Artificial Intelligence Capabilities and the Development of a Smart and Sustainable Auditing Ecosystem: The Moderating Role of Cyber Forensic Accounting Intelligence

ARTIFICIAL INTELLIGENCE, BIG DATA ANALYTICS, TIME PRESSURE, AND AUDIT QUALITY: THE MODERATING ROLE OF ETHICAL CULTURE IN PUBLIC ACCOUNTING FIRMS

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.

Applying artificial intelligence within decision support systems and its role in improving proactive thinking and reducing security threats: The mediating role of data quality

The study aimed to identify the impact of applying artificial intelligence within decision support systems in improving the level of proactive thinking and reducing security threats in government institutions in the Arab Republic of Egypt, as well as to examine the mediating role of data quality in this relationship, at a significance level of (α ≤ 0.05). The study sample consisted of (360) participants working in the departments of information technology, decision support, and cybersecurity within government institutions and national authorities that rely on AI-enhanced decision support systems. The study adopted the descriptive analytical method and used a questionnaire as the primary tool for data collection. The findings revealed a statistically significant relationship between certain dimensions of artificial intelligence (predictive analytics systems, intelligent agents, and machine learning) and the level of proactive thinking. The results also showed a statistically significant relationship between artificial intelligence and the reduction of security threats. Furthermore, the study demonstrated a statistically significant mediating role of data quality in the relationship between artificial intelligence and proactive thinking, as well as between artificial intelligence and the reduction of security threats. The study recommended strengthening the use of artificial intelligence in decision support systems, improving data quality, and integrating these systems with cybersecurity measures to maximize predictive and preventive benefits within institutions. It also recommended identifying the theoretical foundations of artificial intelligence applications in decision support systems and their role in enhancing proactive thinking within security institutions, determining the most prominent AI applications used in such systems, and clarifying how previous literature interprets methods for promoting AI adoption in decision support systems to improve data quality in security institutions.

Mechanisms and Pathways for Enhancing Internal Audit Effectiveness in Universities through Artificial Intelligence

As artificial intelligence (AI) becomes increasingly embedded in university governance and auditing, a central concern in the intelligent transformation of internal auditing is how to leverage its technological advantages to improve audit effectiveness. This study examines the process through which AI enables internal auditing in universities, analyzes the mechanism by which audit effectiveness is generated, and develops an evaluation system comprising five dimensions and 17 indicators. The analytic hierarchy process (AHP) and fuzzy comprehensive evaluation are then applied to assess a case university. The results indicate that the university achieves an overall rating of good in AI-enabled internal audit effectiveness. Although it has established a certain level of digital infrastructure and capability for converting technological inputs into audit outcomes, further improvement is required in technological innovation, the in-depth application of intelligent tools, and data governance. Based on the weaknesses identified by the evaluation, this study proposes targeted improvement pathways. The findings provide a reference for universities seeking to advance intelligent internal auditing and enhance the effectiveness of AI applications.

Cybersecurity Challenges in AI - Integrated Accounting and Auditing Systems: Empirical Evidence from Vietnam

The rapid proliferation of artificial intelligence (AI) and digital transformation technologies in the Vietnamese business environment has profoundly altered the landscape of accounting and auditing, simultaneously introducing new and complex information security challenges. This study applies the Technology-Organization-Environment (TOE) framework to examine factors affecting Accounting Information Security (AISe) in Vietnamese enterprises during the ongoing digital transformation. The research model integrates four independent variables — Senior Management Support (TMS), Information Security Culture (SC), Quality of Accounting Information Systems (QAIS), and Cybersecurity Readiness (CSR) — and constructs the dependent variable AISe as a second-order formative construct encompassing three dimensions of the CIA triad: Confidentiality (CISe), Integrity (IISe), and Availability (AvISe). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0, the study analyzed data collected from 228 respondents across Vietnamese enterprises. Results show that QAIS exerts the strongest positive influence on AISe (β = 0.570, p < 0.001), followed by SC (β = 0.152, p = 0.047) and CSR (β = 0.151, p = 0.046). TMS does not directly affect AISe but exerts a strong indirect effect through SC (β = 0.777, p < 0.001). The model explains 69.4% of variance in AISe (R 2 = 0.694). These findings offer empirical evidence supporting the integrated role of technological and organizational factors in securing accounting information within Vietnam's developing digital economy. Recent developments in AI governance, including Resolution No. 57-NQ/TW (2024) and Vietnam's national AI transformation strategy (2025-2026), further underscore the urgency of these findings for policy and practice.

Can artificial intelligence (AI) predict cybersecurity risks? Qualitative evidence from the banking sector in an emerging economy

Cybersecurity, and Artificial Intelligence

The study demonstrates that the successful deployment of AI Builder is contingent more on organizational readiness and accountability than technological maturity, and offers an informed blueprint to organizations adopting low-code AI platforms.