Bridging Knowledge Gaps in Internal Auditing and Cybersecurity: Transitioning from CAATTs to AI-Driven Solutions

Within the rapidly advancing technological environment, the intersection of internal auditing and cybersecurity has become increasingly critical. By applying a literature review, this research critically evaluates established frameworks to identify existing knowledge gaps and establish a basis for further development. The paper focuses on the technological transition from traditional Computer-Assisted Audit Tools and Techniques (CAATTs) to modern Artificial Intelligence (AI)-driven internal auditing solutions. By analyzing recent academic literature (period 2021-2026), the study explores how AI enhances cyber threat detection within accounting information systems and identifies the primary challenges practitioners encounter during implementation. The findings aim to bridge the current gap in cybersecurity-related accounting literature and provide a theoretical foundation for redefining frameworks in the era of AI. Ultimately, this paper results in a synthesized theoretical foundation for future research. The identified future directions serve to guide both academics and practitioners in the evolving domain of automated auditing, providing a framework amidst the intensive development of AI technologies and the rapid digital transformation of the internal auditing.