Artificial intelligence and financial statement transparency: The moderating role of accounting information systems’ reliability

This paper will analyze how artificial intelligence (AI) technologies, expert systems, automated learning and neural networks affect transparency of financial statements via voluntary disclosure. It also examines the moderating relationship between these relationships through the reliability of the accounting information systems (AIS) and specifically focuses on the small and medium-sized enterprises that are functioning in the emerging economies. The research design adopted a quantitative and cross-sectional design where 375 respondents were used to gather data through a structured questionnaire. Six hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM), which tested the effects of variables on each other both directly and through the moderating variables. The conceptualization of AIS reliability was in the form of a higher-order construct, which consists of five dimensions, namely, availability, security, confidentiality, integrity, and privacy. The comparison shows that the three AI methods have a strong impact on voluntary disclosure with neural networks having the biggest influence with automated learning and expert systems coming second. AIS reliability moderately positively relates to expert systems and voluntary disclosure, and neural networks and voluntary disclosure; its moderating facilitation effect on automated learning was not meaningful. These findings affirm that AI-based transparency relies on the reliability and stability of the accounting systems. It adds to the empirical data based on an emerging-economy setting and builds on the theoretical knowledge of the impact of technological reliability on the regulation and performance of AI in accounting disclosures.