Research on the Path and Challenges of Artificial Intelligence in Improving the Quality of Financial Reporting

Abstract

The development of the digital economy has placed higher demands on the quality of financial reporting. Traditional manual and semi-automated models are showing bottlenecks in data collection, error prevention, and in-depth analysis, while the intervention of artificial intelligence (AI) technology offers a possibility for overcoming these bottlenecks. This paper focuses on the specific paths and real challenges of AI-enabled improvement of financial reporting quality. At the path level, the paper discusses four dimensions: strengthening the foundation through data governance, preventing errors through automated accounting, enhancing reliability through intelligent auditing, and improving relevance through in-depth analysis. At the challenge level, the paper analyzes obstacles at three levels: data and algorithm credibility, organizational responsibility and talent, and regulatory compliance and ethics. Finally, the paper proposes optimization strategies such as building a credible data foundation, developing interpretable models, reshaping the responsibility framework, and cultivating interdisciplinary talent, pointing out that AI empowerment is a systematic project requiring the coordinated evolution of technology, management, and systems.