The Certified Lead Internal AI Auditor (CLIAIA) program prepares professionals to conduct internal audits of AI-enabled systems. Participants learn to evaluate internal control frameworks, build AI risk registers, and design audit plans. The program emphasizes AI governance, risk, and compliance. It is ideal for those involved in corporate or government AI audit practices. This course supports the development of risk-based audit strategies and prepares individuals for external AI audits. Designed by industry experts, the program balances regulatory knowledge with practical tools. Graduates will be ready to lead AI internal audit initiatives across sectors.
Audience:
- Internal audit professionals
- Risk and compliance officers
- AI governance specialists
- Corporate audit teams
- Government audit personnel
- Quality assurance managers
Learning Objectives:
- Understand AI-specific internal control frameworks
- Build and manage AI risk registers
- Plan and execute internal AI audits
- Prepare for third-party and regulatory AI assessments
- Align AI compliance programs with organizational goals
Program Modules:
Module 1: Foundations of Internal AI Auditing
- Introduction to AI auditing
- Role of internal auditors in AI systems
- AI compliance vs. traditional IT compliance
- Regulatory landscape overview
- Audit readiness assessments
- Key success factors for internal AI audits
Module 2: Internal Control Frameworks for AI
- Mapping AI to existing frameworks
- COSO, COBIT, and ISO alignment
- Designing AI-specific control activities
- Control testing strategies
- Reporting AI control deficiencies
- Updating controls for evolving AI models
Module 3: Building and Managing AI Risk Registers
- Risk identification in AI systems
- Classifying AI risks (data, algorithm, outcome)
- Prioritizing AI risks
- Linking risks to controls
- Using heatmaps for AI audit planning
- Risk monitoring techniques
Module 4: Internal AI Audit Planning and Execution
- Risk-based audit scoping
- AI system walkthroughs
- Interviewing developers and stakeholders
- Documentation review techniques
- Sampling AI transactions
- Writing audit observations and recommendations
Module 5: Preparing for External AI Audits
- Aligning internal audits with external requirements
- Gathering AI audit evidence
- Working with third-party auditors
- Addressing regulatory inquiries
- Maintaining AI audit trails
- Post-audit follow-up actions
Module 6: Governance, Ethics, and Continuous Improvement
- AI governance structures
- Ethical considerations in AI audits
- Bias and fairness auditing
- Data privacy and security compliance
- Reporting to boards and committees
- Continuous audit and improvement cycles
Exam Domains:
- AI Governance and Internal Audit Alignment
- Risk Identification and Control Assessment
- AI Audit Planning Methodologies
- Regulatory Readiness and Reporting
- AI Risk Mitigation Strategies
- Ethics and Organizational Audit Integration
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, and project-based learning, facilitated by experts in the field of AI auditing. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification:
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified Lead Internal AI Auditor (CLIAIA).
Question Types:
- Multiple Choice Questions (MCQs)
- True/False Statements
- Scenario-based Questions
- Fill in the Blank Questions
- Matching Questions (Matching concepts or terms with definitions)
- Short Answer Questions
Passing Criteria:
To pass the Certified Lead Internal AI Auditor (CLIAIA) Certification Training exam, candidates must achieve a score of 70% or higher.
Advance your audit career. Enroll in the CLIAIA program today and lead the future of AI compliance.