Tracing the Past, Predicting the Future: A Systematic Review of <scp>AI</scp> in Archival Science
ABSTRACT The rapid expansion of content presents significant challenges in records management, notably in retention and disposition, appraisal, and organization. Our study highlights how integrating artificial intelligence (AI) into archival science can help address these issues. We begin with a thorough analysis of 45 papers published between 2011 and 2023 that met our predetermined criteria. All the articles were written in English; 40% of these were reviews, and the remaining 60% were original research articles. We investigated the key AI techniques and their applications in archives and records management functions. Our findings highlight key AI‐driven strategies that promise to streamline recordkeeping processes and improve data retrieval in the immediate future. This review outlines the current state of AI in archival science and records management and lays the groundwork for integrating new techniques to transform archival practices. Our research emphasizes the necessity for enhanced interdisciplinary collaboration between AI experts and archival professionals.
Institutions
- University of British Columbia (CA)
- San Jose State University (US)
Publication Details
- Journal
- Proceedings of the Association for Information Science and Technology
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/pra2.1286
- Citations
- 2
- Primary Topic
- Maritime Transport Emissions and Efficiency
- Type
- article
- Field-Weighted Citation Impact
- 1.60