Artificial Intelligence Empowering High quality Audit Rectification: Mechanisms of Action and Path Selection
Abstract
rectification efficiency, insufficient cross subject collaboration, lack of dynamic management and control, and post hoc risk disposal. Leveraging perception, computation, reasoning and prediction capabilities, artificial intelligence reshapes the whole process of audit rectification. This
paper identifies four theoretical effects of AI empowered audit rectification: guidance, multiplication, collaboration and long term effectiveness. It unpacks five core action mechanisms, sorts out practical constraints concerning data, technology, talent, collaboration and regulation,
and proposes implementation paths from the perspectives of platform construction, data mining, human machine collaboration and dynamic
monitoring. This research enriches the theories of digital intelligent audit rectification and provides practical references for audit institutions to
build a digital long term rectification mechanism.
Keywords
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DOI: http://dx.doi.org/10.70711/frim.v4i9.10242
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