Artificial Intelligence (AI) is increasingly being incorporated into financial reporting, sparking considerable interest among researchers and practitioners. This research explores the impacts of AI-powered tools, such as machine learning (ML), natural language processing (NLP), robotic process automation (RPA) and deep learning, on accuracy, efficiency, and compliance in financial reporting practice in modern firms. Through an integration of empirical research, practitioner surveys and benchmarking analyses, this study shows that AI-enhanced financial reporting ecosystem improves material misstatement rates by 79% on average, shortens period-end close times by 55-81%, and dramatically enhances compliance with regulatory frameworks. It also highlights key adoption constraints such as cost, skills gap, bias, privacy and data quality issues. The research concludes with a visionary model and policy considerations for financial CFOs, auditors and regulators preparing to navigate inevitable consequences of AI-driven financial ecosystems.
Mathur, A. (2026). Impact of Artificial Intelligence on Financial Reporting Accuracy and Efficiency. International Journal of Innovations & Research Analysis, 06(01(II)), 99–106. https://doi.org/10.62823/IJIRA/06.1(II).8793
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