AI Governance for Audit & Accounting
AI-assisted audit procedures that satisfy professional standards.
Big Four and mid-market accounting firms are rapidly adopting AI for audit procedures. They need infrastructure that satisfies professional standards requiring auditors to document their work and exercise professional skepticism.
REGULATORY CONTEXT
The professional standards landscape
When auditors use AI to assist with audit procedures, professional standards still require:
| Standard | Requirement | AI Challenge |
|---|---|---|
| SOX Section 404 | Documentation of internal control testing | Prove AI-assisted tests actually occurred |
| PCAOB AS 1215 | Audit documentation requirements | Workpapers must support conclusions |
| ISA 315 | Risk assessment procedures | Document how AI identified risks |
| AICPA AU-C 230 | Audit documentation | Sufficient appropriate audit evidence |
The question regulators will ask:
When your AI identified these anomalies, how do you know your audit team actually exercised professional judgment rather than just accepting the AI's conclusions?
THE CHALLENGE
Your AI analyzed thousands of transactions. Can you prove the auditor actually reviewed the results?
AI dramatically improves audit efficiency—anomaly detection, document review, sampling optimization. But professional standards don't change just because AI is involved.
The documentation gap
- AI identifies 47 anomalies requiring follow-up. How do you document that follow-up actually occurred?
- The AI recommended a sample size of 25. Can you explain why that was appropriate?
- Your engagement team used AI to assess revenue recognition risk. Where's the evidence of professional judgment?
The workpaper problem
- Traditional workpapers document human work
- AI-assisted procedures need workpapers that document both what the AI did and how humans engaged with it
The consistency challenge
- Different engagement teams use AI differently
- How do you ensure consistent methodology and documentation across your practice?
THE SOLUTION
Infrastructure-level documentation for AI-assisted audit
Deterministic Replay
Reproduce exactly what the AI analyzed, when, and what it concluded—for any audit procedure.
- Complete record of every AI-assisted procedure
- Timestamp, input data, model version, and output for each analysis
- Ability to replay any procedure for peer review or inspection
- Immutable audit trail that satisfies PCAOB documentation requirements
Evidence Packaging
Generate workpaper-ready documentation directly from AI procedures.
- Pre-formatted output for common audit procedures
- Integration with audit management platforms
- Automatic inclusion of methodology documentation
- Version control for procedure modifications
Professional Skepticism Verification
Prove your audit team actually exercised professional judgment—not just accepted AI conclusions.
- Engagement scoring for auditor review of AI outputs
- Detection of rubber-stamping patterns
- Documentation of auditor modifications and overrides
- Time-on-task metrics for meaningful review
Sampling Methodology Documentation
Document why the AI-recommended sample was appropriate for the audit objective.
- Automatic capture of sampling parameters and rationale
- Population characteristics and stratification documentation
- Sample selection methodology explanation
- Statistical validity documentation
Anomaly Investigation Tracking
Track follow-up on every AI-identified anomaly through resolution.
- Workflow for anomaly investigation assignment
- Status tracking through resolution
- Documentation of investigation procedures performed
- Linkage to supporting workpapers
INTEGRATION
Built for audit infrastructure
Audit Management Platforms
- CCH ProSystem
- Thomson Reuters
- Wolters Kluwer
- CaseWare
- Custom platforms via API
Data Analytics Tools
- IDEA
- ACL Analytics
- Alteryx
- Python/R analytics environments
Document Management
- Export to firm document management systems
- Appropriate metadata and classification
- Retention policy compliance
USE CASES
Common audit applications
Journal Entry Testing
AI-assisted anomaly detection with complete documentation of testing procedures, auditor follow-up, and resolution.
Accounts Receivable Confirmation
AI-optimized confirmation selection with sampling methodology documentation and response tracking.
Revenue Recognition Assessment
AI risk assessment for revenue streams with professional judgment documentation and supporting evidence.
Inventory Observation Planning
AI-assisted selection of inventory locations with risk-based rationale documentation.
Analytical Procedures
AI-powered trend analysis with auditor review documentation and expectation development support.
Contract Review
AI-assisted identification of unusual contract terms with auditor evaluation documentation.
FOR FIRM LEADERSHIP
The quality control opportunity
AI-assisted audit creates both risk and opportunity for quality control:
Risk: Inconsistent use of AI across engagements, inadequate documentation, professional skepticism concerns.
Opportunity: Standardized methodology, consistent documentation, demonstrable quality improvement.
CleanAim® provides the infrastructure to realize the opportunity while managing the risk.
Inspection Readiness
| How do you document AI-assisted procedures? | Deterministic replay with workpaper-ready output |
| How do you ensure professional skepticism? | Engagement scoring and modification tracking |
| Is the methodology consistent across engagements? | Standardized procedures with version control |
| Can you reproduce this analysis? | Complete audit trail with replay capability |
PROVEN ARCHITECTURE
Built on validated infrastructure
CleanAim's audit capabilities are built on the same architecture that powers our core platform—proven across 1.1 million lines of production code.
Capture rate
Deterministic replay
Audit score
Event propagation
AI-assisted audit starts with proper documentation.
Learn how CleanAim® provides PCAOB-ready documentation, workpaper integration, and firm-wide deployment.
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