Support of Google Gemini in Cataloguing Audiovisual Archival Materials

Purpose: This article aims to present the use of the generative tool Google Gemini in cataloguing audiovisual archival materials.Methodology: Iterative approach, including segmented submission of contributions, precise instructions, and continuous verification. The study covers daily news programs, music shows, and sessions of the National Assembly.Results: Google Gemini enables accelerated and standardized cataloguing, improves record transparency, and supports content classification, while requiring ongoing professional supervision and corrections.Conclusion: The combination of generative AI models and archival expertise allows efficient digitization and streamlining of audiovisual archival cataloguing.