AI Tools in Dermatology: Practical Uses, Risks, and Guiding Principles

Conclusions

• Current AI tools in dermatology are already useful for streamlining administrative work, patient communication, documentation, education, and research.
• AI scribes and similar workflow tools appear to reduce clinician burden and may improve well-being, with early studies suggesting modest daily time savings.
• NotebookLM-style systems can effectively transform source documents into helpful educational outputs such as summaries, podcasts, mind maps, quizzes, infographics, and slide decks.
• Prompt quality matters, and effective use of generative AI requires clear goals, output formats, warnings, and context.
• Medical education can be enhanced by using AI to create study aids, practice difficult conversations, and organize complex topics for learners.
• Deep research tools can accelerate literature review and topic exploration, but their outputs still require human review and refinement.
• Consumer-facing AI medical advice tools may be appealing, but current evidence and security testing suggest important safety and reliability concerns.
• Even when AI cites references, its answers can be wrong or mis-cited, so clinicians must verify AI-generated information against primary sources.
• AI should be used as an augmenting tool rather than a replacement for clinical judgment, because current systems can still hallucinate or provide unsafe guidance.
• Guiding principles for dermatology AI use should prioritize safety, privacy, fairness, and generalizability.
• The overall conclusion is that AI is promising and immediately useful in dermatology, but it must be adopted cautiously and with strong human oversight.