دور الذكاء الاصطناعي في تطوير النماذج المحاسبية: مراجعة تحليلية

Abstract

This study provides an in-depth analytical review of the role of Artificial Intelligence (AI) in developing accounting models across financial accounting, managerial accounting, and auditing. It examines the structural challenges facing traditional accounting frameworks in light of the rapid technological transformation and the rise of Big Data, highlighting key limitations such as subjectivity in estimates, limited predictive capacity, and the reliance of auditing on post-event sampling techniques. The paper demonstrates how AI techniques— including Machine Learning, Artificial Neural Networks, Deep Learning, and Natural Language Processing— contribute to enhancing the accuracy of accounting measurements, improving fair value estimation, enabling continuous auditing, strengthening fraud detection, and supporting predictive budgeting and cost analysis.

The findings reveal that AI offers significant opportunities to address methodological gaps in conventional accounting by increasing objectivity, enabling real-time monitoring, and transforming accounting into a forward-looking analytical tool. However, the study also identifies major challenges, including explainability issues associated with complex AI models, heightened risks to data security and privacy, and the growing need to equip accountants with advanced competencies in data analytics and technological tools. The study recommends developing flexible accounting standards that incorporate AI-based evidence, updating academic curricula to include data science components, and establishing robust governance and cybersecurity frameworks to ensure the responsible and effective adoption of AI in accounting practice.