Module 1
AI Risks in Auditing Firms: Awareness and Accountability
Learning Objectives:
- Identify the different types of risks associated with AI use in auditing
- Understand how these risks impact audit quality, ethics, and compliance
- Recognize key areas where AI may compromise or support audit objectives
Topics Covered:
- Types of AI used in audit (data analytics, automation, GenAI tools)
- Risk categories
- Connection to auditing standards
Practical Examples
Interactive Element
Module 2
Why an AI Policy is Essential: Safeguarding Quality and Ethics
Learning Objectives:
- Understand the rationale behind developing an AI policy
- Explore stakeholder expectations and governance principles
- Learn how a policy supports professional judgement and public interest
Topics Covered:
- Why a policy is non-negotiable in audit firms using AI
- Legal accountability and audit trail requirements
- Roles of firm leadership, engagement partners, and staff
- AI governance principles: fairness, transparency, explainability, and auditability
- The risk of unmanaged AI tools (shadow AI use)
Practical Examples
Interactive Element
Module 3:
Explaining the AI Policy and Real-World Implementation
Learning Objectives:
- Break down the structure and key elements of a good AI policy
- Apply policy guidelines to audit engagements
- Understand controls, monitoring, and documentation procedures
Topics Covered:
- Purpose and scope
- Definitions and prohibited uses
- Approval and registration of AI tools
- Risk assessment procedures
- Human oversight and review responsibilities
- Documentation, monitoring, and reporting
- Integration with firm policies (independence, data governance, training)
- Alignment with IRBA expectations and quality management standards
Practical Examples
Interactive Element
