# Patient perceptions of artificial intelligence integration in dermatology: a cross-sectional study of trust, comfort and equity across multiple care modalities

## TL;DR

Patients prefer AI as a tool with dermatologists rather than alone, especially for serious concerns, and show lower trust in AI among Black patients and those with darker skin tones.

## Contribution

This study reveals patient preferences and equity concerns in AI integration across different dermatology care modalities.

## Key findings

- Patients strongly prefer dermatologist-guided AI over standalone AI apps, with 73.8% trusting the former and only 1.5% trusting the latter.
- Black patients and those with darker skin tones reported significantly lower acceptance of AI-assisted care.
- In-person visits showed dramatically higher odds of patient comfort compared with AI apps alone for new and serious concerns.

## Abstract

Artificial intelligence (AI) and telemedicine are rapidly changing the way dermatological care is delivered. As these tools are increasingly used in tandem, understanding how patients perceive the integration of AI across different care settings is important for responsible implementation.

To assess patient perceptions of AI in dermatology across five care modalities and examine how demographic factors influence acceptance.

A cross-sectional survey was conducted among 130 adults at a US academic dermatology clinic between December 2024 and April 2025. Participants rated trust, comfort, perceived quality, privacy and confidence in equitable performance across three AI-involved modalities: standalone AI apps, AI-assisted in-person visits and AI-assisted telemedicine visits. Differences in perception outcomes across the three care modalities were analysed using repeated measures Anova. Logistic and linear regressions analysed predictors of acceptance, including age, race, skin tone, socioeconomic status, rurality and technology experience.

Patients strongly preferred dermatologist-involved care over standalone AI, with 73.8% trusting dermatologist-guided AI and only 1.5% trusting AI apps alone. Comfort and perceptions of equal performance across skin tones were significantly higher for telemedicine and AI-assisted visits compared with AI apps (P < 0.001). Darker skin tone and Black race predicted lower acceptance of AI-assisted care (P = 0.01 and P = 0.003, respectively), while greater technology familiarity predicted higher acceptance (P = 0.05). Comfort varied by clinical scenario, with in-person visits showing dramatically higher odds of patient comfort compared with AI apps alone [odds ratio (OR) 232.8 for new concerns, OR 137.3 for serious concerns, OR 18.4 for sensitive concerns]. AI-assisted in-person visits also showed significantly higher odds of comfort over AI apps (OR 18.4 for serious concerns, OR 3.6 for ongoing concerns).

Patients strongly prefer AI as clinical support systems rather than autonomous decision-makers, especially for high-stakes and sensitive concerns. Differences in acceptance by race and skin tone point to the need for better representation in datasets and clearer communication about how these tools perform. Moving forward, development and implementation should emphasize clinician and patient involvement, fairness and patient choice to ensure AI is integrated into dermatology in a way that earns patient trust.

Artificial intelligence (AI) is entering dermatology in many forms, from standalone apps to AI-assisted in-person and telemedicine visits. This study surveyed 130 adults in an academic dermatology clinic to explore how patients perceive trust, comfort, quality and fairness across these formats. Interestingly, patients rated AI-assisted visits highest in perceived quality, yet they were most comfortable and trusting with dermatologist-led care. Patients strongly preferred dermatologist-involved care over AI alone, especially for new, serious or sensitive skin concerns. The odds of preferring in-person care over AI apps were more than 200 times higher for new conditions. While greater technology experience predicted higher acceptance, Black patients and those with darker skin tones reported significantly lower acceptance of AI-assisted care, raising concerns about equity and representation. Across all scenarios, human involvement remained key to patient comfort and trust. This study provides basis and guidance for how to develop and integrate AI into dermatologic care in ways that centre on patient preferences, transparency and fairness.