The Impact of Artificial Intelligence on Computerized Accounting Systems and Data Analysis

Abstract

This paper examines the impact of artificial intelligence (AI) on computerized accounting systems (CAS) and data analysis, with a particular focus on automation, system integration, reporting, and decision-making. Computerized accounting systems represent the interaction between accounting and information systems, enabling the recording, processing, analysis, and reporting of financial and non-financial information. The integration of AI technologies into these systems is increasingly transforming traditional accounting processes by reducing manual work, improving accuracy, and enabling real-time analysis.

Based on the workshop material, the paper discusses several AI-related technologies that can be implemented in computerized accounting systems, including Machine Learning, Optical Character Recognition (OCR), Intelligent Document Processing (IDP), Natural Language Processing (NLP), Robotic Process Automation (RPA), Business Intelligence (BI), predictive analytics, and virtual finance assistants. OCR and IDP support the automatic extraction and processing of data from invoices, scanned documents, contracts, and other accounting records. API interfaces enable the integration of accounting software with POS systems, ERP modules, and fiscal platforms such as SelfCare, while AI can be used to detect anomalies, identify errors, monitor VAT inconsistencies, and support risk scoring. RPA further facilitates the automation of repetitive rule-based processes, such as transferring payroll data from accounting software to tax reporting platforms.

The study also highlights the role of AI in advanced reporting and data analysis. Through BI dashboards and tools such as Power BI, accounting data stored in databases can be transformed into customized reports that support managerial decision-making. AI-based forecasting and predictive analytics allow organizations to identify trends, anticipate future patterns, and improve financial control. In addition, chatbots and virtual finance assistants can provide immediate answers to accounting-related questions, reducing the need for manual report generation.

The findings suggest that the use of AI in computerized accounting systems offers important benefits, including higher efficiency, improved accuracy, faster reporting, cost and time savings, enhanced decision-making, and stronger internal control. However, implementation also involves challenges, such as initial investment costs, staff training requirements, system integration and maintenance costs, resistance to change, and skills gaps. The paper concludes that AI has significant potential to improve computerized accounting systems and data analysis, especially when supported by reliable data, appropriate infrastructure, and trained accounting professionals.