Trusting in Generative AI: Catalyst for Employee Performance and Engagement in the Workplace

Abstract

This paper investigates the impact of the usage of generative AI (GenAI) and services with integrated GenAI on employee performance, alongside with the role of trusting in these tools and services. Employing a mixed methodology, the research first analyzes data from 251 professionals in Spain using a structural equation modeling (SEM) approach, followed by a qualitative survey of 69 top academics in management sciences. Findings indicate that the adoption and effective use of GenAI services does not directly improve workplace performance. Instead, an optimal level of trust in these services plays a critical mediating role, enhancing work engagement and thereby performance. The study draws on the reviewed job demand-resources theory (JD-R) to construct a new theoretical framework of applied in GenAI services, offering insights into how user experience and trust influence engagement and productivity. For managers, these results highlight the importance of building an optimal level of trust in GenAI among employees and users of services with integrated GenAI to boost work engagement and performance.