AI in Financial Reporting
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The rapid integration of Artificial Intelligence (AI) is fundamentally transforming financial reporting, offering unprecedented opportunities to overcome the inefficiencies, costs, and error vulnerabilities inherent in traditional manual systems. Utilizing a qualitative methodology based on a systematic thematic review of secondary academic and industry literature, this study investigates the impact of AI technologies—specifically machine learning, natural language processing, and data analytics—on corporate reporting practices. The findings reveal a significant upward trajectory in corporate AI adoption between 2018 and 2024. Organizations utilizing these technologies report substantial improvements, including accelerated reporting cycles, enhanced data accuracy, and superior capabilities in fraud detection and predictive forecasting. Despite these quantifiable benefits, the research highlights critical ongoing challenges such as data quality dependence, algorithmic opacity (the "black box" effect), and cybersecurity risks. Ultimately, this paper concludes that while AI serves as a powerful catalyst for operational efficiency and analytical depth, it is not a substitute for human expertise. To ensure the reliability and integrity of financial disclosures, AI must be deployed as a complementary tool, firmly guided by professional judgment, ethical oversight, and robust regulatory frameworks.
Keywords
Algorithmic Transparency, Artificial Intelligence (AI), Automation, Corporate Governance, Financial Reporting, Fraud Detection, Machine Learning, Predictive Analytics