Russian Federation
The paper examines the transformation of a key audit category — assessment of materiality — under the in ence of artificial intelligence (AI) technology. The goal of this study is to comprehensively analyze the new opportunities and systemic risks arising from the integration of machine learning and natural language processing algorithms into the auditor’s professional judgment on materiality. As a result, the main capabilities of AI were identified, and critical risks were systematized. A conclusion has been reached that the most effective model is a hybrid one, in which AI acts as a powerful tool for preliminary analysis and data filtering, while the final judgment on materiality, consideration of qualitative factors, and decision-making remain with the auditor.
audit materiality, artificial intelligence, machine learning, professional judgment, audit procedures, risk, sampling, ISAs
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