This research investigates gender norms in the classic Grimm’s fairy tale ‘‘Snow White’’ and its contemporary adaptation, ‘‘Snow White and the Huntsman,’’ utilizing advanced Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques. By meticulously annotating and computationally analyzing textual data, the study identifies nuanced shifts in character dynamics, thematic emphases, and narrative structures between the traditional tale and its modern retelling. The comparative analysis reveals how the original ‘‘Snow White’’ perpetuates stereotypical gender norms, with female characters often depicted as passive and reliant on male saviors [1]. In contrast, the modern adaptation challenges these conventions by portraying empowered female protagonists who exert greater agency and leadership [2]. The study also examines how narrative trajectories and character interactions evolve to reflect changing societal values regarding gender roles. The findings contribute to a deeper understanding of the evolution of gender norms in children’s literature, highlighting the role of contemporary adaptations in reshaping traditional narratives to promote gender equality. Furthermore, the research demonstrates the potential of AI-driven analysis in literary studies, offering a precise and objective approach to exploring complex cultural phenomena. By leveraging AI tools, this study not only enhances the analysis of gender representations in literature but also provides insights into the broader impact of media on social change. This work underscores the importance of revisiting classic tales to create more inclusive and diverse narratives that resonate with modern audiences.