Lodovico, Chiara DiBertolino, AriannaSpallazzo, DavideBollati, IlariaCappellini, GretaCampana, StefanoFerdani, DanieleGraf, HolgerGuidi, GabrieleHegarty, ZackaryPescarin, SofiaRemondino, Fabio2025-09-052025-09-052025978-3-03868-277-6https://doi.org/10.2312/dh.20253189https://diglib.eg.org/handle/10.2312/dh20253189Social media-based trend identification platforms powered by Artificial Intelligence (AI) are gaining considerable attention from scholars and industry professionals alike. These platforms analyze large amounts of user-generated data, identify the emergence and evolution of practices, and support data-driven decision-making. Although automatic trend analysis is growing, limited attention has focused on developing platforms that target digital transformation practices in Intangible Cultural Heritage (ICH). This paper introduces the development process behind ICH Atlas, a digital platform that displays and enables dynamic navigation of emerging trends connected to ICH-related professional roles, skills, and digital technologies and their expected growth based on global trends. The platform was the result of nine-month remote collaboration between a university-based design research group with expertise in cultural heritage and a trend forecasting company specializing in artificial intelligence (AI) and big data analytics. Based on a qualitative analysis of meeting records, email correspondence, datasets, and platform prototypes, the paper outlines the platform's iterations. We trace the decision-making process development, encountered challenges, and coping strategies. Based on our reflections, we identify three tensions that might be of interest for industry-academia initiatives in the intangible cultural heritage sector: scaffolding vs ambiguity, interpretation vs granularity of data, tacit vs explicit knowledge.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Information extraction; Human-centered computing → Collaborative and social computing systems and toolsComputing methodologies → Information extractionHuman centered computing → Collaborative and social computing systems and tools10.2312/dh.2025318910 pages