Аннотация
In the context of rapidly growing data volumes and stricter auditing requirements, artificial intelligence technologies–particularlyArtificialNeuralNetworks(ANNs)–arebecomingincreasinglyrelevantintheauditing field. This study investigates the impact of expert systems, machine learning methods, and intelligent agents on audit quality.The empirical data were collected through a structured questionnaire survey conducted among accounting and auditing consulting firms located in Astana, Aktobe, Atyrau, and Aktau. A purposive sampling methodwasappliedtodeterminethesamplesizeof375respondents.Thecollectedprimarydatawereanalyzedusing descriptive statistics and Ordinary Least Squares (OLS) regression analysis.The findings reveal a significant positive correlation between the use of expert systems, machine learning, intelligent agents, and audit quality. The application of ANNs enhances the quality of audit reporting and is expected to become a dominant trend in the coming decades, as intelligent systems increasingly take over decision-making tasks.The study recommends continuous training for accountants and auditors in ANN methodologies to improve auditquality.Furthermore,auditingfirmsareadvisedtoinvestinmachinelearningtoolsandexpandtheuseof intelligent agents to assist in classifying audit objects across different categories.