5 Audit Tasks You Should Automate Today
Start your AI automation journey with these five high-impact, low-risk audit tasks that deliver immediate value.
Not sure where to start with AI automation? You don’t need to transform your entire audit function overnight. Start with tasks that are high-volume, rule-based, and time-consuming—areas where AI delivers immediate, measurable value.
Here are five audit tasks you can automate today.
1. Expense Report Policy Testing
The manual way: Sample 25-50 expense reports, pull supporting documentation, manually check each against policy thresholds, document exceptions.
The automated way: AI scans every expense report from the period, automatically flags policy violations (meals over $75, missing receipts, duplicate submissions), and generates an exception report with supporting details.
Why automate this first:
- High volume of transactions
- Clear, rule-based criteria
- Low risk of false positives affecting operations
- Immediate time savings (hours → minutes)
Expected outcome: Full population testing instead of sampling, with documented evidence of every exception and non-exception.
2. Terminated User Access Reviews
The manual way: Get termination list from HR, request access reports from IT, manually compare dates, identify stragglers, follow up on each.
The automated way: AI matches termination dates against access logs across all systems, immediately identifies any access that wasn’t revoked within your policy window (e.g., 24 hours), generates a remediation list.
Why automate this first:
- Critical security control
- Binary logic (terminated = no access)
- Easy to validate results
- High-stakes finding if exceptions exist
Expected outcome: Continuous monitoring capability that catches access control gaps before they become audit findings.
3. Three-Way Match Verification
The manual way: Sample purchase orders, match to receiving documents and invoices, verify quantities and amounts, document discrepancies.
The automated way: AI performs three-way matching across your entire AP population, identifies mismatches in quantities, prices, or receiving status, and categorizes exceptions by type and materiality.
Why automate this first:
- Straightforward matching logic
- High transaction volumes
- Direct link to financial statement assertions
- Quantifiable error rates
Expected outcome: Comprehensive testing of the procure-to-pay cycle with clear metrics on match rates and exception categories.
4. Journal Entry Testing
The manual way: Define testing criteria (round numbers, after-hours entries, unusual accounts), query the GL, review entries meeting criteria, investigate selected items.
The automated way: AI applies your risk criteria to the entire journal entry population, scores entries by risk factors, identifies unusual patterns or outliers, and presents high-risk items for your review.
Why automate this first:
- Required by auditing standards (especially for fraud risk)
- Complex criteria that benefit from computational power
- High volume makes sampling inadequate
- Pattern detection is AI’s strength
Expected outcome: Risk-ranked journal entries with anomaly explanations, enabling focused investigation on truly unusual items.
5. Contract Compliance Monitoring
The manual way: Read contract terms, track deliverables and deadlines in spreadsheets, manually verify compliance, chase down documentation.
The automated way: AI extracts key terms from contracts (dates, deliverables, pricing, SLAs), monitors for compliance against actual performance data, alerts you to upcoming deadlines or breaches.
Why automate this first:
- Contracts contain unstructured data (AI handles this well)
- Manual tracking is error-prone
- Proactive monitoring prevents issues
- High value for vendor and customer agreements
Expected outcome: Automated compliance tracking that catches issues before they become disputes or audit findings.
Getting Started
You don’t need to automate all five at once. Pick one based on:
- Pain level: Which task consumes the most time today?
- Data availability: Where is your data cleanest and most accessible?
- Stakeholder interest: Which area would your audit committee most like to see improved?
Start small, prove value, then expand. That’s the path to sustainable AI adoption.
The Bigger Picture
These five tasks share common characteristics:
- Rule-based with clear criteria
- High volume benefiting from full population testing
- Time-consuming when done manually
- Low risk of AI errors causing downstream problems
Once you’ve mastered these, you’re ready to tackle more complex scenarios—risk assessments, control evaluations, and predictive analytics.
But it all starts with one automated task that proves AI can work for your team.
Related Reading
- Accelerating SOX ITGC Testing with AI — See AI-powered control testing in action
- Automating Expense Reimbursement Audits — Step-by-step guide to expense audit automation
Ready to automate your first audit task? Request a demo and see results in your first week.