Museums and heritage sites increasingly serve highly diverse, multicultural audiences, but most digital storytelling and exhibition content is still designed for a single, generic visitor. Existing adaptive content pilots tend to be one-off installations rather than transferable practice, accessibility for visitors with sensory impairments is usually bolted on rather than designed in, and museum professionals lack a practical, tested toolkit for adapting narratives to different cultural backgrounds, languages, and accessibility needs — especially within the resource constraints most public heritage institutions operate under.
In this context, the EU-funded ADAPTECH project will build a toolkit and technological framework for adaptive, inclusive heritage storytelling. It has two main components: an audience-and-ethics foundation, combining comparative studies of multicultural museum visitors with a responsible-AI framework addressing bias in adaptive content, and an XR and GenAI system that turns this evidence into practice — immersive, audience-responsive environments paired with GenAI pipelines that generate and dynamically adapt narrative, image, video, and 3D content to different visitor profiles. Together these feed a practical adaptation and accessibility toolkit of guidelines, decision frameworks, and content templates for curators and heritage professionals.
The toolkit is co-designed and validated through workshops and site-based pilots across Spanish, Italian, and Greek collections, testing its transferability across different heritage contexts and stress-testing it against the real operational and resource constraints of public museums, so the final outputs are actionable for practitioners rather than only for researchers.
