AI Audit Training: Governance, Risk Management & Ethical AI Auditing Techniques

Master AI Governance, Mitigate Risks, and Ensure Ethical Auditing Excellence

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AI Audit Training: Governance, Risk Management & Ethical AI Auditing Techniques

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Course Overview:

This AI Audit Training for AI Governance and Risk is designed to empower internal auditors with the tools and knowledge to assess and audit AI-driven systems, ensuring compliance with governance frameworks and AI audit practices. The course will focus on AI Risk Assessment Tools, Audit Compliance, and applying AI auditing techniques to evaluate the ethical, regulatory, and security challenges that come with machine learning and automation technologies. Participants will also explore AI risk control strategies, AI model risk management, and data privacy in auditing.

Target Audience:

IT Auditors and Compliance Professionals
Risk Management and Governance Leaders
Data Scientists and AI Development Teams
Cybersecurity Professionals
Internal and External Auditors focusing on AI Systems
IT/AI Consultants specializing in Audit Practices

Targeted Organizational Departments:

Internal Audit & Assurance
Risk Management & Compliance
IT Governance & Cybersecurity
AI and Data Science Teams
Finance & Regulatory Reporting
Legal and Ethics Committees

Targeted Industries:

Financial Services & Banking
Healthcare & Pharmaceuticals
Technology & Telecommunications
Government & Public Sector
Manufacturing & Engineering
Professional Services & Consulting

Course Offerings:

By the end of this course, participants will be able to:

Effectively conduct AI audits in compliance with AI Governance frameworks
Identify and mitigate risks related to AI Governance and Ethics
Evaluate AI model risk management practices and assess AI compliance with regulatory standards
Conduct bias, fairness, and privacy assessments for AI systems
Implement AI Risk Assessment Tools to manage data privacy and security
Understand AI model lifecycle from development to deployment and ensure comprehensive risk controls

Training Methodology:

The course uses a hands-on, practical approach to learning, including:

Case Studies simulating real-world AI auditing challenges
Group Discussions to explore AI governance issues in different sectors
Lab exercises focusing on AI auditing tools and risk management frameworks
Expert-led Sessions to break down AI governance models and practical applications
Feedback and Reflection sessions after each topic to consolidate learning

Course Toolbox:

Digital Workbook with AI audit templates, tools, and best practices
Checklists for AI Governance and Risk Management
Access to case studies and real-world examples of AI audits
AI Risk Control Strategy templates for developing audit protocols
Resource guides on AI audit tools, including those for machine learning and model validation

Course Agenda:

Day 1: Introduction to AI Audit Frameworks

Topic 1: Overview of AI Governance and Risk Management Frameworks
Topic 2: Introduction to AI Audit Compliance and Certification Requirements
Topic 3: Key AI Risk Assessment Tools and Methodologies
Topic 4: Ethical Considerations in AI Auditing
Topic 5: Understanding the Lifecycle of AI Systems (from development to deployment)
Reflection & Review: Reviewing AI Governance and Risk Frameworks for effective auditing

Day 2: AI Governance and Risk Management

Topic 1: AI Governance Structures: Key Roles and Responsibilities
Topic 2: Risk Management in AI: Identifying, Assessing, and Mitigating Risks
Topic 3: Data Privacy and AI Auditing: Ensuring Data Security and Compliance
Topic 4: Audit Controls for AI Systems in the Regulatory Landscape
Topic 5: Exploring Bias, Fairness, and Accountability in AI Systems
Reflection & Review: Evaluating AI Risks and Controls in Organizational Context

Day 3: Advanced AI Risk Assessment Tools

Topic 1: Implementing AI Risk Assessment Frameworks for AI Systems
Topic 2: AI Compliance and Security Tools for Audit Procedures
Topic 3: Using AI Audit Tools for Machine Learning Model Auditing
Topic 4: Practical Case Study: AI Audit of a Healthcare AI System
Topic 5: Advanced Techniques for Identifying and Mitigating AI System Bias
Reflection & Review: Advanced Audit Practices for Ensuring AI System Integrity

