I don’t know how you feel about audit season, but for me, it usually means a lot of tedious reading and repetitive checks. Still, I know this work matters — as CFOs, we’re the stewards of compliance inside our organizations.
And even after years in finance, audits — whether internal or external — can still be stressful, especially for new CFOs or fractional CFOs juggling multiple clients.
Over the past few years, I’ve found that AI can ease some of that pressure — not by automating the audit, but by helping finance teams prepare more efficiently and stay in control.
Through trial and error, I’ve learned where AI genuinely helps and where it doesn’t.
Below are two practical cases you can start using AI to make audit prep less reactive — plus a short list of don’ts, because the last thing any of us wants is to look unprepared in front of the audit team with something we haven’t verified.
In the paid edition, I share the full playbook: detailed prompts, example file structures, and downloadable templates — including an Audit-Ready Checklist and an AI Governance Log — so you can operationalize these ideas safely and confidently.
Two Ways to Use AI to Get Audit-Ready Faster
Case 1: Build Your Private Policy Knowledge Base
Most audit delays come from people not knowing where to find the right rule.
Was it in the delegation matrix, a travel policy appendix, or a local procedure last updated in 2022?
Instead of jumping between folders, PDFs, and old emails, build a private AI knowledge base that centralizes all your internal policies.
Upload your delegation of authority, procurement, travel, expense, and compliance guidelines into a secure project in your organization’s approved LLM — such as ChatGPT Enterprise, Claude Team, Gemini, Perplexity Pro, or Microsoft Copilot.
Once uploaded, you can use AI to navigate faster, compare versions, and spot gaps or contradictions across documents.
Ask focused queries like:
“Summarize all spending approval limits across departments.”
“Highlight where thresholds differ between global and regional policies.”
“List policies that reference outdated procedures or inconsistent terminology.”
This approach turns scattered policy documents into a structured knowledge environment — one that helps new CFOs or finance leaders quickly get up to speed and ensures experienced teams stay aligned on rules that change year to year.
Keep this database ready when your audit begins. It can help you locate clauses instantly, confirm approvals, and demonstrate mastery of your policies under review.
Just remember: always double-check before sharing an answer externally — AI can misread or generalize, so verify responses against the source document.
In the paid edition, I show exactly how to structure this private knowledge base, what documents to include, and how to reduce the likelihood of hallucinations or incorrect answers.
Case 2: Use AI to Flag Anomalies Before Your Auditors Do
Auditors are trained to spot irregularities — you can use AI to do a first pass yourself.
Export a clean dataset from your ERP (AP, T&E, or GL detail) and ask AI to run a quick “pre-audit scan.” Even simple prompts can reveal transactions that deserve a closer look:
“Highlight vendors with duplicate invoice amounts in the last 60 days.”
“Show payments that are 30% higher than each vendor’s usual average.”
If you want to get more advanced, you can also upload multiple months of spending data and ask AI to:
“Identify new vendors added this year and total spend per vendor.”
“Find expense reports with nonstandard or missing descriptions.”
The goal isn’t to replace sampling or statistical testing — it’s to highlight areas worth verifying before your auditors bring them up. You’ll walk into fieldwork with a clearer view of potential findings and stronger explanations ready.
In the paid edition, I show how to build this workflow step by step — from setting up the project in an approved AI tool to documenting results in an AI Governance Log, with sample prompts you can adapt for your own data reviews.
What Not to Do When Using AI in Audit Prep
AI can speed up your audit preparation — but it can also create risk if misused.
Keep these boundaries in place:
Don’t upload confidential data to public models. Use enterprise or sandboxed tools only.
Don’t treat AI outputs as evidence. Auditors need original documentation.
Don’t erase your audit trail. Save prompts and outputs as part of your control documentation.
Don’t assume context. Explicitly share fiscal year, thresholds, and exceptions with the LLM.
Don’t skip human sign-off. AI assists; finance leadership approves.
With those guardrails in place, you’re ready to take the next step: building audit workflows that are faster, more transparent, and fully documented.
In this week’s paid edition, I show how to do it safely using approved AI tools — how to structure your policy knowledge base, run anomaly detection with controls, and document everything through an Audit-Ready Checklist and AI Governance Log.
Closing Thoughts
AI doesn’t change what auditors look for—it changes how efficiently finance teams can prepare.
By combining a single audit-ready knowledge base with structured anomaly detection and disciplined governance, you’ll enter every audit confident, compliant, and in control.
We Want Your Feedback!
This newsletter is for you, and we want to make it as valuable as possible. Please reply to this email with your questions, comments, or topics you'd like to see covered in future issues. Your input shapes our content!
Want to dive deeper into balanced AI adoption for your finance team? Book a consultation!
Did you find this newsletter helpful? Forward it to a colleague who might benefit!
Until next Tuesday, keep balancing!
Anna Tiomina
AI-Powered CFO, Trainer and Advisor