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Agentic AI in Dermatology: A Call to Action
Brian Chu1, Heather Shen2, Ivy Lee3
1Department of Dermatology, Brown University, 593 Eddy St, APC 10th Floor, Providence, RI, 02903, United States, 1 4014447959.
JMIR Dermatology
|June 5, 2026
Summary
Agentic artificial intelligence (AI) systems offer autonomous capabilities in healthcare, with dermatology poised for significant benefits. A proposed risk framework aims to guide the safe and equitable adoption of these advanced AI tools.
Area of Science:
- Medical Informatics
- Artificial Intelligence in Healthcare
Background:
- Artificial intelligence (AI) is evolving from passive tools to proactive, agentic systems capable of autonomous actions.
- These agentic AI systems can gather information, execute tasks, and collaborate without constant human prompting.
- Early healthcare adoption shows feasibility across specialties, with dermatology being a prime candidate due to high patient volumes and administrative burdens.
Purpose of the Study:
- To propose a risk-stratification framework for the responsible adoption of agentic AI in clinical settings.
- To identify key barriers hindering the widespread implementation of agentic AI in healthcare.
Main Methods:
- Development of a risk-stratification framework based on clinical risk and task reversibility.
- Analysis of current limitations and challenges for agentic AI adoption in healthcare.
Main Results:
- Agentic AI systems demonstrate potential for autonomous, multi-step actions in healthcare settings.
- Dermatology's workflows are well-suited for agentic AI integration.
- A framework for risk stratification and identification of adoption barriers are presented.
Conclusions:
- Agentic AI offers significant potential to enhance healthcare, particularly in dermatology.
- Addressing limitations in reliability, interoperability, liability, privacy, and regulation is crucial for widespread adoption.
- Proactive engagement by dermatologists is essential for the safe, equitable, and value-aligned development of agentic AI.
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