This study investigates how user perception and recognition of Artificial Intelligence (AI) shape experiences with AI-based User Interfaces (UIs). Addressing critical gaps in understanding user awareness and interaction with AI-driven systems, the research examines the relationship between users’ awareness of AI functionality and the problems they encounter. An online survey (n = 386) was conducted in English and German to capture cross-linguistic insights into user experience (UX) with AI-enabled software, applications, and websites. Data were analyzed using a 3×3 matrix framework, mapping perception of AI use against reported interaction problems. Results show that only 25% of users could reliably identify AI usage, 47% were unaware, and 28% were uncertain. A statistically significant positive correlation was found between perceived usefulness and problem frequency (r = 0.299, p < 0.001), suggesting that users who view AI-based UIs as more valuable are more likely to report issues—potentially due to higher engagement, greater expectations, or willingness to tolerate flaws for perceived benefit. As the study is correlational, no causal inferences are warranted. Qualitative feedback from users who encountered problems reveals recurring challenges, including inaccurate or unhelpful responses, slow performance, privacy concerns, and inappropriate outputs. These findings provide actionable insights for UX practitioners, emphasizing the need for transparent, trustworthy, and usable AI-based UIs that prioritize system performance, accuracy, and privacy.