From e-compliance to smart taxation: Institutional pressures, digital trust, and SME adoption of AI-based tax tools in Morocco

Abstract

This article explores the dynamics of advanced tax digitalization adoption, including artificial intelligence–enabled systems, by Small and Medium-sized Enterprises (SMEs) in the context of an emerging economy. It examines how institutional pressures, organizational capabilities, and digital trust shape and moderate the process through which these firms appropriate such technologies.

Methodologically, the research follows an interpretivist qualitative approach based on 24 semi-structured interviews conducted in Morocco, including 18 SME owners/managers and 6 tax and digitalization experts. The dataset is analysed using the Gioia data structure, which enables the systematic emergence of first-order concepts, second-order themes, and aggregate dimensions, thereby providing a nuanced understanding of the underlying adoption logics.

The findings show that the adoption of AI-driven tax solutions by SMEs unfolds as a coercive and reactive process, primarily driven by regulatory mandates rather than strategic innovation intent. The perception of AI in taxation is strongly marked by fear of algorithmic opacity, frequently described as a “black box,?? which undermines perceived transparency and fairness. This perception is exacerbated by a structural deficit of internal resources and skills (liability of smallness) and by a pervasive distrust of the tax administration’s motives, particularly in terms of control and sanctioning power. As a result, SMEs tend to deploy façade compliance strategies, such as symbolic decoupling and extensive outsourcing of fiscal tasks, which limit genuine learning and prevent any deeper strategic transformation.

As an original contribution, the article proposes a theoretical extension of the Technology–Organization–Environment (TOE) framework tailored to coercive institutional settings by introducing Digital Institutional Trust as a mediating variable between environmental pressures and actual appropriation of digital tax tools. It also highlights the urgent need to establish forms of “digital procedural justice?? capable of enhancing transparency, explainability, and perceived fairness in AI-driven tax systems, thereby fostering more substantive and sustainable adoption among SMEs in emerging economies.

Classification JEL: H20

Paper type: Theoretical Research and Empirical Research