With the rapid development of new technologies, recent advances in Artificial Intelligence (AI) are promoting the growth of the Cultural Heritage field and changing approaches to the design of museum spaces. The museum visitor experience is evolving towards greater user involvement, creating new dynamic and interactive cultural contexts. The design of museum spaces and, in particular, the organisation of visual, spatial and material elements are more oriented toward the needs and expectations of visitors, thus generating an impact on direct involvement and the quality of the visit. In this context, among the tools for capturing user engagement data, facial expression analysis enables the collection of implicit and explicit measures of user activation and emotional engagement in application fields ranging from neuromarketing to user experience. To support this analysis, Artificial Intelligence technology plays a key role through its ability to generate data and algorithms to “reshape” the creative process beyond traditional design methods and tools derived from the study of human perception. This paper proposes a review of the state of the art of the main digital technologies used in museum exhibitions and the identification and detailed study of integrated systems and two methods used for facial emotion recognition during the enjoyment of museum works and spaces through examples and case studies in the literature. Also, the study highlights the importance of facial recognition technology, capable of identifying and classifying different visitor reactions, among the metrics for data collection in the museum field already found in the literature. Moreover, this technology, used in the Cultural Heritage field, is identified as a possible key factor in the construction of guidelines for designing museum spaces in line with current research areas related to the advanced visitor experience in the enjoyment of cultural heritage.