In the dynamic realm of Artificial Intelligence (AI), transitioning from research to production is a pivotal phase, where Quality Assurance (QA) plays a vital role in ensuring the seamless adaptation of AI models to real-world applications. This article explores the challenges of this transition, emphasizing the need for a robust QA process.