Answers
No. AI handles pattern recognition and repetitive screening; auditors apply judgment, investigate exceptions, and sign off on conclusions.
Evidence collection and population-wide triage often change first—teams see fewer blind spots and faster exception routing before expanding into narratives and continuous monitoring.
AI analyzes full transaction populations instead of small samples, reducing the chance that rare but material issues hide between sample items.
Structured reasons for each flag, links to source data, threshold documentation, and logs that support re-performance and file review.
Pilot on one population—journal entries or vendor payments—with conservative thresholds, validate against known exceptions, then expand scope as the team trusts the workflow.
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