What Is an AI Audit?
An AI audit is a systematic review of AI systems and their governance. It evaluates whether AI is being developed, deployed, and operated responsibly and in accordance with policies, regulations, and ethical principles.
AI audits can be internal (self-assessment) or external (independent review). Both serve important purposes in demonstrating accountability.
Why AI Audits Matter
Regulatory Requirements
Regulations like the EU AI Act require conformity assessments. NYC Local Law 144 requires bias audits for hiring AI.
Stakeholder Assurance
Clients, customers, and partners want assurance that AI is being used responsibly. Audits provide independent verification.
Risk Identification
Audits identify risks and gaps that internal teams might miss. Fresh eyes catch problems.
Continuous Improvement
Regular audits drive ongoing improvement in AI governance practices.
What Auditors Look For
Governance Structure
- Policies and procedures
- Roles and responsibilities
- Oversight mechanisms
- Training and awareness
Documentation
- AI system inventory
- Risk assessments
- Design documentation
- Testing records
- Change logs
Technical Controls
- Development practices
- Testing procedures
- Monitoring capabilities
- Incident response
Outcomes
- Performance metrics
- Bias testing results
- Incident history
- Stakeholder feedback
Preparing for an AI Audit
Step 1: Self-Assessment
Conduct your own review first:
- Use our Governance Checklist as a starting point
- Identify gaps before auditors do
- Prioritize remediation efforts
Step 2: Documentation Review
Ensure documentation is complete and current:
- Update AI inventory
- Complete missing risk assessments
- Organize evidence files
- Verify access to historical records
Step 3: Evidence Gathering
Prepare evidence for each control area:
- Policy documents and approvals
- Training completion records
- Meeting minutes and decisions
- Testing and monitoring reports
Step 4: Interview Preparation
Prepare personnel for auditor interviews:
- Brief key personnel on audit scope
- Review roles and responsibilities
- Practice common questions
Step 5: Remediation Plan
Have a plan for addressing findings:
- Prioritization framework
- Resource allocation
- Timeline expectations
Common Audit Findings
- Incomplete AI inventory
- Missing or outdated risk assessments
- Inadequate documentation
- Insufficient testing evidence
- Unclear accountability
- Limited monitoring
Next Steps
Start your audit preparation with our free Governance Checklist. The Documentation System provides the templates you need to close common documentation gaps.