The role of artificial intelligence in enhancing internal audit quality: A resource-based view approach

Nowadays, artificial intelligence (AI) has experienced a remarkable resurgence of interest in the business world due to its ability to perform tasks traditionally carried out by humans, replicating cognitive capacities and professional judgment through machines and computers. This technological advancement, now in its golden age, enables organizations to respond to rapidly evolving market demands, achieve competitive advantages, and ensure long-term sustainability. Consequently, managers are increasingly adopting AI tools to integrate them into their organizational processes and decision-making activities. Internal auditing, as a key function within organizations, has been profoundly affected by this technological revolution, experiencing significant transformations through the automation of audit processes, expansion of its scope, reduction of processing times, and, ultimately, improvement in audit quality. The present article aims to theoretically explore how AI techniques contribute to enhancing the quality of internal auditing, relying on the Resource-Based View (RBV) framework as a guiding theoretical framework. Specifically, it identifies five explanatory dimensions through which AI supports auditing practices: task automation, document processing and analysis, risk and fraud detection, communication of results, and the reduction of human errors. Each dimension represents a critical pathway through which AI can increase audit efficiency, accuracy, and overall effectiveness. Furthermore, the competence of internal auditors is introduced as a moderating variable, as it conditions the extent to which these technological contributions can be effectively utilized and translated into meaningful improvements in audit performance. By highlighting the interaction between technological resources and human expertise, this study emphasizes the strategic value of integrating AI within internal auditing practices.