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

Area of Science:

• Health Professions Education
• Artificial Intelligence in Healthcare
• Clinical Informatics

Background:

• Artificial intelligence (AI) is increasingly integrated into healthcare, impacting documentation, clinical decision support, and workflows.
• Current physical therapist curricula lack specific guidance on evaluating AI-generated content and recommendations.
• There's a growing need to prepare physical therapists for AI-augmented practice.

Purpose of the Study:

• To propose an AI Competency Overlay Framework for entry-level physical therapists.
• To define observable, supervisory-level expectations for AI-augmented practice.
• To guide the integration of AI competencies into physical therapy education.

Main Methods:

• Development of a conceptual framework based on competency-based education theory.
• Identification of 9 observable entry-level competencies.
• Organization of competencies into three domains: AI Literacy and System Awareness, Supervisory Practice in AI-Augmented Care, and Ethical and Systems Stewardship.

Main Results:

• The proposed framework comprises 9 observable competencies.
• Competencies are categorized under AI Literacy and System Awareness, Supervisory Practice in AI-Augmented Care, and Ethical and Systems Stewardship.
• The framework addresses risks of automation bias and aligns with health professions' AI-readiness expectations.

Conclusions:

• The AI Competency Overlay Framework clarifies how existing professional obligations apply in AI-assisted clinical settings.
• Implementation requires curricular and assessment adjustments, faculty development, and validation.
• A staged implementation pathway is suggested for adoption.