Date of Award

1-1-2023

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Information Science

Content Description

1 online resource (ix, 349 pages) : illustrations (some color)

Dissertation/Thesis Chair

Sanjay Goel

Committee Members

Kevin Williams, Dennis Caplan

Keywords

AI audit, Audit quality, Emerging technologies, External audit, Auditing

Subject Categories

Accounting

Abstract

The external audit profession faces a rapidly changing environment due to innovative and intelligent technologies. For example, traditional external auditors are challenged to perform cybersecurity related tasks and conduct remote audits. Today, external audits are not only performed on financial statements and IT controls, but also on Artificial Intelligence (AI) systems to ensure compliance with laws and ethical standards, and technical robustness. To address these emerging trends of technology and their impact on the audit profession, this dissertation focuses on three research questions: 1) What affects professional auditors’ and accounting students’ performance in cybersecurity-related tasks? 2) How are changes from onsite audits to remote audits associated with audit quality, audit efficiency, and auditors’ job satisfaction? and 3) What auditability characteristics of AI systems and auditors’ competencies are necessary for AI audits? Through surveys and interviews, this dissertation reveals that drivers of audit quality for the emerging tasks (i.e., cybersecurity related tasks, AI audit tasks) and working modes (i.e., remote audits, hybrid audits) deviate from existing audit quality drivers for traditional audit tasks (i.e., financial audits, IT audits). As an outcome of this dissertation, many new factors related to remote work, AI auditability, and AI auditors’ competencies have been identified that may contribute to external audit success. Some existing audit quality drivers, such as professional skepticism, remain important in emerging cybersecurity related tasks for external auditors. This dissertation has both academic and practical significance. First, this dissertation enriches the existing literature by exploring how traditional drivers of audit quality affect external auditors’ performance in emerging tasks and working modes, including cybersecurity-related tasks, AI audit tasks, and working remotely. Second, this dissertation identifies new factors that may enhance auditors’ performance in these novel tasks and working modes. Third, the proposed auditability framework and a listing of required auditors’ competencies translate high-level auditability principles and competency requirements for auditors into actionable and detailed measures. The results can also benefit AI developers and AI deployed parties in enhancing the auditability of AI and help audit managers identify the right experts for the AI audit team.

Download

Included in

Accounting Commons

Share

COinS