The fast integration of artificial intelligence into mobile applications has completely changed the digital landscape; however, the impact of this change on user perception of AI features remains poorly understood. This large-scale analysis examined 1,484,633 mobile application reviews across 422 applications (200 AI-featuring, 222 control) from iOS App Store and Google Play Store. By employing sentiment classification, topic modeling, and concern-benefit categorization, we identified a major disconnect: only 11.9% of reviews mentioned AI, even though 47.4% of applications featured AI capabilities. AI-featuring applications received significantly lower ratings than traditional applications (d = 0.40); however, hierarchical regression revealed a hidden pattern - the negative relationship reversed after controlling for AI mentions and review characteristics (b = 0.405, p < .001). Privacy dominated user concerns (34.8% of concern-expressing reviews), while efficiency represented the primary benefit (42.3%). Effects varied greatly by category, from positive for Assistant applications (d = 0.55) to negative for Entertainment (d = -0.23). These findings suggest that AI features often operate below user awareness thresholds, and it is the explicit recognition of AI, rather than its mere presence, that drives negative evaluations. This challenges basic assumptions about technology acceptance in AI systems.

翻译：人工智能在移动应用中的快速集成已彻底改变了数字景观；然而，这种变化对用户感知AI功能的影响仍鲜为人知。这项大规模分析检查了来自iOS应用商店和Google Play商店的422个应用程序（200个含AI功能，222个控制组）的1,484,633条应用评论。通过采用情感分类、主题建模和担忧-收益分类方法，我们发现了一个重大脱节：尽管47.4%的应用程序具备AI功能，但仅有11.9%的评论提及AI。含AI功能的应用程序获得的评分显著低于传统应用程序（d = 0.40）；然而，分层回归揭示了一个隐藏模式——在控制AI提及和评论特征后，负面关系发生了逆转（b = 0.405, p < .001）。隐私问题主导了用户担忧（占表达担忧评论的34.8%），而效率提升则是主要收益（42.3%）。不同应用类别的影响差异显著：从助手类应用的正面效应（d = 0.55）到娱乐类应用的负面效应（d = -0.23）。这些发现表明，AI功能常常在用户意识阈值之下运行，正是对AI的明确认知（而非其单纯存在）驱动了负面评价。这对AI系统技术接受度的基本假设提出了挑战。