The arrival of AI and machine learning in the archiving world implies a reconceptualization of archival institutions from consisting of archives as records to be read towards archives as data to be mined. This thesis aims to survey and analyse the arrival of AI and machine learning within the Swedish archival sector.

Through the analyses of four archival institutions and semi-structured interviews with archive professionals, this study illuminates the current state of AI in the Swedish archival sector, opportunities and obstacles of AI implementations, and the impact of AI on the Swedish archival profession. Swedish archival institutions have interest in and expectations of AI implementation. Yet, the current level of AI implementation is generally on experimental instead of an operational level. The findings show that collaboration and knowledge exchange are key drivers to accelerate the implementation of AI in the archival sector. The study concludes with practical rec-ommendations for archival institutions and archive professionals.