Analysis of the Role of Information System Audit in Ensuring Organizational Data Security in the Era of Artificial Intelligence (AI)

Abstract

The advancement of Artificial Intelligence (AI) within organizational information systems has led to notable improvements in efficiency and decision-making processes. Nonetheless, the integration of AI-based systems introduces new challenges pertaining to data security, including threats to data integrity, vulnerabilities in machine learning models, and a lack of transparency in algorithms. Consequently, information system audits, which traditionally concentrated on conventional systems, must evolve to assess these complex and dynamic systems effectively. This paper seeks to theoretically explore the function of information system audits in safeguarding data security in the context of AI, employing a literature review and descriptive analysis methodology. The findings of this study suggest that audits play a crucial role in maintaining the integrity, security, and reliability of AI systems through an adaptive auditing approach, a comprehensive understanding of the AI pipeline, and the implementation of standards such as COBIT and ISO/IEC 27001. Therefore, it is imperative that auditing methodologies are updated to address the intricacies and dynamic nature of AI technologies