CC BY 4.0Lowagie, Hannes2025-10-192025-10-192025-10https://www.ifla.org/events/artificial-intelligence-bibliographic-control-and-legal-matters-navigating-new-horizons/https://2025.ifla.org/bibliography-section-with-the-information-technology-section-and-the-ifla-artificial-intelligence-special-interest-group/https://wlic2025.astanait.edu.kz/https://repository.ifla.org/handle/20.500.14598/6855This presentation introduces a pioneering approach to modernizing cataloguing practices through the transformation of cataloguing guidelines into a fully machine-readable format, aiming to contribute meaningfully to the long-term vision of Universal Bibliographic Control (UBC). In an era where AI technologies, particularly generative AI, are rapidly reshaping information management, this project reimagines how local cataloguing rules can be authored, maintained, and deployed. We present a real-world implementation from KBR, the national library of Belgium, which has progressed through several stages: from printed cataloguing manuals, to PDFs, to static HTML, and finally to a dynamic HTML interface that fetches and renders data from a structured machine-readable file, in this case a JSON file. This JSON serves as the backbone of our cataloguing guidelines. Uniquely, this same JSON is sent as a prompt input to generative AI tools to ensure that the AI adheres to our institution's specific cataloguing rules, establishing a triangular relationship: JSON as the core schema, that can be used to generate a HTML for the human cataloguer, and that van also be sent to an AI prompt input, ensuring consistency across both human-readable and machine-readable platforms. This proposal fits those two subtopics : 1. AI and Metadata: Our model directly enhances metadata creation and workflows by making cataloguing rules interoperable with AI tools. This streamlines operations and minimizes human error. 2. Generative AI Outputs: Our structured, prompt-ready rule set allows generative AI to produce cataloguing outputs that are both compliant and aligned with institutional standards, resolving bibliographic inconsistencies at scale. We conclude with a call to action: if every institution transforms its rules into machine-readable formats, we open the path to interoperability, and to the unification of cataloguing practices. True Universal Bibliographic Control is no longer just about standardization — it is about convergence of logic and content. (presented on 15 August 2025 at "Metadata's New Frontiers: AI-Driven Systems and Standards" session)enghttps://creativecommons.org/licenses/by/4.0Artificial intelligenceCataloguing standardsBibliographic controlAutomationMetadataInteroperabilityEvents MaterialInternational of Library Associations and Institutions (IFLA)