Day 4: Model Governance and Risk Control

Topic 1: Managing AI Model Risks: Evaluation and Governance Frameworks
Topic 2: Monitoring and Validating AI Model Behavior and Performance
Topic 3: Role of the Auditor in AI System Design and Monitoring
Topic 4: Auditing AI-driven Decisions and Outcomes for Transparency
Topic 5: Legal and Ethical Considerations in AI Auditing
Reflection & Review: Hands-on Audit Simulation with AI Governance Controls

Day 5: Final AI Audit Simulation and Review

Topic 1: Comprehensive Review of AI Audit Tools and Techniques
Topic 2: Real-World Application of AI Audit in Risk Management
Topic 3: Final AI Audit: Preparing for Real-World AI Auditing Scenarios
Topic 4: Reviewing AI Governance Structures and Internal Controls
Topic 5: Preparing Your AI Audit Report: Best Practices and Reporting Standards
Reflection & Review: Final Q&A and Actionable Insights for Implementing AI Audits

FAQ:

What specific qualifications or prerequisites are needed for participants before enrolling in the course?

Participants should ideally have experience in IT auditing, risk management, or a related field. Familiarity with AI technologies and basic auditing frameworks is recommended.

How long is each day's session, and is there a total number of hours required for the entire course?

Each session lasts approximately 4-5 hours, including breaks and interactive activities. The entire course spans five days with a total of 20-25 hours of instruction.

Can AI Auditing Tools Be Used in Real-Time Auditing?

Yes, AI auditing tools can be integrated into live environments for continuous monitoring, providing auditors with real-time insights into the performance and risks of AI models.

How This Course is Different from Other AI Audit Courses:

This course uniquely combines the latest AI governance and risk frameworks with practical tools and techniques for auditing AI systems. Unlike other programs, it emphasizes the application of real-world auditing skills, using case studies and hands-on exercises to ensure participants can audit AI models and systems effectively. It also integrates industry-recognized frameworks, providing participants with a well-rounded understanding of AI audit practices.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Location	Dates	Duration	Mode	Price
Athens	Week 20, 2026 17 - 21 May 2026	5 Days	Onsite	€6,700
Vienna	Week 21, 2026 18 - 22 May 2026	5 Days	Onsite	€5,700
Milan	Week 22, 2026 25 - 29 May 2026	5 Days	Onsite	€5,700
Dubai	Week 22, 2026 25 - 29 May 2026	5 Days	Onsite	€4,500
Doha	Week 22, 2026 31 May - 04 Jun 2026	5 Days	Onsite	€5,500
Barcelona	Week 25, 2026 15 - 19 Jun 2026	5 Days	Onsite	€5,700
London	Week 25, 2026 15 - 19 Jun 2026	5 Days	Onsite	€5,700
Dubai	Week 25, 2026 21 - 25 Jun 2026	5 Days	Onsite	€4,500
Madrid	Week 26, 2026 22 - 26 Jun 2026	5 Days	Onsite	€5,700
Jakarta	Week 26, 2026 28 Jun - 02 Jul 2026	5 Days	Onsite	€5,700
Baku	Week 28, 2026 06 - 10 Jul 2026	5 Days	Onsite	€5,000
Kuwait	Week 28, 2026 12 - 16 Jul 2026	5 Days	Onsite	€5,500
Rome	Week 32, 2026 03 - 07 Aug 2026	5 Days	Onsite	€5,700
Seoul	Week 34, 2026 17 - 21 Aug 2026	5 Days	Onsite	€10,000
Amsterdam	Week 36, 2026 31 Aug - 04 Sep 2026	5 Days	Onsite	€5,700
Zoom	Week 37, 2026 07 - 11 Sep 2026	5 Days	Online	€1,500
London	Week 38, 2026 14 - 18 Sep 2026	5 Days	Onsite	€5,700
Dubai	Week 38, 2026 14 - 18 Sep 2026	5 Days	Onsite	€4,500
Cape town	Week 38, 2026 20 - 24 Sep 2026	5 Days	Onsite	€6,000
Dubai	Week 39, 2026 21 - 25 Sep 2026	5 Days	Onsite	€4,500