Mobile app interactions dominate user engagement, with 94% occurring through apps rather than browsers, making the optimization of the app experience vital for business success. However, maintaining visual consistency across various devices and operating systems is challenging for development teams due to issues like misaligned layouts and incorrect fonts, which can drive users away. Traditional UI testing methods, such as manual inspection and snapshot-based regression testing, are inadequate for addressing these challenges, leading to the rise of AI-powered visual testing. Luciq, after extensive development, has tackled three main hurdles: the fragmentation of device and OS variations, the high rate of false positives due to misinterpreted design choices, and the infinite variations of UI inconsistencies. Solutions include refining AI models with high-quality, purpose-built datasets, balancing data needs with privacy concerns, and ensuring the AI is trained across platforms like iOS and Android. Future developments aim to improve efficiency by potentially running AI models directly on client devices, thus enhancing real-time anomaly detection and maintaining user privacy.