Sabri Simsek
Journal of Social and Analytical Health - 2026;6(1):1-3
Artificial intelligence (AI) is progressively transforming healthcare systems, yet its integration into physiotherapy education remains limited and inconsistently structured. This discrepancy raises an important concern: while clinical environments are rapidly evolving toward digitalization, educational frameworks may not be adapting at the same pace. In this context, integrating AI into entry-level physiotherapy education should no longer be viewed as a future consideration, but rather as an emerging educational imperative. AI technologies are increasingly being incorporated into patient care, particularly through tools designed to enhance engagement and support behavioral change. For example, AI-based chatbots have shown potential in supporting health-related behavior modification and improving patient interaction (1). More broadly, the emergence of large language models (LLMs) highlights the expanding role of AI in medicine, with possible applications in information synthesis and clinical support (2). Despite these developments, the level of preparedness among physiotherapists appears to remain variable. A cross-sectional study reported heterogeneous knowledge and attitudes toward AI applications, with many professionals indicating limited familiarity and uncertainty regarding their clinical use (3). This situation suggests that current educational programs may not yet fully equip future practitioners to critically engage with these technologies. While AI systems may assist with certain aspects of clinical reasoning, such as information processing and hypothesis generation, their reliability remains subject to ongoing evaluation. Recent research has raised concerns regarding the consistency and trustworthiness of AI-generated clinical reasoning in physiotherapy contexts (4). These findings highlight the importance of developing robust critical appraisal skills when interacting with AI-generated outputs. From an educational perspective, emerging evidence suggests that AI-based approaches may contribute to the development of clinical reasoning skills. A randomized controlled trial reported improvements in clinical reasoning outcomes among physiotherapy students exposed to AI-supported educational interventions (5). However, given the relatively recent nature of this evidence, these findings should be interpreted with caution and warrant further investigation. Clinical reasoning remains a core competency in physiotherapy practice and involves complex processes such as data interpretation, decision-making, and patient-centered communication. In this context, AI should be considered a complementary tool rather than a substitute for professional judgment. Nevertheless, insufficient exposure to AI during training may risk producing graduates who are not fully prepared to navigate increasingly digitalized clinical environments. This perspective is reinforced by clinical educators at HESAV Lausanne, who note that a thoughtful and critical integration of AI into practice could foster greater practitioner autonomy and improved care quality, provided that physiotherapists (6). Accordingly, the integration of AI into physiotherapy education should extend beyond basic technical exposure. It may include the development of digital literacy, ethical awareness, and advanced critical thinking skills. Students could benefit from structured learning experiences that enable them to understand the capabilities and limitations of AI systems, critically evaluate their outputs, and integrate them appropriately into clinical reasoning processes. As a physiotherapy student in Switzerland, I have observed during my clinical placements that digital tools and data-driven approaches are progressively being incorporated into routine practice. However, structured training in AI remains limited, often requiring students to explore these technologies independently. This observation reflects a broader gap between technological innovation and formal education, which may become increasingly problematic if not addressed. A structured and progressive integration of AI into physiotherapy curricula could therefore be considered. This may involve foundational teaching on AI concepts, practical exposure to clinical applications, and reflective discussions addressing ethical and professional considerations. Such an approach may help ensure that future physiotherapists are not only competent users of emerging technologies but also critical and responsible practitioners. In conclusion, AI represents both a potential opportunity and a significant challenge for physiotherapy education. While its applications continue to expand in clinical practice, its integration into educational programs remains uneven. Addressing this gap at the curricular level appears essential to better align training with the realities of modern healthcare. Without such efforts, there is a risk that future practitioners may be insufficiently prepared for the evolving demands of their profession.
