How does the rise of artificial intelligence (AI) affect our physiotherapy skills? 

AI presents a fascinating paradox for physiotherapists— incredible opportunities for advancement alongside potential risks to fundamental clinical abilities. 

Navigating the interplay of upskilling and deskilling, especially in light of AI scribes and other emerging technologies, is essential for every physiotherapist. 

It’s crucial to acknowledge the long-term implications of AI development. 

While we currently focus on AI as a tool to assist our work, the potential for artificial super intelligence—a hypothetical future stage where AI surpasses human intelligence in all aspects— cannot be ignored. 

If we achieve artificial super intelligence in our lifetime, which some leading AI researchers speculate is possible, there’s a risk of us becoming subservient to AI rather than AI working with us as the beneficiaries. 

This underscores the importance of responsible AI development and the need for careful consideration of the ethical and societal implications of these powerful technologies. 

From physiotherapist to AI advocate 

My career began with nearly two decades as a physiotherapist, immersed in hands-on care. 

Driven by a desire to leverage technology for better healthcare, I made a mid-career shift to software engineering. 

One of my first AI projects involved developing CliniScribe AI, an AI-powered scribe designed specifically for allied health, including physiotherapy. 

My aim was to ease the burden of documentation while preserving the crucial element of patient connection—that vital therapeutic alliance we build. 

This experience brought into sharp focus the delicate balance between utilising AI tools and maintaining core physiotherapy skills—a challenge that mirrored my own transition into software development. 

Upskilling versus deskilling 

AI offers a double-edged sword: the potential for both upskilling and deskilling. 

On the one hand, it empowers us with tools for enhanced diagnostics, personalised treatment plans and greater efficiency in our clinics. 

On the other hand, over-reliance can lead to the atrophy of essential abilities like manual palpation, movement analysis and clinical reasoning. 

AI can significantly enhance our skills in several ways: 

• enhanced learning and knowledge access—AI can provide access to the latest research, evidence-based guidelines and expert opinions, tailored to individual learning styles
• simulations and data-driven insights— AI can create realistic virtual environments for practising complex techniques or analysing movement patterns. It can also analyse large datasets of patient outcomes, leading to more effective treatment strategies
• AI-powered support for clinical decision-making—advanced AI assistants can aid in differential diagnosis, treatment planning for complex cases and refining clinical reasoning based on vast amounts of data. 

Over-reliance on AI carries the risk of deskilling, particularly in areas fundamental to our practice. 

This can manifest as a decline in our tactile skills, a reduced ability to accurately assess movement dysfunction and a weakening of our clinical judgement. 

While AI presents risks of deskilling, it also offers the potential to enhance certain aspects of patient interaction. 

For example, by automating note taking, AI can free up physiotherapists to: 

• maintain better eye contact—reducing the need to look down at a notepad or screen can improve patient connection and build rapport, fostering a stronger therapeutic alliance
• focus more on non-verbal cues—with documentation handled by AI, physiotherapists can dedicate more attention to observing patient body language and other non-verbal signals, leading to a more holistic understanding of the patient’s condition. 

This highlights the complex nature of AI’s influence. 

It’s not simply a matter of gain or loss but a shift in focus and skill application within the therapeutic encounter. 

Lessons from handwritten coding 

Physiotherapist and software developer Barry Nguyen.

During my computer science master’s, written coding exams—writing code by hand—proved surprisingly valuable. 

It forced me to slow down, deeply engage with the logic and solidify my understanding of fundamental concepts. 

Similarly, manually taking clinical notes or mapping treatment plans can deepen our engagement with patient care and sharpen our reasoning as physiotherapists. 

Handwritten mind mapping has been invaluable in my software engineering transition. 

Creating visual maps of complex ideas clarifies thinking and reveals connections. 

For physiotherapists, mind mapping can: 

• make it easier to visualise patient care pathways and rehabilitation programs
• synthesise information (eg, clinical notes, research, patient data and outcome measures)
• support teaching and mentoring of students and junior colleagues
• enhance personal learning and recall of anatomy, biomechanics and treatment techniques. 

