The merging of Artificial Intelligence (AI) with financial auditing and reporting is revolutionizing the face of new-age accounting methods. The paper discusses how revolutionary AI technologies have been to influence the mechanization of auditing tasks and ensure financial statements' precision, efficacy, and authenticity. Conventional audit procedures, being labor-intensive and manual, are being increasingly supplemented or replaced by smart systems with the ability to scan large amounts of data, identify anomalies, and provide real-time insights. The research surveys existing AI applications in auditing, their advantages and disadvantages, and examines their implications for auditors, financial institutions, and regulatory authorities. It also discusses the ethical, technical, and legal issues of implementing AI-based audit tools. The report indicates that while AI has a lot of potential to enhance audit quality and decision-making, effective integration is needed with careful planning, transparency, and continuous oversight. The use of Artificial Intelligence (AI) in auditing and financial reporting is revolutionizing conventional accounting processes. AI technologies such as machine learning (ML), natural language processing (NLP), and robotic process automation (RPA) are transforming the way audits are performed by automating tedious tasks, enhancing accuracy, and improving decision-making in financial reporting. AI systems can process huge amounts of data in real time, identify anomalies, and recognize patterns that might go unnoticed by human auditors, resulting in more precise and timely financial statements. This paper discusses the use of AI in automating auditing procedures, the benefits it provides in terms of efficiency and accuracy, and its effect on the quality of financial reporting. AI technologies used in audits offer auditors a strong capability to examine financial information at scale, identify latent threats, and spot fraud, all while lowering the risk of human mistakes and bias. This raises the integrity of financial reports and makes financial reporting more transparent and reliable. AI adoption in auditing is not free of issues. Problems like data privacy issues, the necessity of professionals to operate AI tools, and algorithmic biases should be tackled. Regulatory systems should also adapt to regulate the use of AI ethically and legally in audits.