The Digital Transformation of the Internal Audit Function: A Qualitative Literature Review

Abstract

Artificial Intelligence (AI) is significantly transforming the internal audit function by enhancing efficiency, accuracy, and data management. Through the automation of repetitive tasks and comprehensive data analysis, AI repositions internal auditors as strategic advisors. However, its adoption presents challenges related to technological complexity, data security, and the need for new skills. In Morocco, AI integration remains limited, hindered by organizational and cultural barriers. This study highlights the importance of examining individual factors influencing AI acceptance among internal auditors. Digitalization thus emerges as a key lever for modernizing and enhancing the strategic role of internal auditing. To explore this transformation, a qualitative literature review was conducted to understand how digitalization has evolved within internal auditing at a global level. More than a simple inventory of publications, this approach captures the discursive and semantic dynamics that have shaped the relationship between digitalization and auditing over time and across regions. The review reveals both convergences and divergences in how internal audit functions are adopting digital tools, and highlights the distinct developmental paths followed by developed countries, emerging economies, and developing regions. Ultimately, the qualitative literature review provides a relevant analytical framework and a rich geographical and textual mapping of the changes underway in auditing in the digital age.