Experts See Promise in AI for Atopic Dermatitis Care

The rapid advancement of artificial intelligence (AI) technologies has sparked considerable interest across numerous medical disciplines, including dermatology. One of the chronic conditions poised to benefit from AI innovations is atopic dermatitis (AD), a complex inflammatory skin disease that imposes significant burdens on patients and healthcare systems worldwide.¹ A recent multicenter survey conducted among dermatology and related health care professionals offers valuable insights into the perceptions, potential benefits, and perceived risks associated with incorporating AI into AD care, with an emphasis on therapeutic patient education (TPE).²

Methodology

The survey, distributed electronically, comprised 9 questions covering areas such as perceived benefits, risks, and implementation readiness. Out of 90 members approached, 38 responded, including 33 dermatologists (87%) and 5 other health care professionals. Most respondents practiced in hospital settings (84%), with a minority in private practice, and a significant proportion employed therapeutic action plans (87%) and patient follow-up tools (90%). Notably, 79% reported engaging in shared decision-making, underscoring a progressive approach to patient-centered care.

Findings

The survey revealed a generally optimistic attitude toward AI's role in AD management. An impressive 86% of respondents believed that AI could facilitate better patient–clinician interaction, while over 90% agreed that AI could assist in preparing for consultations, enhancing efficiency and clinician preparedness. Many respondents also recognized AI's potential in predicting disease flares and offering personalized responses—key aspects of proactive, tailored care.

As one respondent highlighted, "AI could serve as a valuable adjunct to enhance patient engagement and support individualized management plans." This sentiment underscores the perceived capacity of AI tools to supplement clinician efforts without replacing human judgment.

Concerns and Cautionary Notes

Despite the enthusiasm, respondents expressed notable concerns about the risks associated with AI integration. A predominant worry (reported by 90.6%) was that patients might receive inaccurate answers from AI tools, which could compromise safety. Additionally, 75% were concerned about the possibility of AI providing dangerous responses that could lead to adverse outcomes if unchecked.

Other apprehensions included the potential for AI to increase patient confusion, with 66.7% fearing that AI could lead to more questions or misunderstandings. Moreover, ethical and trust issues surfaced, particularly regarding misinformation and the erosion of clinician authority. As one expert stated:

“While AI has exciting potential, we must exercise caution to prevent misinformation and maintain trust in the clinician-patient relationship.”

Risks Versus Benefits

The survey underscores the need for caution in AI's deployment in clinical settings. As the authors note, "While enthusiasm for AI in AD care is clear, respondents highlighted important risks. Concerns about misinformation, patient confusion, and erosion of clinician authority underscore the need for caution." They emphasize that different AI applications, such as chatbots, predictive algorithms, and educational tools, have varied roles and safety considerations. Each modality warrants specific validation and safeguards before routine use.

Limitations and Future Directions

The study's limitations include a modest sample size and potential selection bias, given the response rate of 42%. Demographic data such as age or prior AI experience were not collected, restricting deeper subgroup analysis. Nevertheless, the participants represented an experienced, international group of specialists whose perspectives offer valuable early insights into AI's prospects in AD management.

Study Background and Rationale

Therapeutic patient education is pivotal in managing chronic conditions like AD, where long-term adherence to treatment plans greatly influences outcomes. However, access to structured educational programs such as "atopy schools" remains limited, especially in resource-constrained regions. Digital health innovations, including AI-powered tools, present an intriguing solution. They could bridge gaps by providing accessible, personalized education and support at scale. Yet, integrating such technologies necessitates understanding provider attitudes, readiness for adoption, and reservations regarding safety and efficacy.

Conclusions and Clinical Implications

Health care professionals acknowledge AI's potential to revolutionize AD management by enhancing patient education, supporting proactive care, and facilitating shared decision-making. However, they also emphasize the importance of developing transparent guidelines, clinician training, and robust validation to minimize risks. As the authors conclude, "Moving forward, targeted training for clinicians is essential, alongside transparent guidelines to ensure AI tools complement rather than replace clinician judgment."

In practice, AI should be viewed as a complementary tool—augmenting but not substituting the nuanced judgment and empathetic engagement of clinicians. Ensuring shared decision-making with patients about AI use is crucial for maintaining trust and optimizing outcomes.

Final Thoughts

As AI continues to evolve, its integration into dermatology and AD care holds promise but must be approached ethically and cautiously. This survey serves as an essential stepping stone, highlighting both the excitement and the reservations among specialists. Future research should focus on evaluating the safety, accuracy, and patient perceptions of AI-driven tools, ultimately aiming to harness their potential to improve patient-centered outcomes in dermatology.

References

1. Jairath N, Pahalyants V, Shah R, Weed J, Carucci JA, Criscito MC. Artificial intelligence in dermatology: A systematic review of its applications in melanoma and keratinocyte carcinoma diagnosis. Dermatol Surg. 2024;50(9):791-798. doi:10.1097/DSS.0000000000004223
2. Stalder J, Aoki V, Aubert H, et al. Perceptions of a group of experts on the integration of artificial intelligence in the management of atopic dermatitis. JEADV Clin Prac. 2025. doi:10.1002/jvc2.70242.