This study investigates the impact of artificial intelligence (AI) on reducing accounting errors from two distinct angles: that of accounting software developers and of certified public accountants. We employ a questionnaire-based approach informed by prior research and validated through pilot testing. Our findings reveal significant benefits for software developers. AI effectively addresses various accounting errors, including tax rate discrepancies, cutoff period inaccuracies, principal violations, concealed transactions, mathematical mistakes, and manipulation errors. However, when considering users, AI’s effectiveness varies. While it successfully mitigates certain errors, such as those related to principles, it falls short in eliminating mathematical errors. This research contributes fresh insights into the role of AI in accounting within emerging markets, enhancing our understanding of its potential and limitations.

The aim of this study is to explore the accounting errors that influence value-added tax (VAT) reporting quality in Lebanon and to identify any additional accounting errors not considered before. The data instrument is a questionnaire; it was developed based on previous studies’ statements (Mat Jusoh et al., 2021), which were validated by a pilot test. The population selected is composed of all 1,691 practising certified public accountants in Lebanon who are registered with the Lebanese Association of Certified Public Accountants (LACPA). The results showed several accounting errors that have a significant influence on VAT reporting quality in Lebanon, including tax rate errors, cutoff period errors, errors of principle, hiding transactions errors, mathematical errors, and overreporting expenses errors. Moreover, the exploratory approach concluded that there are two main problems that influence VAT reporting quality: the unclear procedures for tax reporting and the absence of guidance regarding the extreme fluctuation of exchange rates in Lebanon. This study provides new insight and a better understanding of the accounting errors that influence VAT reporting quality.

In recent years, artificial intelligence has increasingly been interesting for its role in improving accounting practices. This research investigates whether there is a significant difference in value-added tax (VAT) reporting quality between traditional methods and those assisted by artificial intelligence (AI) in emerging markets. The experiment introduces an AI intervention using ChatGPT-4 to analyze data for accounting errors. The results demonstrate that AI-assisted reporting significantly improves reporting quality, as the AI effectively identified accounting errors that were missed in traditional reporting. This study makes a valuable contribution by providing novel, practical insights into the role and capabilities of AI in tax reporting, employing a rarely used experimental methodology to explore this topic.