Perceived Architectural Fit in Workplace Reliance on Artificial Intelligence: Evidence from a UTAUT-Based Model

Abstract

Artificial intelligence (AI) is increasingly integrated into workplace operations through general-purpose systems, including large language models, foundation-model platforms, and AI assistants. The Unified Theory of Acceptance and Use of Technology (UTAUT) explains adoption through performance expectancy, effort expectancy, social influence, and facilitating conditions; however, the four UTAUT-related constructs used here do not directly represent whether an AI system’s technical and governance supports fit the accountability demands of its intended use. This study tests perceived architectural fit, defined as the perceived match between those supports and the accountability demands of the intended use, as an added predictor in a UTAUT-based model. A quantitative vignette-based survey with prebalanced 2 × 2 conditions and post-vignette perception measures collected 350 responses from U.S. workers with workplace AI exposure and retained 282 after screening. The four UTAUT-related predictors jointly explained 59.7% of the variance in AI reliance intention (ARI). Adding perceived architectural fit increased explained variance by 10.0 percentage points, and perceived architectural fit remained significant in the full model. Participants receiving the enhanced architectural-support description reported higher perceived architectural fit than participants receiving the limited-support description. Assigned conditions did not produce statistically significant differences in perceived legitimacy or ARI. Secondary analyses found that perceived architectural fit was associated with perceived legitimacy and that perceived legitimacy was associated with ARI. A bootstrap analysis also identified a positive indirect association through perceived legitimacy after controlling for the UTAUT-related predictors. The findings provide quantitative evidence that perceived architectural fit may contribute explanatory value to UTAUT-based research on workplace ARI.