Exploring the Adoption of Artificial Intelligence in Auditing Using System Dynamics

Abstract

Adoption of artificial intelligence (AI) in the auditing sector is influenced by ambiguous interaction of various factors that impact the input, processing, and output stages of AI adoption representing a complex system. System dynamics, one of the areas of system thinking, provides a comprehensive framework for understanding the dynamic behaviour and interactions of such complex systems. In the present research, the adoption of AI in auditing has been analysed through system dynamics. A conceptual framework of AI adoption has been proposed to comprehensively understand the process of AI adoption in auditing. Systems dynamics tools such as causal loop diagram (CLD) and stock and flow diagram have been deployed to study the complex and unclear interactions of factors influencing adoption. To simulate and model AI adoption in auditing, Vensim and Stella software were utilised to construct a CLD and a stock and flow model, offering novel understandings into the drivers and inhibitors of AI integration. This study provides a foundational understanding for practitioners and researchers navigating the transformative impact of AI on auditing.

Keywords: Artificial Intelligence, Auditing, System Dynamics, Causal Loop Diagram, Stock Flow Model

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