Toward Culturalized Generative AI for the Creative and Cultural Industries: Lessons from Adaptive Cultural Mediation

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This paper argues that contemporary generative AI systems are not yet consistently equipped to provide the level of culturalization required in the creative and cultural industries (CCIs). Debates on generative AI in cultural domains have focused primarily on productivity, innovation, intellectual property, labor disruption and bias. While these concerns are important, they do not fully capture a more basic issue: cultural production depends on forms of meaning that are historically situated, socially mediated and unevenly distributed across languages, communities and markets. In such contexts, fluency, safety and technical usefulness are not sufficient measures of system quality. The paper discusses how an existing line of thought from localization, cross-cultural design and culturalization research should be carried into the era of generative AI as explicit attention to cultural context, symbolic meaning and interpretive plurality. The CCIs provide a particularly revealing testbed for this claim because they expose limitations of generic AI evaluation in domains where value depends on tone, memory, symbolism and representation. The argument combines published evidence on cultural bias and uneven representation in contemporary models with diagnostic case studies using ChatGPT 5.5 in museums, heritage sites and pilgrimage contexts. These studies illustrate concrete cultural-mediation problems under the conditions tested. On that basis, the article proposes a framework for culturalized generative AI and outlines an integrated research and governance agenda spanning AI, the humanities and cultural-sector practice.