Abstract
Research on Generative Artificial Intelligence (GenAI) implementation often overlooks the hidden, politically charged labour required to make it functional. This paper provides an insider's account of the sociotechnical friction arising when institutional goals conflict with the technical limitations of Large Language Models (LLMs). Through analytic autoethnography, this study examines a workaround developed to navigate not only technical constraints but also organisational politics. Drawing on Alter’s (214) theory, the analysis interprets the necessary “articulation work” as “invisible labour,” arguing such workarounds are acts of sociotechnical integration, not deviations. This integration, however, creates a paradox where workarounds for “unfinished” systems form “shadow” systems that obscure this crucial labour. The findings suggest this invisible political labour is an important, rather than peripheral, component of how GenAI becomes functional in practice.
Recommended Citation
Lee, Shang Chieh; Kocaballi, Baki; Narayan, Bhuva; Shum, Simon Buckingham; and Ng, Stella, "Making AI Functional with Workarounds: An Insider’s Account
of Invisible Labour in Organisational Politics" (2025). ACIS 2025 Proceedings. 73.
https://aisel.aisnet.org/acis2025/73