Attitudes of physical therapists toward AI diagnostics: barriers, enablers, and clinical implications

Artificial Intelligence (AI) is increasingly integrated into healthcare, yet its application in physical therapy remains limited. Unlike other medical fields, physical therapy relies heavily on hands-on assessments and individualized clinical reasoning, which may shape unique adoption challenges. Understanding physical therapists' perceptions of AI-powered diagnostic tools is essential for supporting their effective and ethical implementation.

This study explored physical therapists' perception of AI-powered diagnostic tools and identified key factors influencing their adoption attitudes.

We conducted semi-structured interviews with 27 licensed physical therapists in Saudi Arabia, representing diverse clinical settings and specialties. Transcripts were analyzed thematically to capture perceptions, barriers, and enablers of AI integration.

A total of 27 licensed physical therapists participated (63% female, mean age 29 years, range 24-38; clinical experience 1-7 + years). Participants demonstrated varied perspectives. Ten (37%) emphasized AI's potential to improve diagnostic accuracy, treatment planning, and improve workflow efficiency, while seven (26%) expressed caution about overreliance and limited insight Ethical concerns were common, with 12 (44%) citing patient data privacy and 5 (19%) highlighting cultural sensitivities in female patient care. Barriers to adoption were identified by 14 (52%), including cost, workload, time, and space limitations. Training needs were also emphasized, with 9 (33%) calling for structured workshops and 6 (22%) noting gaps in foundational AI literacy. Overall, most participants viewed AI as a complementary tool rather than a replacement for clinical judgment.

Physical therapists in Saudi Arabia recognize the potential benefits of AI-powered diagnostic tools but remain cautious due to ethical, educational, and systemic challenges.

Addressing barriers through structured training, ethical guidelines, and supportive policies can foster responsible adoption of AI in rehabilitation practice.