Opportunities

An overview of the opportunities afforded by generative AI in the context of clinical practice.

The integration of generative AI into physiotherapy practice offers transformative potential to enhance how practitioners assess, treat, and engage with patients across various clinical settings. This technology presents opportunities to augment clinical reasoning, personalise interventions, and streamline administrative processes that traditionally consume significant practitioner time. By using AI thoughtfully, physiotherapists can potentially improve clinical reasoning, develop more tailored treatment approaches, and create more efficient practice workflows, ultimately allowing for greater focus on the human elements of therapeutic care. The following examples suggest some of the way that generative AI might enhance physiotherapy practice.

Note that some of the functionality described below requires custom software i.e. it is not available directly via frontier language models.

---

Enhanced administrative efficiency

Automating routine administrative tasks to reduce clinician workload, freeing up time for direct patient care.

• Streamline documentation, appointment scheduling, and report generation

• Reduce time spent on repetitive tasks, improving productivity

• Standardise reporting for consistent communication with other healthcare providers

Enhanced clinical reasoning

Analyse patient data, including medical histories, assessment outcomes, and patient preferences, to support clinical reasoning and potentially improve diagnostic accuracy (Bilika, et al., 2024; Bragazzi & Garbarino, 2024; Cabral, et al., 2024).

• Identify subtle patterns and risk factors that might be overlooked by offering alternative perspectives

• Support clinical reasoning in less experienced clinicians, sometimes by suggesting connections between symptoms in complex presentations

• Suggest differential diagnoses, based on patient presentation and clinical history

• Support clinical decision-making in conditions of uncertainty (Steyvers & Kumar, 2023)

Personalised treatment planning

Create personalised treatment plans by considering multiple patient-specific factors such as medical history, lifestyle, and personal goals and preferences (Baig, et al., 2024; Wah, 2025).

• Help adjust treatment plans based on patient progress and feedback

• Support goal-oriented therapy, improving patient motivation and adherence through personalisation

• Enhanced patient clinical pathway with access to personalised advice

• Provide personalised exercise reminders and progress tracking

For some of the examples above, it seems likely that we will soon start seeing the development of personal apps, created by patients + AI, that support their rehabilitation goals.

Enhanced patient education and engagement

AI can generate customised educational materials to improve patient understanding and support active participation in their care.

• Create tailored exercise guides, progress trackers, and interactive learning tools

• Provide on-demand information through chatbots and virtual assistants

• Foster better adherence to treatment plans through personalised engagement strategies

By leveraging these opportunities, physiotherapists can enhance clinical outcomes, improve patient satisfaction, and optimise workflow efficiency.

Discussion questions on the opportunities of integrating AI into clinical practice

1. How might AI-enhanced clinical reasoning and assessment change the way you approach patient evaluation?

2. In what ways could personalised AI-generated treatment plans improve patient outcomes in your practice?

3. How do you envision using AI feedback in your day-to-day patient interactions?

4. What administrative tasks in your practice could benefit most from AI-support?

5. How might AI-powered patient education tools change the way you communicate with and engage your patients?

6. How could AI-powered tools be used for prevention and health promotion initiatives?

7. What ethical considerations should be addressed when implementing AI tools in physiotherapy practice?

8. How could AI-enhanced assessment tools change the way we measure and document patient outcomes?

9. In what ways might AI support interdisciplinary collaboration and communication in healthcare teams?