Abstract
Generative AI (GenAI) is reshaping knowledge-intensive work by automating routine tasks and reallocating employees’ time and cognitive effort. While these tools promise efficiency and creativity gains, their benefits are not necessarily equally shared. This study examines how configurations of personal and organisational resources shape job satisfaction in GenAI-mediated knowledge work, with particular focus on marginalised employees. Survey data from 2 knowledge workers were analysed using a configurational approach. Results show that most employees thrive under high time pressure and cognitive demands when sufficient resources are available, underscoring the role of capital in buffering job strain. However, subgroup analysis reveals contrasting patterns: formal organisational support is essential for non-marginalised employees but unnecessary, and sometimes counterproductive, for marginalised employees, who rely instead on informal peer support, AI efficacy, and autonomy. These findings extend digital inclusion research and highlight the need for differentiated organisational strategies to develop equitable participation in AI-mediated workplaces.
Recommended Citation
Brooks, Jade; Seong, Daeun; and Wong, Randy, "Inclusion in GenAI-Mediated Work: A Configurational
Approach to Job Satisfaction of Marginalised Knowledge
Workers" (2025). ACIS 2025 Proceedings. 244.
https://aisel.aisnet.org/acis2025/244