Introduction. Artificial intelligence (AI) technologies have been used in dermatovenerology for several years, primarily for the analysis of dermatoscopic images and the screening of skin growths. However, the attitude of Russian dermatovenerologists to these technologies has not been studied. A feature of the sample in this study is the high proportion of residents, which makes it possible to compare the perception of AI by students and established specialists. Objective. To characterize the attitude of Russian dermatovenerologists towards AI technologies and to determine whether the perception of AI differs between residents and practicing specialists when group sizes are controlled. Materials and methods. Anonymous online survey (Anketolog.ru , March–July 2026), 191 specialists (dermatovenerologists and cosmetologists). The questionnaire consists of 26 questions (two blocks). Subgroup analysis of residents (n = 94) and non-residents (n = 94) in a balanced sample. Mann–Whitney criteria, χ2, Spearman coefficient, cluster analysis. Results. 85.4% of women, average age 34.4 ± 12.1 years. 65.9% are skeptical about trust in AI. The subjective assessment of AI accuracy is a median of 45% (IQR 25-65%), the accuracy of doctors is 75% (IQR 65-85%). Despite the 17-year gap in median age and different digital activity in everyday life, there were no statistically significant differences between residents and practitioners in any indicator of attitudes towards AI (all p > 0.05). Cluster distribution: "Skeptics" 23.2%, "Moderates" 50.3%, "Enthusiasts" 26.5%. Discussion. The proportion of AI users among Russian dermatovenerologists (66.5%) is comparable to international data. The barrier of distrust is formed not by a lack of user experience, but by the lack of validated clinical AI systems in dermatovenerological practice. Conclusion. The digital activity of young professionals does not translate into higher professional confidence in AI. The barrier of distrust is formed not by a lack of user experience, but by the lack of validated clinical AI systems in dermatovenerological practice.