Contextual AI implementation 

Effective AI implementation requires context. 

For example, when mentoring junior clinicians, AI tools should be used to support learning, not replace it. 

Encourage manual practice and critical thinking alongside AI assistance. 

As far as maintaining cognitive engagement is concerned, even experienced physiotherapists benefit from ‘AI-free’ practice to prevent cognitive atrophy and maintain essential manual and assessment skills. 

A hybrid approach to clinical note taking 

A key strategy for mitigating the risk of deskilling is adopting a hybrid approach to clinical note taking. 

This involves strategically blending AI assistance with manual methods: 

• initial manual notes—begin by taking brief handwritten notes during patient interactions to focus on active listening, observation and palpation findings
• AI-assisted expansion—use AI scribes or transcription tools to expand on these initial notes, capturing more detail and ensuring comprehensive documentation for medico-legal purposes
• manual review and refinement—critically review and edit AIgenerated notes, ensuring accuracy, adding clinical insights based on your physical examination findings and reflecting your professional judgement. 

This hybrid approach allows us to leverage AI’s efficiency while maintaining our core clinical skills and ensuring the quality and accuracy of our documentation. 

Practical tips for navigating the AI landscape in physiotherapy 

To thrive in the long-term, physiotherapists will require: 

• core skills maintenance—regularly engage in manual therapy techniques, movement analysis and other hands-on assessments
• active review and editing—treat AI-generated notes as drafts, comparing them with your clinical reasoning and physical examination findings
• strategic AI use—leverage AI for complex cases, data analysis and brainstorming but always validate its suggestions with your clinical judgement
• handwriting and visual aids—incorporate handwritten notes, diagrams and mind maps, especially for complex cases or when learning new techniques
• customised AI for education—tailor AI tools for students and junior clinicians to prioritise active learning and the development of core clinical skills
• balanced practice—dedicate time each week to traditional handson methods and patient interaction without relying on AI tools
• mind mapping—use mind mapping routinely for treatment planning, learning new concepts and reflecting on clinical practice
• brainstorming prior to using AI—when tackling a complex case or developing a rehabilitation program, try brainstorming solutions and generating ideas without AI assistance first. Then use AI tools to expand on your initial thoughts, explore alternative perspectives and identify potential gaps in your reasoning. This approach ensures that you’re actively engaging your own cognitive abilities before leveraging AI’s capabilities. 

Conclusion 

AI is transforming allied health, including physiotherapy. 

By embracing a balanced approach—prioritising upskilling, maintaining core skills, adopting a hybrid approach to key tasks like note taking and recognising AI’s potential to enhance certain aspects of patient interaction—we can harness its power to improve patient care and clinical outcomes. 

It’s tempting to view AI scribes as a simple solution to documentation overload and mental burnout. 

The immediate benefits of reduced cognitive load can be significant. 

However, while trusting AI to handle the bulk of note taking may seem appealing in the short-term, we must carefully consider the long-term implications. 

The potential for deskilling, as discussed, and erosion of critical thinking skills present a real risk to our professional development and, ultimately, the quality of patient care we provide. 

Crucially, remember that you are the expert clinician. 

You understand your own learning style, your professional learning expectations and the specific needs of your patients. 

You are therefore best positioned to judge how and when to integrate AI tools into your practice. 

AI should serve you, not the other way around. 

As someone who has experienced both sides of the AI equation, I believe that curiosity, adaptability and lifelong learning—coupled with a mindful and clinician-driven approach to AI implementation—are key to thriving in this new era. 

We must not sacrifice long-term competency for short-term convenience. 

>> Barry Nguyen APAM is a digital health adviser at the Australian Digital Health Agency, a physiotherapist, a software engineer and the founder and CEO of CliniScribe AI. Barry was a finalist at the Physiotherapy Research Foundation’s Physio Pitchfest in 2023 with CliniScribe. 

Course of interest:  

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