Paper Type
Complete
Abstract
Despite widespread adoption of generative AI (GenAI), many organizations still fall short in providing adequate AI tools or support, raising questions about how such corporate AI inadequacy shapes employees’ propensity to engage in shadow GenAI usage. As a result, concerns over unapproved or “shadow” GenAI usage have intensified. We thus investigate whether and how corporate AI inadequacy influences employees’ unauthorized use of GenAI. Using online survey data from 340 full-time employees, we find that corporate AI inadequacy exerts two countervailing emotional effects: it heightens employees’ frustration with internal AI resources while simultaneously reducing their fear of missing out (FoMO) about falling behind in AI adoption. These opposing emotions, in turn, exhibit distinct downstream implications for shadow GenAI usage. Furthermore, we show that perceived GenAI sycophancy shapes these affective pathways by amplifying the FoMO-reducing effect of AI inadequacy while altering the influence of frustration. This study offers practical and theoretical implications.
Paper Number
1642
Recommended Citation
Liu, Huiyu; Shan, Guohou; Wu, Ying; Yin, Jingfeng; and Thatcher, Jason B., "Corporate AI Inadequacy and Employee Shadow Generative AI Usage" (2026). AMCIS 2026 Proceedings. 10.
https://aisel.aisnet.org/amcis2026/sig_osra/sig_osra/10
Corporate AI Inadequacy and Employee Shadow Generative AI Usage
Despite widespread adoption of generative AI (GenAI), many organizations still fall short in providing adequate AI tools or support, raising questions about how such corporate AI inadequacy shapes employees’ propensity to engage in shadow GenAI usage. As a result, concerns over unapproved or “shadow” GenAI usage have intensified. We thus investigate whether and how corporate AI inadequacy influences employees’ unauthorized use of GenAI. Using online survey data from 340 full-time employees, we find that corporate AI inadequacy exerts two countervailing emotional effects: it heightens employees’ frustration with internal AI resources while simultaneously reducing their fear of missing out (FoMO) about falling behind in AI adoption. These opposing emotions, in turn, exhibit distinct downstream implications for shadow GenAI usage. Furthermore, we show that perceived GenAI sycophancy shapes these affective pathways by amplifying the FoMO-reducing effect of AI inadequacy while altering the influence of frustration. This study offers practical and theoretical implications.
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