PERAN DAN TANTANGAN ARTIFICIAL INTELLIGENCE DALAM KUALITAS PELAPORAN KEUANGAN - A SYSTEMATIC LITERATURE REVIEW

Abstract

This research aims to investigate the roles, benefits, and challenges of implementing Artificial Intelligence (AI) in enhancing the quality of financial reporting. Using the Systematic Literature Review (SLR) methodology, this research analyzes relevant articles related to the research topic obtained from Scopus-indexed academic journals published between 2021 and 2024. The literature selection was carried out based on predetermined inclusion and exclusion criteria, focusing on studies that specifically discuss the application of AI in financial reporting. The analysis results are categorized into five main AI sub-technologies: Natural Language Processing (NLP), Optical Character Recognition (OCR), Predictive Analytics & Machine Learning, Generative AI, and Anomaly Detection. The study finds that AI significantly contributes to improving accuracy, operational efficiency, predictive capabilities, and audit quality in financial reporting. However, several challenges remain, including data security risks, algorithmic bias, regulatory misalignment, infrastructure limitations, and organizational resistance. The findings are expected to provide practical insights for accountants, regulators, and decision-makers, as well as a theoretical foundation for future research on AI adoption in the accounting field.