Date of Graduation

5-2024

Document Type

Thesis

Degree Name

Bachelor of Science in Business Administration

Degree Level

Undergraduate

Department

Accounting

Advisor/Mentor

Bryan, Barry

Abstract

The evolving landscape of the audit profession has been significantly influenced by the integration of artificial intelligence (AI) and automation, marking a pivotal shift in audit methodologies, the auditors' roles, and the overarching quality of audits. This thesis delves into the breadth of AI's impact on the industry through a comprehensive review of academic literature, professional publications, and industry insights, highlighting the transformative effects of AI on audit processes. AI-driven tools, including machine learning, deep learning, and natural language processing can expedite laborious audit tasks, enhancing data analytics capabilities, and enabling more accurate risk assessment and fraud detection. AI technologies facilitate a timelier audit process through task efficiencies, shifting the auditor’s role towards analytical and decision-making functions. This indicates the need for auditors to have competence in the areas of data analytics and AI in addition to traditional accounting and auditing expertise. AI tools can create evidentiary benefits that raise the bar of reasonable assurance provided by issued opinions, fostering stakeholder confidence in audited financial statements, and thus achieving higher audit quality. However, there are ethical concerns related to data privacy and algorithmic transparency, which have created uncertainty regarding AI’s implementation. Addressing these challenges will require the formulation of standards and guidance that ensure AI can be integrated responsibly. Despite these challenges, the adoption of AI is becoming ever more important for audit firms aiming to stay competitive and deliver higher-quality audits. This paper communicates the necessity for auditors to adapt to these technological advancements and advocates for the establishment of AI regulations and training programs to ensure ethical practices and the reliability of audit outcomes.

Keywords

Accounting; Auditing; Artificial Intelligence; Audit Quality; Machine Learning; Deep Learning

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