How AI Shapes the Cultural Tourism Visitor Experience: A Scoping Review with a Personalisation Lens
Authors: Ferraris, C., Tomczyk, A., Splendido, D.
Conference: Enter26
Dates: 28/01/2026
Publication Date: 31/03/2026
Abstract:This scoping review maps how artificial intelligence, particularly large language models (LLMs) and adjacent modalities, influence the cultural tourism visitor experience through personalisation. Following Arksey and O’Malley’s PRISMA-ScR reporting guidelines, searches were conducted in Scopus and Google Scholar (2015–2024), yielding 610 records, of which 18 studies were retained after screening. The analysis identifies a layered “personalisation stack” comprising conversational guidance (LLM pilots), knowledge-graph storytelling, behaviour-aware recommenders, telemetry-informed orchestration, and immersive/assistive media. Reported benefits cluster around engagement, perceived relevance, comfort in VR, and progress towards accessibility. However, value is contingent on governance, autonomy calibration, spatial/crowding effects, and explainability. Evidence gaps include longitudinal evaluation, multimodal LLM integration with knowledge graphs and sensor streams, accuracy/bias auditing, privacy-by-design, and performance reporting for real-time operation. The paper synthesises theoretical, managerial, and policy implications and outlines a practice-oriented checklist. Overall, the findings clarify how AI shapes cultural visitor experiences and the safeguards required to deliver equitable value at scale.
https://eprints.bournemouth.ac.uk/41777/
Source: Manual