Jul 2026· Current: Jurnal Kajian Akuntansi dan Bisnis Terkini· Vol 7, pp. 609-626· 0 citations· 38 references
TL;DR
Investigation of the effects of Artificial Intelligence, Big Data Analytics, and Time Pressure on audit quality, while examining the moderating role of Ethical Culture indicates that AI and Time Pressure significantly improve audit quality, whereas BDA has no significant effect.
Abstract
The rapid advancement of digital technologies has transformed audit practices, creating opportunities and challenges for maintaining audit quality. Drawing on the Theory of Planned Behavior, this study investigates the effects of Artificial Intelligence (AI), Big Data Analytics (BDA), and Time Pressure on audit quality, while examining the moderating role of Ethical Culture. Using a quantitative approach, questionnaire data were collected from 99 external auditors across 25 Public Accounting Firms in Semarang, Indonesia, and analyzed using Partial Least Squares Structural Equation Modeling. The results indicate that AI and Time Pressure significantly improve audit quality, whereas BDA has no significant effect. Ethical Culture weakens the relationship between Time Pressure and audit quality but does not moderate the effects of AI or BDA. These findings extend the Theory of Planned Behavior by demonstrating that organizational ethical conditions influence how auditors respond to time constraints in technology-enabled audit environments. Practically, the study highlights the need to strengthen ethical culture, organizational readiness, and auditors' digital capabilities to optimize technology adoption and sustain audit quality.
This study examined the impact of data analytics and artificial intelligence (AI) on audit
quality of listed manufacturing companies in Nigeria. Specifically, the study investigated the
effects of audit data analytics adoption, artificial intelligence utilization, and auditor
technological competence on audit quality. The study was anchored on the Technology
Acceptance Model and Resource-Based View Theory. An ex-post facto research design was
adopted, and data were obtained from annual reports and corporate disclosures of 25 listed
manufacturing companies on the Nigerian Exchange Group (NGX) covering the period
2015–2024. The study employed panel regression analysis. Audit quality was proxied by
audit report quality, while data analytics adoption, AI utilization, and auditor technological
competence served as explanatory variables. The findings revealed that audit data analytics
adoption has a positive and significant effect on audit quality (β = 0.421, p = 0.000),
artificial intelligence utilization exerts a positive and significant effect on audit quality (β =
0.387, p = 0.002), while auditor technological competence also has a positive and significant
influence on audit quality (β = 0.294, p = 0.011). The model explained approximately 68.4%
of the variation in audit quality (Adjusted R² = 0.684). The study concluded that data
analytics and artificial intelligence significantly enhance audit quality by improving audit
efficiency, fraud detection capability, risk assessment accuracy, and financial reporting
reliability. The study recommended increased investment in AI-enabled audit systems,
continuous auditor training, and the establishment of regulatory guidelines for technology
assisted auditing.
Okolo Chibueze Friday· Journal of Accounting and Fi...· 0 citations
The findings indicate that AIC significantly supports the development of SSAE, and CFAI strengthens the influence of AIC on SSAE, suggesting that accountants’ cyber forensic competencies enhance the effectiveness of AI-enabled auditing systems.
Phuc Kien Vu, H. Q. Pham· Journal of Cyber Security an...· 0 citations
The rapid advancement of digital technologies has significantly transformed auditing practices, leading to the emergence of audit analytics as an important research domain that integrates accounting, auditing, and data science. This study aims to examine the evolution, intellectual structure, influential contributions, and emerging research trends in audit analytics through a bibliometric analysis approach. Data were collected from the Scopus database using relevant keywords related to audit analytics and analyzed using VOSviewer to perform citation analysis, keyword co-occurrence analysis, density visualization, and collaboration network analysis. The findings indicate that audit analytics research has experienced substantial development, particularly with the increasing adoption of big data analytics, artificial intelligence, machine learning, predictive analytics, blockchain, and automation technologies. Citation analysis identifies key contributions focusing on the role of big data and artificial intelligence in improving audit quality, audit judgment, fraud detection, and decision-making processes. The keyword analysis reveals that recent research trends have shifted from traditional analytical methods toward intelligent and automated audit systems that support continuous auditing and risk-based decision-making. Furthermore, collaboration analysis demonstrates the global nature of audit analytics research, with the United States emerging as the most influential contributor and strong research connections among countries and institutions. This study contributes to the literature by providing a comprehensive understanding of the development trajectory of audit analytics and identifying future research opportunities related to generative artificial intelligence, explainable AI, cybersecurity, and digital audit transformation.
L. Judijanto· West Science Accounting and...· 0 citations
Data science and artificial intelligence (AI) are increasingly used in public health surveillance, triage, diagnostics, and service delivery, while legal and audit controls often lag behind deployment. This paper integrates the third wave of digital era governance (DEG3) with corporate governance mechanisms to frame public health AI as auditable decision infrastructure. Using a structured review and qualitative documentary analysis of public records from 12 jurisdictions between 2016 and 2024, the study identifies recurring failures in senior oversight, contracting transparency, audit rights, model documentation, monitoring and redress. Findings show that capability-first deployments scale faster than accountability mechanisms, whereas pooled standards, auditable procurement and independent assurance reduce repeated failures. The paper proposes a corporate-governance-informed control architecture for lawful, auditable and rights-based scaling of public health AI.
W. Latif, Inkar Mussayeva, Supta Chowdhury et al.· Corporate Law & Governan...· 1 citation· ⚡1
The integration of artificial intelligence (AI) into auditing has created a paradigm shift, presenting both unprecedented opportunities to enhance audit quality and significant policy challenges that threaten the foundations of professional judgment. This systematic literature review analyses peer-reviewed articles to synthesize the current landscape of AI in auditing and identify the primary policy challenges confronting the profession. Our analysis reveals a fundamental tension between the automation of audit tasks and the preservation of professional skepticism and judgment. Key themes emerging from the literature include the paradox of professional judgment in an automated environment, the double-edged sword of AI in enhancing audit quality while introducing new risks, the critical need for transparency and explainability in AI systems, the pervasive threat of algorithmic bias, and the significant gaps in regulatory frameworks and professional standards. The findings indicate that while AI offers powerful tools for data analysis, fraud detection, and risk assessment, its adoption is hampered by a complex web of ethical, technical, and organizational barriers. The primary policy challenges identified include regulatory lag, the erosion of professional identity, new quality assurance demands, evolving competency standards, the need for robust ethical frameworks, unresolved liability issues, and a lack of standardization. This review concludes 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. I propose a research agenda focused on the long-term effects of AI on professional judgment, the effectiveness of governance models, and the development of new audit methodologies that effectively integrate human and machine intelligence.
Geoffrey Odoch· International journal of com...· 0 citations
A strong positive relationship was found between the use of AI and the four dimensions of corporate administration that were investigated, thereby suggesting that the proposed integrated framework could serve as a basis for developing a theory and organizational practice for the future.
Tulika Dutta Roy· International Journal of Mod...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
