Integrating AI-Augmented Practice Into Physical Therapy Education: A Competency Overlay Framework

Artificial intelligence (AI) is increasingly embedded in health care documentation systems, clinical decision support, and workflow technologies. Physical therapist education must prepare graduates to evaluate AI-generated documentation and recommendations, yet curricula rarely specify observable behaviors for doing so. The purpose of this position paper is to propose an AI Competency Overlay Framework that defines entry-level supervisory expectations for AI-augmented physical therapist practice and supports targeted integration into existing curricula.

Physical therapy education programs should adopt an AI Competency Overlay Framework: 9 observable entry-level competencies organized across AI Literacy and System Awareness, Supervisory Practice in AI-Augmented Care, and Ethical and Systems Stewardship. The rationale rests on documented automation-bias risks, emerging health professions AI-readiness expectations, and competency-based education theory. The framework is offered as a conceptual position for consensus refinement and empirical testing.

The proposed overlay clarifies how established obligations for patient safety, documentation integrity, and ethical reasoning apply when AI contributes to clinical work. A staged implementation pathway is presented as an illustrative route for adoption. Implementation will require curricular and assessment changes, faculty development, consensus validation, and pilot testing.