The research aims to establish a comprehensive framework for the integration of artificial intelligence (AI) into the archival value chain for born-digital data, with a particular emphasis on its implementation in the National Library and Archives of the United Arab Emirates. Combining document analysis of pertinent policies and standards with semi-structured interviews with key specialists from five prominent national archives (The National Archives UK, National Archives and Records Administration USA, Library and Archives Canada, National Archives of Australia, and National Library and Archives of the UAE), the research employs a qualitative multi-method approach. Thematic analysis of interview data collected from 10 experts and supporting documents revealed critical challenges in current archival practices for born-digital data, including issues with metadata and context preservation, exponential data growth management, and labour-intensive processes. These findings influenced the development of a novel archival value chain model for born-digital data and a proposed framework for AI integration. Before AI is integrated into the workflow of archives, there is a need for exhaustive regulations, ethical considerations of AI use, metadata standards, and rigorous governance methods at the policy level. In terms of AI integration, the framework proposes the use of AI for the optimisation of long-term preservation of digital archives, automated and intelligent quality control, advanced search and retrieval capabilities powered by AI, AI-driven metadata management, and improved record selection and appraisal. The study contributes to the field of archival science by examining the practical, ethical, and transformative aspects. It offers actionable insights for national archives worldwide, particularly those in emerging digital landscapes such as the UAE, to effectively utilize AI technologies while maintaining archival integrity and addressing evolutionary challenges in digital record management.
| Date of Award | 2025 |
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| Original language | English |
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| Awarding Institution | |
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| Supervisor | Sarah Higgins (Supervisor) & Anoush Simon (Supervisor) |
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- artificial intelligence
- born-digital data
- archival value chain
Integrating Artificial Intelligence in the Archival Value Chain for Born-Digital Data: A Framework for National Libraries and Archives of the UAE
Almteiri, H. A. M. (Author). 2025
Student thesis: Doctoral Thesis › Doctor of Professional Studies