Årg. 25 Nr. 44 (2026): Kunstig Intelligens og sundhed
Originalartikler

Before Deployment: Anticipatory Infrastructuring and Early AI Integration in Acute Stroke-ready MRI Workflow

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  • Maria Bach Nielsen,
  • Tom Børsen,
  • Casper Knudsen
Maria Bach Nielsen
Aalborg Universitet
DOI: https://doi.org/10.7146/tfss.v25i44.156503

Publiceret 2026-06-26

Nøgleord

  • AI-integration,
  • health,
  • decision-support,
  • clinical workflow

Citation/Eksport

Bach Nielsen, M., Børsen, T., & Knudsen, C. (2026). Before Deployment: Anticipatory Infrastructuring and Early AI Integration in Acute Stroke-ready MRI Workflow. Tidsskrift for Forskning I Sygdom Og Samfund, 25(44), 19–47. https://doi.org/10.7146/tfss.v25i44.156503

Copyright (c) 2026 Maria Bach Nielsen, Tom Børsen, Casper Knudsen

Creative Commons License

Dette værk er under følgende licens Creative Commons Navngivelse –Ikke-kommerciel (by-nc).

Resumé

Artificial intelligence (AI) decision support is often framed as a technical response to diagnostic pressure, yet making AI usable in clinical settings depends on anticipatory work that connects new outputs to existing infrastructures, routines, and responsibility relations. This article examines early integration work around Apollo, a commercially available AI-based decision-support system for brain MRI, explored in a Danish acute stroke-ready hospital context as support for triage and attention during image acquisition rather than as diagnostic authority. The analysis draws on longitudinal rapid ethnographic fieldwork (2019–2024), including approximately 60 hours of observation across collaboration meetings, clinical workflow settings, training, and pilot-related sessions; six semi-structured interviews with key stakeholders; and a corpus of project documents. Focusing on pilot and pre-implementation activity, the article traces how clinicians, developers, and institutional actors negotiated what Apollo could be allowed to do, how it could connect to the installed base, and how its outputs could be made visible and timely within established work practices. Conceptually, the article frames these activities as anticipatory infrastructuring: alignment work oriented toward possible future routine use, carried out while attachments and responsibilities remain unsettled. The article contributes an empirically grounded account of anticipatory infrastructuring in early clinical AI integration. It shows how, in pilot and pre-implementation work, actors collectively stabilized a future possibility of use by (1) delimiting scope and legitimacy, (2) stabilizing routability and tempo of data flows, (3) tuning visibility within existing screen ecologies, and (4) negotiating expectations for noticing and responding to algorithmic suggestions.

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