The Transformational Role of Artificial Intelligence in Enhancing Internal Audit Practices in the Digital Era

Abstract

In a context of accelerated digital transformation, internal audit functions are being reshaped to meet new governance and risk management challenges. Artificial Intelligence (AI) emerges as both a strategic asset and an organizational challenge for internal auditors. This research conducts a narrative and integrative literature review of recent scientific contributions, aiming to understand how AI enhances the efficiency and quality of internal audits. Three theoretical frameworks underpin the analysis: contingency theory, agency theory, and innovation diffusion theory. These perspectives help explain the organizational adjustments required for AI adoption, its role in reducing information asymmetry, and the dynamics of technological diffusion.

Findings indicate that AI enables advanced automation of audit processes, strengthens fraud detection, and facilitates predictive, real-time auditing. However, its implementation requires the development of hybrid skills among auditors, as well as robust ethical and regulatory frameworks. Empirical studies from the Moroccan context reinforce these findings while highlighting specific constraints such as limited technological infrastructure, variable digital maturity, and institutional readiness. The study offers valuable managerial implications, emphasizing the need for training, technology governance, and strategic alignment between audit functions and digital transformation initiatives. It also proposes a set of guidelines for responsible AI integration in internal auditing practices. Lastly, it calls for future empirical research to examine how auditors engage with AI tools in practice and to assess the organizational impact of such technologies in real-world settings.

JEL Classification: M42, M49

Paper type: Theoretical Research