Paper Number
ECIS2026-2558
Paper Type
SP
Abstract
The development and deployment of AI in real-world hospital settings remain limited, with data-related challenges being a major barrier. This paper explores these challenges as ‘frictions’, points of tension between data-dependent AI technologies and the existing sociotechnical installed base of healthcare. Based on 18 interviews with 14 experts in the Norwegian healthcare sector, we examine which data-related frictions arise during the data lifecycle in in-house AI development and how they shape AI implementation in public hospitals in Norway. Our findings highlight significant frictions, including challenges in data generation and access, the extensive work to ensure data quality and compatibility, and difficulties in utilising data for model development and integration. The paper contributes an empirical mapping of these frictions, offering a more detailed picture of how data-related challenges are shaped by current sociotechnical contexts.
Recommended Citation
Soetens, Esli; Kannelønning, Mari; and Grisot, Miria, "Data-Related Frictions In AI Development In Norwegian Hospitals" (2026). ECIS 2026 Proceedings. 19.
https://aisel.aisnet.org/ecis2026/hit/hit/19
Data-Related Frictions In AI Development In Norwegian Hospitals
The development and deployment of AI in real-world hospital settings remain limited, with data-related challenges being a major barrier. This paper explores these challenges as ‘frictions’, points of tension between data-dependent AI technologies and the existing sociotechnical installed base of healthcare. Based on 18 interviews with 14 experts in the Norwegian healthcare sector, we examine which data-related frictions arise during the data lifecycle in in-house AI development and how they shape AI implementation in public hospitals in Norway. Our findings highlight significant frictions, including challenges in data generation and access, the extensive work to ensure data quality and compatibility, and difficulties in utilising data for model development and integration. The paper contributes an empirical mapping of these frictions, offering a more detailed picture of how data-related challenges are shaped by current sociotechnical contexts.
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