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Accounting, Audit & Tax AI Strategy: opportunities, use cases & the operating model
In audit and tax, AI moves the profession from sampling to full-population testing, where anomaly detection, evidence automation, and research synthesis reduce risk while defending margins under pricing pressure.
Where AI creates value
Risk assessment — Full-population anomaly and journal-entry testing
Controls testing — Automated evidence gathering and walkthroughs
Audit sampling — Risk-weighted selection replacing manual sampling
Tax research — Position analysis across codes and rulings
Financial close — Reconciliation, flux analysis, and disclosures
Tax compliance — Return preparation and data validation automation
Top AI use cases
- Full-population journal-entry testing flagging anomalous manual and period-end entries
- Automated control walkthrough documentation and evidence request generation
- Tax research copilots synthesizing code sections, regulations, and case law for positions
- Contract and lease review for revenue recognition and ASC 842 classification
- Flux and variance analysis with auto-drafted narrative explanations for the close
What has to change (operating model)
- PCAOB and AICPA expectations for auditing AI-produced evidence and audit trail
- Independence and confidentiality controls governing client-data model usage
- Reviewer sign-off standards ensuring human judgment on AI-flagged exceptions
- Quality management systems documenting AI tools within the audit methodology
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