Welcome
This discussion document explores the integration of generative AI in physiotherapy, developed through collaborative activities at the 2024 IFOMPT conference. It serves as a stimulus for physiotherapy departments, schools, organisations, regulators, practitioners, students, and even patients, to engage in meaningful - and hopefully productive - conversation about what this rapidly evolving technology might mean for the profession.
The document is intentionally designed for flexible engagement rather than linear reading. Recognising the diverse needs and contexts of the wider professional audience, we've structured the content so that you're able to dip in and out according to your specific interests, working context, and use cases. Some information may be repeated across sections, as we don't expect anyone to read the document from cover to cover.
An overview of the potential of AI in clinical practice, exploring how generative AI can support reasoning, personalise treatment planning, improve monitoring, increase administrative efficiency, and strengthen patient education while addressing associated risks and implementation strategies.
An overview of the potential of AI in physiotherapy education, exploring how generative AI might create personalised learning experiences, enhance simulations, automate assessment processes, and develop critical research skills, while also considering the challenges to traditional educational approaches.
An overview of the potential of AI in research, exploring how the technology can streamline literature reviews, uncover complex data patterns, generate novel hypotheses, standardise protocols, and facilitate global collaboration while addressing scientific integrity and ethical considerations.
As you explore this resource, we encourage you to consider both the opportunities and challenges that generative AI presents to physiotherapy. The insights gathered here are not prescriptive, but rather aim to spark thoughtful discussion, critical reflection, and proactive planning within your own professional context. Whether you're a clinician, educator, researcher, student, or connected to the profession in another capacity, there's relevant content to help you navigate this technological transformation.
Note: This document deliberately focuses on generative AI's current capabilities rather than speculative future applications. We've tried to ground our discussion in what today's AI models can actually, and avoided unsubstantiated claims about potential future developments. At the same time, we hope that the document remains relevant despite rapid technological changes in AI. The key opportunities, challenges, and integration strategies we discuss are anchored in fundamental professional principles and practices that transcend specific model capabilities. This means - we hope - that the document's insights will remain valuable even as frontier models like ChatGPT, Claude, and Gemini continue to evolve. Another point worth noting is that this is not a "research output"; much of what is included is based on discussion and personal experiences of those who contributed to the document. While we will aim to cite sources, this is not an attempt to prove anything.
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