Certified AI Auditor

Overview

The Certified AI Auditor course equips professionals with practical knowledge and skills to assess, audit, and govern AI systems effectively. The course provides a structured approach to evaluating AI risks, ensuring regulatory compliance, and promoting ethical and responsible AI use. It prepares participants to provide independent assurance over AI systems, addressing concerns such as bias, transparency, data integrity, security vulnerabilities, and compliance with evolving regulations.

Prerequisites

A fundamental understanding of AI principles, AI system lifecycle, and audit methodologies.

Target audience

• Internal auditors evaluating controls and technology risks
• External auditors understanding AI-related audit risks
• IT auditors and information security professionals
• Risk and compliance officers managing AI regulations
• Data and AI governance professionals
• Consultants supporting AI risk and compliance initiatives

Objectives

Delegates will learn how to:

• Explain core AI concepts, AI system lifecycle activities, and the role of audit in AI assurance
• Assess AI governance, accountability, risk, ethics, transparency, bias, security, and control environments
• Plan and execute AI audit engagements, including audit objectives, scope, criteria, resources, work programmes, and evidence collection
• Evaluate AI audit evidence and test AI controls, including model cards, system maps, data quality, fairness, performance, robustness, traceability, and monitoring
• Report AI audit findings, communicate conclusions, recommend corrective actions, and verify remediation through follow-up activities

Outline

AI assurance foundations and governance context

• Training course objectives and structure
• Introduction to AI assurance
• AI fundamentals
• AI strategy and decision-making governance
• AI governance, accountability, and organisational oversight
• AI risk landscape
• AI audit universe

AI risk, controls, and audit planning

• AI risk assessment process
• AI control environment evaluation
• AI lifecycle controls
• Risk-based AI audit planning
• AI audit objectives and scope

AI audit engagement design and work programme development

• AI risk and control matrix
• Resource management for AI audits
• Planning the AI audit engagement
• Developing the AI audit work programme

AI audit execution, reporting, and follow-up

• Gathering and evaluating AI audit evidence
• Testing AI controls and model governance
• Audit report preparation
• Communication of findings and conclusions
• Corrective action tracking
• Follow-up and verification

Exams and assessments

Participants will complete a formal certification exam administered by PECB, post course. Certification fees and the exam voucher are included in the course price. Candidates who do not pass on the first attempt may retake the exam once for free within 12 months of the initial attempt. Knowledge checks, exercises, and quizzes are provided throughout the course to reinforce learning and readiness for the certification exam.

Hands-on learning

This course includes:

• Practical exercises based on real-world AI audit scenarios
• Interactive group discussions and case-based simulations
• Workshops on developing and applying AI audit techniques
• Guidance from experienced instructors and access to over 450 pages of supporting materials