Exploring the Consequences of Intelligent Accounting Process Automation on Earnings Quality, Financial Performance Sustainability, and Firm Value
Keywords:
intelligent accounting, earnings quality, financial performance sustainability, firm value, artificial intelligence, financial reporting., data analyticsAbstract
This study aimed to explore the consequences of intelligent accounting process automation for earnings quality, financial performance sustainability, and firm value from the perspective of accounting, auditing, finance, and financial technology experts in Tehran. This qualitative study was conducted using a thematic analysis design. The participants consisted of 24 senior accountants, financial managers, auditors, accounting academics, and financial technology specialists working in Tehran. They were selected through purposive sampling with maximum variation. Data were collected using semi-structured interviews. Sampling continued until theoretical saturation was achieved; saturation occurred at the twenty-first interview, and three additional interviews were conducted to confirm thematic stability. All interviews were transcribed verbatim and analyzed using NVivo software through open coding, axial coding, and theme development. Credibility was enhanced through member checking, peer review, and constant comparison of codes and categories. Data analysis led to the identification of five main categories: data integration and reduction of human error, improvement of earnings quality and transparency of accruals, sustainability of financial performance through process efficiency and predictability, enhancement of firm value through market trust and reporting quality, and requirements for algorithmic governance and technology risk control. Participants emphasized that intelligent accounting systems, when properly implemented, can reduce financial closing time, improve anomaly detection, strengthen internal controls, increase the usefulness of accounting information, and support more reliable financial forecasting. However, poor data quality, insufficient analytical skills, excessive reliance on algorithms, cybersecurity concerns, and the opacity of machine-based decision rules were identified as major implementation challenges. Intelligent accounting process automation should not be understood merely as a technological upgrade; rather, it represents a strategic transformation in financial reporting, internal control, and managerial decision-making. The findings indicate that the positive effects of intelligent accounting on earnings quality, financial performance sustainability, and firm value become sustainable only when supported by data governance, smart internal controls, professional oversight, and continuous training of accounting personnel.
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