Adaptive structural audit processes as shaped by emerging technologies

Abstract

This study investigates how audit firms integrate emerging technologies to transform traditional audit methodologies and enhance audit quality. Using a qualitative research approach, the findings highlight that centralized audit platforms streamline documentation, promote knowledge sharing, and facilitate more effective internal reviews. Advanced Data Analytics (ADAs) such as the General Ledger (GL) Analyzer, process mapping technologies, and data visualization platforms complement professional judgment and skepticism, ensuring that human expertise remains central to the audit process. However, regulatory lag and dual data governance frameworks challenges hinder the seamless adoption of data-centric audit practices. This study emphasizes the importance of audit-data team collaboration for managing large datasets, ensuring data quality, and mitigating the risks of noisy data and false positives. Scalable audit tools are essential to serve a broad client base while retaining the flexibility to address client-specific risks. The Adaptive Audit Ecosystem (AAE) is introduced as a theoretical contribution, conceptualizing the interaction between technology, human expertise, governance structures, and regulatory requirements. The AAE illustrates how emerging technologies augment traditional practices while preserving essential audit principles, such as professional skepticism, judgment, independence, and accountability. This study concludes by presenting a future research agenda within the People, Process, Technology, and Governance (PPTG) framework.