PILOTING

To ensure a robust and user-centric validation of the platform, the project adopted a standardized qualitative framework:

  • Usability Assessment: Using the System Usability Scale (SUS) to evaluate the interface’s ease of use and complexity.
  • User Satisfaction: Measuring the Net Promoter Score (NPS) to gauge the likelihood of professional adoption.
  • Qualitative Insights: Conducting structured Focus Groups with media professionals to capture deep thematic feedback on workflows and functional gaps.

The three core use cases

The pilots were structured around three fundamental operational scenarios:

  1. Content Distribution: Focusing on expanding the reach of regional media to international audiences through AI-driven multilingual adaptation, including automated subtitling and dubbing.
  2. Content Access and Search: Testing multimodal and cross-node search capabilities to allow journalists and creators to find relevant materials across different archives and languages.
  3. Content Adaptation and Enrichment: Validating automated metadata generation, tagging, and transcription tools to simplify the processing of legacy archives and raw media assets.

Preparation and Data Collection

The transition from development to real-world testing followed a precise operational path:

  • Technical Readiness: Each node environment (servers, connections, and storage capacity) was individually assessed through one-to-one meetings to ensure stability.
  • Localized Feedback Loops: Questionnaires and evaluation tools were translated into the native languages of the participants to remove linguistic barriers during data collection.
  • Centralized Data Management: Results were gathered through digital platforms and processed using a thematic analysis approach, identifying common patterns and operational benefits across different production environments.

General Conclusions

The pilots confirmed that a centralized AI hub can significantly streamline media production by automating repetitive tasks like transcription and metadata enrichment. The platform proved to be a powerful support tool for handling legacy content and facilitating cross-border collaboration within a distributed architecture. Moving forward, MOSAIC establishes a scalable foundation for a more integrated, multilingual European media ecosystem, bridging the gap between traditional broadcasting and modern AI-driven workflows.

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