Auditing AI: Hands-On for Internal Auditors
By the end of this course participants will gain the expertise, tools, and accreditation needed to effectively audit AI systems. The course covers the implementation of governance, management, and internal audit policies specific to AI. Auditors will gain proficiency in upholding AI governance through adherence to compliance regulations, overseeing AI implementations, and performing data audits, including the assessment of Large Language Models (LLM). The curriculum includes an advanced workshop where participants practice applying an AI audit framework to a real-world business scenario, concentrating on the auditing of AI services in the operational and financial sector.
Course Information
Price:
Duration:
Certification:
Exam:
Learning Credits:
Continuing Education Credits:
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Prerequisites:
The following is recommended before attending:
- A fundamental understanding of AI
- Familiarity with the IIA AI Framework
- Review the NIST AI RMF
- The IIA beginner course: Essentials for AI Auditing
Target Audience:
Who should Attend:
- Internal Auditors or anyone in an internal Compliance role.
Course Objectives:
Learners who attend this course will have a clear understanding of the following:
- Understanding AI and Generative AI Services: Explore key concepts and differences between AI and Generative AI, including hands-on workshops for practical experience.
- Auditing AI Applications: Learn the duties and tasks of AI Auditors, how to examine AI systems, measure data quality, and ensure transparency and responsibility.
- Reviewing Auditing Roles: Gain insights into auditing data and models used by AI applications, and assess fundamental abilities needed for examining AI applications responsibly and ethically.
- Implementing AI Auditing Policies: Administer AI auditing policies to carry out effective governance, management, and internal auditing administration.
- Designing Governance for AI Applications: Apply AI governance compliance policies and manage AI and Gen AI management processes for operational best practices.
- Auditing Data and AI: Manage AI applications and audit data and the LLM life cycle, including classifying data and auditing AI applications with advanced tools.
Course Outline:
Learning Path 1: Explore cutting-edge AI and optimized AI Auditing
- These module lessons help you explore nuances in artificial intelligence including Generative AI, and how they are implemented. They also teach you an auditor's responsibilities and how to efficiently audit AI.
Module 1: Exploring AI and Generative AI Services
This lesson will have you explore the key concepts and differences of AI and Generative AI. Hands-on-workshop
- Advanced insights into AI and machine learning.
- Exploring Generative AI.
- Walkthrough examples of Generative AI and Real-World foundational LLM.
Module 2: How to Audit the intricate components of AI applications:
This lesson covers the duties and tasks that AI Auditors need to perform. Hands-on-workshop
- How to examine the AI system
- Measuring Generative LLM Data Quality.
- Ensuring Transparency and Responsibility.
- Reviewing and classifying the data and models
Module 3: Reviewing Auditing Roles in the AI Landscape
This lesson will teach you how to audit the data and models that AI applications use. Hands-on-workshop
- Assessing fundamental abilities needed to examine AI applications responsibly and ethically. (Recommend IIA introductory level Audit Course)
- Assessing the ability to evaluate model degradation, data and model accuracy, risk and bias, and compliance responsibility
- Learning How AI applications can help auditors enhance their work through advanced prompt engineering.
Learning Path 2: Implementing the AI Auditing Policies
- These module lessons will teach you how to administer the AI auditing policies defined in your framework to carry out the governance, management, and internal auditing administration effectively by completing hands-on workshops.
Module 4: Investigating internal AI usage – Governance:
In this lesson, you will discover how oversight and monitoring work in an auditing investigation of AI utilization. Hands-on-workshops.
- Learn how to Assess and measure usage utilizing systems of auditing.
- Track results utilizing systems of auditing.
- Evaluate and ensure adherence utilizing systems of auditing.
Module 5: Execute AI Project Management efficiently:
This lesson will show you how to audit an enterprise well by understanding the organization’s AI vision and strategy.
- Exploring how AI affects the enterprise through frameworks utilizing systems of Project management.
- Examine how AI is applied strategically within an enterprise utilizing systems of Project management.
- Learn how to utilize business intelligence to drive AI decision-making. Hands-on-workshops.
Module 6: Exploring AI's Effect on Auditing – Internal Audit:
This lesson will teach you how an auditor can prepare and conduct audit assignments utilizing modern services. Hands-on-workshops.
- Evaluating the AI application in practice by Microsoft Copilot.
- Assessing the interactions with the AI application by Microsoft Copilot and Microsoft Purview.
- Examining mistakes, prejudices, and irregularities utilizing Microsoft Purview.
Learning Path 3: Managing The AI Landscape with Strong Governance
- These module lessons will teach Auditors how to implement governance, management, and internal AI audits.
Module 7: Designing Governance in NEW AI and Gen AI Applications
In this lesson, you will learn how to apply AI governance compliance policies. Hands-on-workshops.
- Applying AI Governance standards and policies.
- Implementing AI Governance through compliance rules.
- Configuring AI Governance by enabling equity, dependability, security, and confidentiality processes.
Module 8: Administering NEW AI and Gen AI Platform Management Processes
In this lesson, you will learn how to administer AI and Gen AI management processes. