Track Co-Chairs
Jochen Scheeg, Brandenburg University of Applied Sciences, Germany
Kai Riemer, The University of Sydney Business School, Australia
Rebecca Downes, Victoria University of Wellington, New Zealand
Shane Lee, University of Technology Sydney, Australia
Track Description
Artificial intelligence represents a novel form of computing that is increasingly infused into information systems and organisational life. Yet the gap between AI capability and AI usability is rarely closed by technology alone. Between an AI system and its productive use in a real organisational setting lies a layer of practical work that is rarely theorised: data must be located, cleaned, and made fit for purpose; workflows must be assembled around AI outputs; those outputs must be verified, explained, and defended to colleagues, clients, or regulators; and use must be reconciled with approval processes, role boundaries, access restrictions, and budget realities.
This track is focused on the practical organisational work required to make AI usable, governable, and accountable in real settings. We seek empirical contributions that surface the invisible labour generated by sociotechnical constraints across the full cycle of AI use in practice: from information and data preparation through workflow assembly, output verification, governance, explanation, and ongoing support around AI and its outputs in use.
We welcome contributions examining: workarounds and improvisations in AI-infused work processes; invisible and affective labour in AI implementation and use; the role of approval processes, access restrictions, role boundaries, and resource constraints in making AI workable in practice; governance, accountability, and explainability as lived organisational practice; sociotechnical friction and breakdown in human-AI collaboration; and the reconfiguration of expertise, responsibility, and professional identity in AI-mediated work; Diverse empirical approaches are encouraged, including qualitative, quantitative, mixed-methods, interpretive, and critical research grounded in the situated realities of AI in organisational practice.