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Exploring AI-in-the-making: Sociomaterial genealogies of AI performativity

Susan Scott & Wanda J. Orlikowski

Information and Organization2025https://doi.org/10.1016/j.infoandorg.2025.100558article
AJG 3ABDC A*
Weight
0.66

Abstract

Recent interest in artificial intelligence technologies has led to much discussion about what the age of AI portends for how we live and work. And specifically for the present discussion, what it means for agency. In offering our contributions to these considerations, we build on approaches to treat AI not as a “thing” but as phenomena in-the-making. Such a framing orients us to doings, to practices, to enactments, and consequential outcomes. These considerations of AI-in-the-making are inspired by agential realism, a theory that calls attention to performativity and accountability. Based on these ideas, we propose a sociomaterial genealogical approach that we suggest is well-suited for the study of AI-in-the-making. In so doing, we provide qualitative scholars with a way of orienting their inquiries toward the performativity of ongoing AI reconfigurations and sociomaterial accountabilities. • Proposes treating AI not as a ‘thing’ but as phenomena in-the-making. • Offers a performative account of agency inspired by agential realism. • Outlines a sociomaterial genealogical approach for studying AI-in-the-making. • Discusses concerns surrounding responsibility and ethics of AI.

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https://doi.org/https://doi.org/10.1016/j.infoandorg.2025.100558

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@article{susan2025,
  title        = {{Exploring AI-in-the-making: Sociomaterial genealogies of AI performativity}},
  author       = {Susan Scott & Wanda J. Orlikowski},
  journal      = {Information and Organization},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.infoandorg.2025.100558},
}

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Exploring AI-in-the-making: Sociomaterial genealogies of AI performativity

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Evidence weight

0.66

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.71 × 0.4 = 0.29
M · momentum1.00 × 0.15 = 0.15
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.