This continuing education course explores the integration of artificial intelligence, specifically large language models (LLMs), into athletic training practice. The course provides foundational knowledge of AI systems, including terminology, system architecture, and practical capabilities, while emphasizing limitations and risks associated with clinical use. Content includes definitions of AI, machine learning, and LLMs, along with an applied “maturation model” to conceptualize system capability. The course addresses reliability concerns such as hallucinations, bias, context loss, and overconfidence in AI-generated outputs. Special attention is given to ethical and legal considerations, including HIPAA and FERPA compliance, and the importance of maintaining human-in-the-loop (HITL) oversight in clinical decision-making. Practical guidance is provided on appropriate use cases, prompt structuring, and safeguards to ensure AI functions as a decision-support tool rather than a replacement for clinical judgment. Key Value Add Positions AI as a force multiplier for clinical practice while clearly defining boundaries, risks, and governance needed for safe adoption in healthcare environments.
Jeremy Howard (Sun,) studied this question.