The rapid digital transformation of the financial services sector is fundamentally reshaping the practice of financial auditing, with artificial intelligence (AI) playing a pivotal role in this evolution. It describes how current AI tools such as machine learning, natural language processing and predictive analytics, are altering audit work by handling routine risk assessments, spotting risks early, constantly monitoring and using large amounts of data. Even though AI improves how efficient, accurate and insightful audits can be, it creates serious issues with explainability, data quality, bias, ethics and regulations. Customary auditing practises, guided by rules of professional scepticism and proof-based decisions, need to change to handle the emergence of algorithms that change the responsibilities of auditors. The review summarises both the ideas and real-life practises related to AI in auditing, pointing out the main problems, risks and benefits these innovations bring. It investigates which auditing abilities are relevant now, the controls that are needed for artificial intelligence (AI) and the ethical considerations involved in working with AI. Certainly, the review points out that there are gaps in research, most importantly about the lasting effects of AI on audit quality, the auditor-AI interaction over time and the compliance measures necessary to maintain transparency and confidence. With its thorough conceptual approach, this study tries to guide action in both academia, professional practice and policy by suggesting ways for auditors, firms and regulators to integrate AI into financial auditing. The review therefore shows that for assurance to work, AI should be used to enhance it but make sure human wise and ethical standards are maintained in financial reporting.
Abetoh Nyiawung Fobellah (Sun,) studied this question.