Methodological Framework for Evaluating AI-Driven Digital Transformation in Accounting and Tax Administration
Author : Achilov Salokhiddin Salomovich
Abstract :
This study develops a rigorous methodological framework for integrating artificial intelligence (AI) into accounting and taxation systems using expert evaluation approaches. Based on a systematic review and critical synthesis of recent academic literature, the research refines the conceptual foundations of AI and clarifies its functional role in the digital transformation of accounting practices and tax administration. The study identifies key domains of AI application, including robotic process automation in accounting operations, intelligent accounting information systems, predictive fiscal analytics, and AI-driven virtual assistants supporting tax compliance and reporting. Particular emphasis is placed on expert-based assessment tools—such as Delphi and multi-criteria methods—to evaluate effectiveness, institutional readiness, and digital maturity of AI-enabled systems. The findings demonstrate that AI adoption serves as a systemic driver of digital modernization, enhancing operational efficiency, analytical reliability, transparency of fiscal processes, and adaptability of regulatory mechanisms. The proposed framework contributes to the development of evidence-based, data-driven governance models in public finance and corporate accounting.
Keywords :
Accounting, taxation, artificial intelligence, digital transformation, tax administration, expert evaluation.
