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Abstract

The integration of Artificial Intelligence (AI) in digital archive management has become increasingly important in response to growing demands for efficiency, accessibility, and information preservation in the digital transformation era. This study analyzes the development of research related to this theme through a bibliometric approach based on Scopus data and visualizations using VOSviewer. The results reveal a surge in publications since 2020, driven by accelerated digitalization following the pandemic and the emergence of generative AI technologies such as ChatGPT. Countries such as the United States, China, and the United Kingdom dominate scholarly contributions, although institutions from developing nations like the University of South Africa also play a strategic role. Bibliometric visualizations show that AI serves as a central node closely linked to terms such as digital archives, metadata, sustainability, and ethical technology. Research evolution is shifting from technical focuses toward ethical, social, and sustainability issues. Despite the significant growth in literature, challenges remain, including gaps in global collaboration, the lack of ethical frameworks, and limited technological literacy. This study highlights the importance of interdisciplinary collaboration and the development of equitable digital policies in building sustainable intelligent archival systems.

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Artificial Intelligence Digital Archives Digital Transformation

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Suryaningtyas, A., & Wijaya, T. (2025). Artificial Intelligence and the Digital Transformation of Archival Systems: A Bibliometric Study. Economics and Digital Business Review, 7(1), 149–169. https://doi.org/10.37531/ecotal.v7i1.2906
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References

