Introduction:
Artificial Intelligence (AI) is transforming financial reporting and auditing by automating complex processes, improving accuracy, and enhancing decision-making capabilities. Current advancements have demonstrated significant potential to streamline operations, increase transparency, and reduce human error. However, this transformative shift is accompanied by risks, such as algorithmic bias, cybersecurity threats, and regulatory challenges. This study examines the current applications of AI in financial reporting and auditing, explores potential future uses, and identifies associated opportunities and risks.

Methods:
This research employs a qualitative analysis of industry case studies to explore AI applications in financial reporting and auditing. Data were collected from published reports, industry insights, and case studies detailing the implementation of AI-driven tools by auditing firms and corporate finance departments. This study categorizes existing AI technologies and projects their future applications based on current trends and expert forecasts.

Results:
Key AI technologies in use today include natural language processing for automated report generation, machine learning for fraud detection, robotic process automation for data reconciliation, and predictive analytics for forecasting financial trends. Potential future applications encompass real-time auditing powered by AI-enhanced blockchain systems, advanced anomaly detection using deep learning algorithms, and AI tools for assessing compliance with increasingly complex regulatory requirements. These developments promise significant efficiency gains, but also highlight risks such as ethical concerns over algorithm transparency and challenges in safeguarding sensitive financial data.

Conclusions:
AI is revolutionizing financial reporting and auditing, offering unprecedented opportunities to improve efficiency and accuracy. However, its implementation must be accompanied by careful consideration of ethical, regulatory, and security concerns. Establishing robust frameworks for AI governance and fostering collaboration among stakeholders will be critical to harnessing AI's full potential while mitigating associated risks. Future research should focus on developing adaptive and ethical AI systems to ensure sustainable innovation in the financial industry.