This study explores the emotional responses of museum visitors to AI-curated exhibits, utilizing data collected from online reviews, surveys, and interviews. The aim was to capture the multidimensional nature of these responses, which were then analyzed using the BERTopic topic modeling method. This approach effectively identified recurring emotional themes in visitor feedback, classifying responses as positive, negative, neutral, or complex. Results reveal significant emotional diversity among visitors. Many expressed curiosity and amazement, often tied to their interest in and appreciation of innovative technology. Conversely, some visitors reported feelings of detachment or skepticism, particularly when AI curation lacked the emotional depth and cultural resonance typically associated with human curation. Emotional reactions were further influenced by factors such as visitors’ familiarity with AI, cultural backgrounds, and their expectations of museum experiences. These insights underscore the importance of understanding audience emotions to enhance the design and implementation of AI-curation strategies. By addressing visitors’ diverse emotional needs, museums can optimize AI-driven exhibitions to create more engaging and meaningful experiences. The findings offer valuable feedback for the cultural sector, providing practical and theoretical guidance for integrating AI into museum curation to better connect with diverse audiences.