AI-Enabled Internal Audit Certificate Program

Course structure

Module 1: Foundations of AI in Internal Audit

• 1.1 What AI Is (and Is Not) for Internal Audit
• 1.2 The AI Technology Landscape for Auditors
• 1.3 How AI Is Reshaping the Profession and the Global Internal Audit Standards
• 1.4 Ethics, Bias, and Auditor Responsibilities with AI
• 1.5 The AI Maturity Spectrum: From Data Analytics to Autonomous Agents
• 1.6 Building Your Personal AI Toolkit for the Internal Audit Function

Module 2: AI-Powered Audit Execution

• 2.1 AI for Risk Assessment and Audit Planning
• 2.2 Continuous Auditing and Monitoring with AI
• 2.3 AI-Assisted Workpaper Documentation and Evidence Analysis
• 2.4 NLP for Contract, Policy, and Document Review
• 2.5 Prompting for Audit Tasks (Risk Identification and Control Testing)
• 2.6 Refining AI Outputs for Accuracy and Relevance
• 2.7 Identifying and Correcting AI Errors and Hallucinations
• 2.8 Documenting AI-Assisted Work to Quality Standards

Module 3: Data, Quality, and Professional Skepticism

• 3.1 Evaluating AI Output: When to Trust, When to Probe
• 3.2 Data-Quality Fundamentals for AI-Augmented Audit
• 3.3 Documenting AI-Assisted Work for Quality Assurance
• 3.4 Managing Over-Reliance and Preserving Human Judgment
• 3.5 The Regulatory and Standards Landscape Governing AI in Assurance

Module 4: Industry Vertical Audit

• 4.1 Financial Services: Credit Risk, Fraud Detection, and Compliance
• 4.2 Healthcare: Operations, HIPAA Compliance, and Revenue-Cycle Integrity
• 4.3 Manufacturing and Supply Chain: Vendor Audits and ESG Assurance
• 4.4 Technology and Cybersecurity: IT Controls, AI Systems, and Third-Party Risk
• 4.5 Government and Public Sector: Compliance, Grants, and Accountability
• 4.6 Energy and Utilities: Resilience and Environmental Compliance
• 4.7 Translating AI Audit Methods Across Sectors

Module 5: AI in Action – Practitioner Use Case Labs

• 5.1 Use-Case Scenarios: Fraud, IT Controls, Vendor Compliance, and ESG
• 5.2 Prompt Engineering for Audit Tasks
• 5.3 Peer Review of AI-Assisted Workpapers
• 5.4 Capstone Project 1: Build a Continuous Audit Exception-Review App Using Replit
• 5.5 Capstone Project 2: Generate and Validate an AI-Assisted Audit Checklist Using Audit Now

Module 6: Leading AI-Enabled Audit Functions

• 6.1 AI Adoption Strategy, Tools, and Governance Frameworks
• 6.2 Building a Team AI Strategy: Upskilling, Tools, Governance
• 6.3 Managing Change, Resistance, and Stakeholder Expectations
• 6.4 Coordinating AI-Enabled Assurance Across the Three Lines in line with Standard 9.5, Coordination and Reliance
• 6.5 Communicating AI-Driven Insights to Audit Committees and Boards