The Impact of Artificial Intelligence on Accounting and Auditing Practices: Opportunities, Risks, and Regulatory Challenges

Abstract This article explores the increasing role of artificial intelligence in accounting and auditing, focusing in particular on the opportunities, risks and challenges for regulation in today's professional and institutional context. AI is redefining the essentials of accounting and auditing by facilitating automation, continuous monitoring, anomalies detection, predictive analysis, and broadening decision support which ultimately strengthens efficiency, coverage, and the quality potential of financial reporting and assurance streams. INFO Researchers at the same time have identified massive challenges with regards to data quality, model opacity, algorithmic bias, cybersecurity, professional judgment, documentation, accountability, and regulatory compliance with the use of AI. Global standard-setting and regulatory dialogues have recently turned to the implications of AI for audit quality, the quality management system (QMS) in response to technological change, and the competence of auditors, and expectations that existing standards are appropriately future-proofed for a changing technology landscape. This paper adopts an analytical and interdisciplinary approach based in accounting, auditing, governance and regulatory scholarship to assess the impact of the AI revolution on accounting operations, audit practices, systems of internal control and professional roles. It also examines if the current regulatory and institutional approaches are adequate enough to tackle challenges posed by AI-driven systems within assurance environments. While AI in accounting and auditing has many advantages, the article emphasizes that success will still rely on sound governance frameworks, human in the loop for oversight, proper documentation and transparency, ethical safeguards, and regulation that can flexibly adapt. The study therefore concludes that the future of AI in accounting and auditing is not one where professional expertise is fully replaced by technological capability, but a hybrid model that accommodates professional skepticism, accountability and public-interest regulation.