Artificial Intelligence in Financial Reporting: A Critical Review of Accuracy, Transparency, and Governance

In 2024 and 2025, Artificial Intelligence (AI) made a rapid debut in financial reporting, promising enhanced reporting efficiency, speed, and transparency. The same period also brought to light a series of outstanding issues: algorithmic bias, data privacy, lack of transparency with regulations, and a lack of easy explanation as to what is being decided by preparers and users. This paper will review the latest literature from peer reviewed journals and institutional repositories, in the following three themes: accuracy, transparency and governance. AI reduces manual errors, automates anomaly detection and facilitates real-time analysis, while NLP and continuous auditing enable disclosures to be more easily scrutinised, the evidence shows. It also reveals that these benefits are undermined by "black box" models, weak regulations and an ongoing reliance on human oversight. The paper recommends three policy options: standardised AI governance, investing in AI literacy and hybrid human-AI reporting models.

artificial intelligence, financial reporting, accuracy, transparency, governance

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