Introduction

By analysing large datasets, AI can support clinical reasoning, tailor interventions to individual needs, and support routine administrative tasks, allowing physiotherapists to focus more on patient-centred care. AI-driven tools also improve patient engagement through customised educational resources and personal feedback mechanisms.

However, these advancements come with significant risks, including the potential for deskilling due to over-reliance on AI, data privacy and security concerns, clinical errors with unclear liability, depersonalisation of care, and the amplification of biases present in training data. To address these challenges, strategies such as comprehensive AI education, fostering human-AI collaboration, ethical guidelines, transparent AI systems, patient-centred approaches, and adaptive regulatory frameworks are essential to ensure AI enhances, rather than deviates from high-quality physiotherapy care.

Clinical practice: Key takeaways

• Enhanced clinical support: AI can improve clinical reasoning, treatment personification, and administrative efficiency, freeing clinicians to focus more on patient care.

• Risk of over-reliance: Dependence on AI may erode critical thinking, clinical reasoning, and hands-on skills essential to physiotherapy practice.

• Ethical and legal concerns: Data privacy, security risks, and unclear accountability in cases of AI-related errors require careful consideration and robust safeguards.

• Maintaining human connection: While AI can optimise processes, preserving the therapeutic relationship and personalised care remains crucial.

• Strategic integration needed: Successful adoption of AI requires comprehensive education, ethical guidelines, transparent systems, and adaptive regulations to balance innovation with patient safety.