Reframing Bibliographic Control in the Age of Generative AI: Toward Inclusive Metadata Policies and Practices

Abstract

The integration of Artificial Intelligence (AI) and, more recently, generative AI into library and information science practices has catalyzed a paradigm shift in how bibliographic control, metadata creation, and legal deposit are conceptualized and operationalized. This study examines the multifaceted implications of generative AI on bibliographic practices with a specific focus on national bibliographies, metadata schemas, and policy frameworks. Drawing from the emerging experiences of national and academic libraries in the Arab Gulf region, particularly Oman, this study presents a hybrid analytical model that rethinks metadata policies in light of the increasing production of AI-generated content.

The study highlights three key areas of transformation: (1) the reconceptualization of metadata to accommodate non-human authorship and novel forms of digital content, (2) the ethical and legal ambiguities surrounding copyright, authorship, and the inclusion of AI-generated works in national bibliographic repositories, and (3) the evolving role of information professionals whose skills and responsibilities must adapt to new AI-assisted workflows. Through case-based policy analysis and comparative examples, the study advocates for the development of inclusive national frameworks that recognize the cultural and informational value of generative AI outputs, while maintaining bibliographic integrity and legal compliance.

Ultimately, this study contributes to the global...