Clinical supervisors, CF mentors, and university clinic directors face a unique challenge: preparing the next generation of SLPs to use AI responsibly while maintaining academic integrity and developing independent clinical thinking.

Key Considerations

• Students may over-rely on LLMs before developing foundational clinical reasoning
• The line between “AI-assisted” and “AI-dependent” is critical during training
• Academic integrity policies may or may not address AI use in clinical documentation
• CFs need to develop their own clinical voice, not an AI-polished version of one

Red Flags Specific to This Setting

• Students submitting AI-generated reports as their own clinical work
• Using AI to bypass the learning process (writing goals without understanding the rationale)
• CFs relying on AI for clinical decisions that should develop through mentored practice
• Supervisors unable to distinguish student clinical thinking from AI output

Where LLMs Can Help

• Teaching prompt engineering as a clinical skill
• Demonstrating the difference between AI-generated and clinician-authored documentation
• Using AI output as a teaching tool (critique this AI-generated goal)
• Scaffolding clinical writing (use AI to organize, then revise into your own voice)
• Modeling responsible AI disclosure in clinical settings