Beyond Adoption Intention How Trust in Augmented Analytics Relates to Perceived Decision Quality Among Non-Technical BI Users

Abstract:Augmented analytics has transformed how Business Intelligence (BI) systems support decision-making, shifting non-technical managers from manual analysis toward dependence on automated insights. Current BI research often overlooks the cognitive mechanisms and the direct impact of AI-enabled analytics on decision quality. This study employs the theory of cognitive delegation to investigate the association between trust in augmented analytics and perceived decision quality among non-technical BI users. Data were collected from 250 business professionals across various organizational roles in Vietnam between January and March 2025 and analyzed using partial least squares structural equation modeling (PLS-SEM). Findings indicate that augmented analytics capabilities are positively associated with perceived ease of use, usefulness, and trust in BI systems. Trust and usefulness are jointly associated with BI adoption intention and perceived decision quality. Notably, trust is positively related to perceived decision quality, as observed within the studied sample of non-specialist users. By framing augmented analytics as cognitive delegation, this study expands BI adoption research to include perceived decision outcomes and contributes to the understanding of human-AI interaction in organizations.

Human-Computer Interaction (cs.HC); Computers and Society (cs.CY); Machine Learning (cs.LG)

arXiv:2605.20198 [cs.HC]

(or arXiv:2605.20198v2 [cs.HC] for this version)

https://doi.org/10.48550/arXiv.2605.20198 Focus to learn more arXiv-issued DOI via DataCite

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.