ARTIFICIAL INTELLIGENCE AND CLOUD ACCOUNTING SYSTEMS: REPORTING RELIABILITY AND CYBERSECURITY
DOI:
https://doi.org/10.55640/Abstract
This article examines the implementation of artificial intelligence and cloud-based accounting information systems to improve the reliability of financial reporting and ensure cybersecurity in the context of the digital transformation of the economy. The study is based on a systematic analysis of scientific literature and draws on sociotechnical systems theory, enabling a comprehensive assessment of the interaction of technological, organizational, and human factors. It has been established that the integration of AI and cloud solutions facilitates the automation of accounting processes, improves the accuracy of financial data, and reduces the risk of fraud. However, the effectiveness of their implementation directly depends on the level of digital maturity of organizations, personnel training, and the quality of regulatory frameworks. It is concluded that a balanced implementation of these technologies is necessary, taking into account the socioeconomic specifics of Uzbekistan.
References
1.The Law of the Republic of Uzbekistan "On Cybersecurity" was adopted by the Legislative Chamber on February 25, 2022. Approved by the Senate on March 17, 2022. April 15, 2022, No. ZRU-764
2.Aisyah, P. N., & D. P., R. T. (2025). Artificial Intelligence and Cloud-Based Accounting Information Systems: Enhancing Financial Reporting Reliability and Cybersecurity in the Digital Era. Jurnal Ekonomi Dan Bisnis Digital, 4(3), 203–222. https://doi.org/10.55927/ministal.v4i3.14519
3.Ionescu , L. (2021). “Big Data Analytics Tools and Machine Learning Algorithms in Cloud-based Accounting Information Systems,” Analysis and Metaphysics 20: 102–115. doi: 10.22381/am2020217.
4.ALNAIMAT M.A., Korsun I., Lutsenko K., Khodorkovskyi O., & Artemchuk M. Artificial Intelligence in Accounting: Revolutionizing Financial Management in the Digital Landscape // Theoretical and Practical Research in Economic Fields. — 2025. — Vol. 16, No. 1 (33). — pp. 130–141. DOI:10.14505/ tpref.v 16.1(33).11
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