The adoption and effective use of artificial intelligence in Moroccan higher education: the moderating role of trust

Abstract

In a context where artificial intelligence (AI) is rapidly transforming pedagogical practices, higher education (HE) methods increasingly integrate intelligent systems to enrich learning. Despite growing interest, research often relies on traditional models such as the Technology Acceptance Model (TAM), which insufficiently address trust-related concerns specific to AI. This study fills that gap by examining factors influencing AI adoption and effective use in HE. It builds on an extended TAM, incorporating perceived efficiency, ease of use, usefulness and trust as a moderating variable, thereby integrating psychological and ethical dimensions often overlooked. Trust is treated not merely as a side factor but as central to moving from intention to sustained use, especially when interacting with autonomous systems. Data were collected via a questionnaire targeting diverse HE stakeholders, ensuring representativeness. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method validated hypothesized relationships. Results confirm that perceived efficiency, usefulness and ease of use significantly influence adoption, which in turn strongly predicts effective use. Trust positively moderates the adoption–use link, reinforcing transition from intention to action. This highlights the need to integrate trust into acceptance models to enhance AI’s successful institutional integration. Theoretically, the study extends TAM to contexts where ethical and trust dynamics are critical. Practically, it suggests that strategies to promote AI adoption must go beyond functional benefits, actively fostering trust through transparent communication, ethical design principles and robust user support. Such measures can address resistance, align AI tools with academic values, and ensure their responsible and impactful deployment in HE.