The Role of Artificial Intelligence Adoption in Transforming Accounting Practices, Audit Quality, and Financial Reporting Transparency: A Multi-Framework Empirical Analysis

Abstract

The rapid proliferation of Fourth Industrial Revolution technologies has fundamentally disrupted traditional corporate governance and accounting ecosystems globally. This study provides a comprehensive empirical investigation into the impact of artificial intelligence (AI) adoption on accounting information systems, audit quality, and the overall transparency and quality of corporate financial reporting. Drawing upon a synthesized theoretical framework that integrates the Technology-Acceptance Model (TAM), the Technology-Organization-Environment (TOE) framework, and Resource-Dependence Theory (RDT), we analyze how different configurations of machine learning, robotic process automation, and natural language processing reshape financial transparency. Using a robust dataset across diverse corporate jurisdictions, this research examines the mediating role of internal control environments and the moderating influence of institutional governance standards. The empirical findings demonstrate that sophisticated AI integration significantly mitigates information asymmetry, reduces earnings management behavior, and enhances the predictive value and faithful representation of financial disclosures. Furthermore, the automation of complex analytical procedures structurally elevates audit quality by minimizing human error and broadening the scope of continuous auditing. However, the efficacy of these technological interventions remains deeply contingent upon the maturity of institutional data governance structures and the strategic upskilling of accounting professionals. This paper offers critical insights for regulators, corporate boards, and accounting standard-setters navigating the digital transformation of financial ecosystems.