For Accountantss and Auditors
Protecting Your Judgement: Accountantss Using AI Without Losing Your Edge
When Sage AI or QuickBooks AI flags a reclassification or KPMG Clara identifies a compliance gap, you face a real choice: accept the result or test it yourself. The faster you accept without checking, the quicker your ability to spot errors atrophies. Junior accountants entering practice today may never develop the manual reconciliation skills that taught previous generations to question numbers instinctively.
These are suggestions. Your situation will differ. Use what is useful.
Reverse-engineer the AI result before you sign it
When you approve an AI-generated journal entry or audit conclusion, you are putting your name on reasoning you may not fully understand. Before you sign off on PwC Halo's proposed adjustments or ChatGPT's tax treatment analysis, trace back through the source data yourself. Ask the tool to show you its working. If you cannot explain why the entry is correct to a client or a regulator, you should not approve it.
- ›After Sage AI suggests a reclassification, manually check the original invoices and GL codes before accepting
- ›When QuickBooks AI calculates depreciation, recalculate one asset category by hand to verify the methodology
- ›Request the audit trail from Clara or Halo that shows which journal entries and data points fed into the conclusion
Build deliberate friction into routine tasks
Efficiency is valuable, but speed that bypasses your thinking is dangerous. Design your practice to slow down the moments where you are most tempted to trust the tool without question. Batch reconciliation reviews so you have time to spot patterns instead of rubber-stamping output. Schedule a separate review step where you look at AI-flagged items before they move to the next stage of processing.
- ›Set a rule that no AI-identified variance over a materiality threshold moves to client reporting without your manual review of the source transaction
- ›When using ChatGPT for tax research, compare its conclusion against at least one published ruling or case before applying it to a client's return
- ›Review AI analytics for the first and last transaction in each batch personally, not just the exceptions the tool identifies
Train yourself on the errors the AI is most likely to make
Every tool has blind spots. Sage AI can miss context in narrative fields. QuickBooks AI may misclassify unusual transactions. KPMG Clara sometimes flags low-risk items while missing higher-risk patterns. Study your tools' error patterns over three months of use. Keep a log of results the AI got wrong or where it missed the point. This creates a mental checklist of moments when you need to intervene.
- ›After using Clara for compliance checks, compare its flagged items against actual regulatory findings from previous years to see what it misses
- ›Track which transaction types Sage AI reclassifies incorrectly most often (payroll accruals, inter-company transfers, non-routine items) and manually review those categories first
- ›Test ChatGPT's accounting guidance against your professional standards body's guidance on the same topic to spot where it diverges
Protect junior staff from skipping the foundational steps
Your junior accountants will not develop professional scepticism if they never see a manual bank reconciliation or learn to read a detailed GL report. They will not recognise unusual patterns because they have never stared at a spreadsheet for an hour spotting anomalies by eye. Create a structured programme where junior staff do core analytical work by hand before using AI to speed it up. This builds the judgment that saves you when the tool gets it wrong.
- ›Require juniors to complete at least one full manual year-end close without AI assistance before they use QuickBooks AI on subsequent years
- ›Have them review a sample of transactions personally each week before they run automated AI checks on the full ledger
- ›Pair junior staff with experienced accountants to review what the AI output actually represents before they file or report it
Keep a record of when your judgement overrides the tool
Every time you disagree with an AI conclusion and correct it, you are building evidence that you are still doing the work of a professional accountant. These moments are also your safety record. If a client or regulator questions why a number differs from what the AI suggested, you need to show that the difference came from your deliberate professional judgement. Document the reasoning when you set aside AI recommendations on materiality, provisioning, classification or compliance.
- ›Note the reason and date when you reject or modify a Sage AI or QuickBooks AI suggestion, not just that you did
- ›Keep examples of errors you caught that the tool missed, organised by category (completeness, valuation, classification)
- ›File these records separately so you can show a regulator or client that your sign-off reflects your work, not just the AI's output
Key principles
- 1.If you cannot explain the AI result to a client or explain why you disagree with it, you cannot sign your name to it.
- 2.The speed of AI is only valuable if it frees you to do harder thinking, not if it replaces your thinking entirely.
- 3.Junior accountants who never do manual work will never develop the instincts that catch what the AI misses.
- 4.Professional scepticism is a skill that atrophies the moment you stop using it, and AI makes it easy to stop.
- 5.Your credibility depends on demonstrable judgement, not on how fast you process information.
Key reminders
- When you approve an AI-generated adjustment, ask yourself aloud why it is correct. If you hesitate, investigate before signing.
- Every month, manually recalculate one metric that the AI handles regularly. This keeps your verification skills sharp and catches tool drift.
- Before adopting a new AI feature in your practice, test it on historical data where you already know the correct answer.
- Create a peer review habit where you and a colleague review each other's AI-dependent conclusions once a quarter, not just client deliverables.
- Document one decision per week where your professional judgement diverged from the AI recommendation, and keep the file for audit trail purposes.