Marathon, a 36% increase over the 2025 ballot. With the marathon quickly approaching on April 26th, many runners have turned to app-generated plans for fast, accessible guidance as their training ramps up. 

 

Research indicates that over four in five (84%) fitness consumers are interested in using AI to personalise their workout routines. While these tools offer structure and motivation, experts warn that their growing influence comes at a critical point in the training calendar, when rapid mileage increases and race pressure can significantly raise the risk of injury.

 

Runna, a popular AI-powered running app, has faced recent criticism for potentially causing increased, faster-paced injuries, such as stress fractures and shin splints, by designing training plans that are too aggressive and offer insufficient recovery.

 

Research, analysed by sports-tech brand Enertor, found that 86% of AI training plans built using minimal runner data were rated below expert standard. Even when more detail was provided, half still failed to meet professional benchmarks.

 

Alongside this, research also shows that increasing a long run by more than 10% can raise injury risk by up to 64% within one to two days, with larger mileage spikes more than doubling the risk. This is particularly concerning when algorithms adjust training largely on pace and logged distance rather than health and well-being, asking runners to push harder without understanding their condition.

 

Physiotherapist and Enertor ambassador Danny Brunton says the biggest risk he sees with AI-generated training plans is load mismanagement.

 

“AI plans are mainly guided by data such as pace, distance and heart rate, but they can’t fully interpret pain patterns, tissue tolerance, previous injury history, sleep quality, stress or subtle fatigue markers,” Brunton explains. “Without that clinical insight, runners may continue progressing through discomfort, increasing their risk of overuse injuries. There’s also a tendency to trust the plan more than what our own body is telling us.”

 

He adds that injury risk often increases when runners feel aerobically fit, but their tissues have not adapted at the same pace.

 

“Cardiovascular fitness can adapt much faster than musculoskeletal tissues,” Brunton says. “Our heart and lungs may feel ready, but tendons, bones and connective tissue adapt more slowly. Rapid increases in load don’t allow sufficient time for tissue remodelling, which increases the risk of overload injuries such as stress reactions or tendinopathies.”

 

Common injuries linked to poorly managed training load include Achilles and patellar tendinopathies, medial tibial stress syndrome (shin splints), plantar fasciopathy and patellofemoral knee pain, all of which are strongly associated with excessive or poorly progressed training.

 

While AI coaching tools focus primarily on pace and distance, Brunton notes that runners should also consider a range of additional factors.

 

“Sleep quality, life stress, footwear transitions and previous injury history are just some of the things that influence tissue capacity and injury risk,” he says. “These variables are difficult for AI systems to accurately take into account.”

 

The popularity of digital training makes the issue timely. Nearly one in five (19%) UK adults now run at least once a month, and participation in digital running communities continues to grow, meaning more runners are relying on app-based guidance to prepare for races.

 

Despite the concerns, Brunton stresses that AI can still play a positive role when used appropriately.

 

“AI adds value in structure, accountability, data tracking and progression planning,” he says. “Apps like Runna, Garmin Coach and RunKeeper can be excellent for recreational runners seeking guidance and consistency. Where AI falls short is in clinical reasoning. It can’t assess movement quality or interpret early warning signs of injury in the way a physiotherapist or experienced coach can.”

 

Managing impact forces during higher mileage training can also support long-term tissue health.

 

“Keeping cumulative load within tissue capacity is key,” Brunton explains. “That means progressing mileage gradually, incorporating rest or cross-training days, maintaining strength training and wearing shock-absorbing inner soles. Lowering repetitive peak forces and improving load distribution supports tendon and bone adaptation over time.”

 

Once runners have reviewed their programme and managed cumulative load, Enertor advises continuing to prioritise overall wellbeing. The brand recommends its PX1 Running Insoles, designed to provide advanced shock absorption and energy return during high-impact training phases.

 

 

Developed for elite athletes, Enertor’s PX1 insole technology is now widely used by runners of all levels. The PX1 material absorbs up to 89% of shock energy, reducing impact forces that can contribute to injury.

 

By reducing repetitive impact forces on joints and soft tissue, PX1 insoles aim to support tissue tolerance during heavier mileage blocks, something AI plans may schedule but cannot physically protect against.

 

“For runners following structured programmes, reducing impact stress can help tissues adapt more comfortably,” Brunton adds.

 

“Treat the plan as a guide, not a rulebook. Only increase weekly mileage by around five to ten percent, don’t ignore pain that alters your gait or lasts longer than 48 hours, prioritise sleep and nutrition and seek early input from a physiotherapist rather than pushing through. Protecting your health is what ultimately gets you to the start line.”

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