This audit measures whether your professional scepticism remains your own or whether AI tools have become a substitute for your analytical thinking. Your score reveals how much of your audit judgment now depends on accepting AI outputs without independent verification.
Keep a log of instances where the AI's output differed from your independent assessment. After five or ten entries, patterns emerge about where the AI's logic breaks down. These patterns tell you which judgments you must never outsource.
In team meetings, ask junior staff to explain the reasoning behind an AI classification before they look at the AI's explanation. This builds their judgment muscle while the AI is still a learning tool for them, not a replacement for thinking.
When an AI tool flags something as low risk, apply extra scepticism. AI systems are often tuned to minimise false alarms, which can mean genuine risks are classified as routine. Your job is to catch what the AI smooths over.
Require yourself to write a brief narrative for every significant audit decision, explaining your reasoning independent of the AI tool. If you cannot do this without copying from the AI output, you have not yet formed your own judgement.
Every quarter, manually audit a sample of transactions that the AI processed as routine. This is not to check the AI's arithmetic. It is to keep your own skills sharp so you can spot the error patterns that AI misses.