AI Resilience Report forAthletic Trainers

Right now, AI is more often augmenting athletic trainers than replacing them. The biggest gains are showing up in the paperwork-heavy parts of the job. According to a recent National Association of Insurance Commissioners survey of 93 insurance companies in 16 states, 84% of responding insurers across health care insurance product lines use AI or machine learning to speed up claims review, which directly touches the insurance-filing task that O*NET flags as 72% automatable (KFF ^[1]).

On the clinical side, the National Athletic Trainers' Association now offers continuing-education programming on "Artificial Intelligence in Athletic Training" ^[2] as part of its 2025 essential curriculum, signaling that the profession is actively learning the tools rather than ignoring them. AI is also showing up in injury prevention and rehab: UC San Diego researchers built a generative-AI model called BIGE that generates the best motions athletes can execute during exercise to avoid injury and improve performance, or the best motions for athletes that need rehabilitation after an injury. Sports-medicine physicians describe similar uses in their own practices, noting that AI can analyze data from wearable devices, motion capture systems, and historical injury records to identify risk factors for injuries.

The hands-on tasks — massage, escorting injured athletes to hospitals, leading warm-ups — remain firmly human.

Adoption is moving quickly on the administrative side because the tools are commercially available, cheap, and tied to insurer cost savings. Technology companies are vying for insurers and TPAs to adopt their AI-related products with the promise of faster, more accurate claims review, which pulls trainers into AI-mediated workflows whether they want it or not. Clinical adoption, however, is slower.

Sports-medicine leaders warn that the deployment of generative AI in clinical settings must be approached with caution, with issues related to data privacy, ethical considerations, and the necessity for rigorous validation protocols. There's also a real labor-market push: the average annual salary for a university athletic trainer is $58,820, nearly $38,000 less than an occupational therapist, and burnout is driving many trainers out of school settings — which makes administrators eager for AI tools that reduce documentation load rather than cut headcount. Finally, leaders in college sports are being told to treat AI as a strategic capability, not a gadget, and to preserve the human core of athlete care.

The takeaway for students considering this career: AI will likely handle more of the typing, billing, and pattern-spotting, while your hands, eyes, and judgment courtside become more valuable, not less.