Critical Review Journal Opportunities for Artificial Intelligence Development in the Accounting Domain: The Case for Auditing Melia A. Baldwin, Carol E. Brown, & Brad S. Trinkle (2006)
Jul 2026· Journal of Creative Power and Ambition (JCPA)· Vol 4, pp. 1591-1598· 0 citations· 9 references
TL;DR
This critical review aims to analyze the article by Baldwin, Brown, and Trinkle (2006) titled Opportunities for Artificial Intelligence Development in the Accounting Domain: The Case for Auditing to show that auditing is a very potential field for AI application.
Abstract
This critical review aims to analyze the article by Baldwin, Brown, and Trinkle (2006) titled Opportunities for Artificial Intelligence Development in the Accounting Domain: The Case for Auditing. The article discusses the opportunities for developing Artificial Intelligence (AI) in the accounting field, particularly in auditing and assurance processes. The method used in this review is a literature study with a descriptive-analytical approach to the article's content, covering research objectives, methods, main findings, contributions, as well as the strengths and limitations of the article. The review results show that auditing is a very potential field for AI application because it involves analyzing large amounts of data, complex decision-making, professional judgment, and anomaly and fraud detection. The authors of the article emphasize that AI is not intended to replace auditors, but rather serves as a tool to enhance efficiency, effectiveness. and the quality of audits. Although this article has limitations because it is conceptual and not yet supported by empirical evidence, the review provides an important contribution as an initial theoretical foundation for research on AI in auditing. Thus, this article remains relevant to be used as a reference in research on audit analytics, continuous auditing, fraud detection, and the use of AI technology in the accounting profession.
It is concluded that the auditing profession is at a critical juncture, requiring a concerted effort from regulators, standard-setters, firms, and educators to navigate the transformative impact of AI.
Geoffrey Odoch· International journal of com...· 0 citations
The findings indicate that XAI is mainly applied to fraud detection, credit assessment, financial auditing, and decision-support processes, with a predominance of techniques such as SHAP and LIME.
Iván Patricio Arias-González, Gabriela Serrano-Torres, Eduardo Ramiro Dávalos-Mayorga et al.· Frontiers in Artificial Inte...· 0 citations
It is suggested that AI enhances fraud detection, risk assessment, and audit quality, while raising concerns regarding algorithmic bias, transparency, and professional skepticism.
Artificial intelligence (AI) is fundamentally reshaping the
auditing profession, challenging traditional competency
frameworks and redefining the scope of the auditor’s role.
This study is based on the premise that, beyond traditional
financial audit tasks, the contemporary auditor is
increasingly expected to contribute to audit committee
governance, sustainability (ESG) assurance, as well as
the direct application of AI-based tools in audit
engagements. Despite the growing academic and
professional interest in AI adoption, a comprehensive and
integrated framework capturing the full spectrum of AI-
related competencies required across all auditor roles
remains insufficiently developed in the literature. This
paper addresses this gap through a Structured Literature
Review (SLR) that examines 22 peer-reviewed articles
indexed in Web of Science and published between 2019
and 2025, identifying and synthesizing evidence on how
AI is reshaping auditor competencies across four
interconnected roles: financial auditor, audit committee
member, ESG assurance provider, and user of AI tools.
Based on the synthesized evidence, the authors propose
an integrated competency framework for the auditor
prepared for the AI era, structured around six competency
dimensions and four professional roles, with direct
implications for professional bodies, Continuing
Professional Development (CPD) programmes, and
certification requirements.
Elena Claudia Badea (florea), Andreea-Larisa Olteanu (Burca), M. Bunea et al.· Audit Financiar· 0 citations
Over the years, there has been an inclined growth in technology such that artificial intelligence (AI), accounting analytics, and machine learning have revolved in the practice of auditing in accounting field. Numerous substantial possibilities are presented by the above-mentioned technologies which include creating a robust framework of internal control and optimizing fraud detecting activities especially in the public organizational sector, where accountability and clarity are a necessity. The study examined the Impact of Artificial Intelligence (AI), Accounting Analytics and Machine Learning on Auditing: Enhancing Internal control and Fraud Detection in public sector organizations. This study employed a mixed-methods approach. It analyzed quantitative and qualitative data collected from: Government audit reports and financial statements, AI-driven risk assessment models and machine learning fraud detection datasets, Auditor and financial expert surveys (to gauge perception and practical AI implementation challenges), and Case studies from public sector organizations worldwide. The findings demonstrate that AI powered audit tools significantly reduce human errors, accelerate financial audits, and improve financial accuracy. Moreso, AI-based fraud detection models outperform traditional auditing methods, identifying fraudulent transactions with an 87% accuracy rate, compared to the 60-70% success rate of conventional audits.
Keywords: Artificial Intelligence, Machine Learning, Accounting Analytics, Fraud Detection, Internal Control, Public Sector.
Princess Ifeyinwa Nmezi· Radiant Journal of Business...· 0 citations
The purpose of this study is to examine the effect of Artificial Intelligence (AI) on the performance of selected audit firms in Nigeria. Globally, major auditing firms, especially the “Big Four” Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY), and KPMG have pioneered the integration of AI technologies into their audit processes. The study acknowledges that Artificial Intelligence encompasses a wide range of technologies including Natural Language Processing (NLP), Expert Systems, Computer-Assisted Audit Techniques (CAATs), and Data Mining. The study adopted descriptive survey research design. The population of this study comprises audit professionals working in selected audit firms within Lagos, Abuja, and Port Harcourt. Primary data was collected through a structured questionnaire divided into sections. The study recommends that audit firms in Nigeria, particularly those yet to fully integrate Machine Learning tools, should invest in machine learning-based audit software capable of detecting unusual transactions, identifying fraud patterns, and classifying high-risk transactions.
Ibrahim Oluwanifemi, Adedeji Elijah Adeyinka· International Journal of App...· 0 citations
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