  1. Ali, W., & Khan, A. Z. (2024). Factors influencing readiness for artificial intelligence: a systematic literature review. Data Science and Management. https://doi.org/10.1016/j.dsm.2024.09.005
  2. Allana, S., Kankanhalli, M., & Dara, R. (n.d.). Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review.
  3. Asser, S. (2022). Spaarnestad: Biography of an Analogue Press Photo Archive. TMG Journal for Media History, 25(1). https://doi.org/10.18146/tmg.818
  4. Colavizza, G., Blanke, T., Jeurgens, C., & Noordegraaf, J. (2022). Archives and AI: An Overview of Current Debates and Future Perspectives. Journal on Computing and Cultural Heritage, 15(1). https://doi.org/10.1145/3479010
  5. Cushing, A. L., & Osti, G. (2022). “So how do we balance all of these needs?”: how the concept of AI technology impacts digital archival expertise. Journal of Documentation, 79(7). https://doi.org/10.1108/JD-08-2022-0170
  6. Darda, K., Carre, M., & Cross, E. (2023). Value attributed to text-based archives generated by artificial intelligence. Royal Society Open Science, 10(2). https://doi.org/10.1098/rsos.220915
  7. Davet, J., Hamidzadeh, B., & Franks, P. (2023). Archivist in the machine: paradata for AI-based automation in the archives. Archival Science, 23(2). https://doi.org/10.1007/s10502-023-09408-8
  8. Dhopte, A., & Bagde, H. (2023). Smart Smile: Revolutionizing Dentistry With Artificial Intelligence. Cureus. https://doi.org/10.7759/cureus.41227
  9. Fewster, K. (2024). Case Study: Developing AI search and retrieval tools to improve archival access using the AvocadoIT email collection. https://docs.google.com/document/d/1UsjkkkGeSJrgCDJGASCAy5q0uo_ZkQpzi_Ch8XUcqYw/edit?usp=
  10. Hernández, R., & Rockembach, M. (2025). Building trustworthy AI solutions: integrating artificial intelligence literacy into records management and archival systems. AI & SOCIETY, 1–18. https://doi.org/10.1007/s00146-025-02194-0
  11. Jaillant, L. (2022). More Data, Less Process: A User-Centered Approach to Email and Born-Digital Archives. American Archivist, 85(2). https://doi.org/10.17723/2327-9702-85.2.533
  12. Jaillant, L., & Caputo, A. (2022). Unlocking digital archives: cross-disciplinary perspectives on AI and born-digital data. AI and Society, 37(3). https://doi.org/10.1007/s00146-021-01367-x
  13. Jaillant, L., & Rees, A. (2023). Applying AI to digital archives: trust, collaboration and shared professional ethics. Digital Scholarship in the Humanities, 38(2). https://doi.org/10.1093/llc/fqac073
  14. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9). https://doi.org/10.1038/s42256-019-0088-2
  15. Modiba, M. (2025). Adoption of artificial intelligence to enhance records management practices at Gauteng Department of Education in South Africa. Collection and Curation, 44(1), 9–17. https://doi.org/10.1108/CC-12-2023-0044
  16. Modiba, M., Ngulube, P., & Marutha, N. (2023). Infrastructure for the implementation of artificial intelligence to support records management at the Council for Scientific and Industrial Research in South Africa. ESARBICA Journal: Journal of the Eastern and Southern Africa Regional Branch of the International Council on Archives, 41. https://doi.org/10.4314/esarjo.v41i.11
  17. Münster, S., Maiwald, F., di Lenardo, I., Henriksson, J., Isaac, A., Graf, M. M., Beck, C., & Oomen, J. (2024). Artificial Intelligence for Digital Heritage Innovation: Setting up a R&D Agenda for Europe. In Heritage (Vol. 7, Issue 2). https://doi.org/10.3390/heritage7020038
  18. Nockels, J., Gooding, P., Ames, S., & Terras, M. (2022). Understanding the application of handwritten text recognition technology in heritage contexts: a systematic review of Transkribus in published research. Archival Science, 22(3). https://doi.org/10.1007/s10502-022-09397-0
  19. Oyighan, D., Ukubeyinje, E. S., David -West, B. T., & Oladokun, B. D. (2024). The Role of AI in Transforming Metadata Management: Insights on Challenges, Opportunities, and Emerging Trends. Asian Journal of Information Science and Technology, 14(2), 20–26. https://doi.org/10.70112/ajist-2024.14.2.4277
  20. Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1). https://doi.org/10.5465/AMR.2018.0072
  21. Sahadevan, S. (2023). Project Management in the Era of Artificial Intelligence. European Journal of Theoretical and Applied Sciences, 1(3). https://doi.org/10.59324/ejtas.2023.1(3).35
  22. Schellnack-Kelly, I., & Modiba, M. (2024). Developing smart archives in society 5.0: Leveraging artificial intelligence for managing audiovisual archives in Africa. Information Development. https://doi.org/10.1177/02666669241286224
  23. Tenzer, M., Pistilli, G., Brandsen, A., & Shenfield, A. (2024). Debating AI in Archaeology: applications, implications, and ethical considerations. Internet Archaeology, 67. https://doi.org/10.11141/ia.67.8
  24. Vivian Ailakhu, U., & Ailakhu, B. (2021). Library and Information Services to the Blind and Visually Impaired: The Role of Academic Libraries in Nigeria. Global Review of Library and Information Science (GRELIS), 17(2).
  25. Wang, H. (2022). Providing public access to archival materials and the problem of fact-checking in the post-truth era. Social Science Quarterly, 103(7). https://doi.org/10.1111/ssqu.13232
  26. Wang, L., Zhang, X., Su, H., & Zhu, J. (2023). A Comprehensive Survey of Continual Learning: Theory, Method and Application. http://arxiv.org/abs/2302.00487
  27. Wang, R., Huang, S., Wang, P., Shi, X., Li, S., Ye, Y., Zhang, W., Shi, L., Zhou, X., & Tang, X. (2024). Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023. Cancer Imaging, 24(1). https://doi.org/10.1186/s40644-024-00737-0
  28. Wilson, C. (2022). Public engagement and AI: A values analysis of national strategies. Government Information Quarterly, 39, 101652. https://doi.org/10.1016/j.giq.2021.101652
  29. Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222. https://doi.org/10.1016/j.knosys.2021.106994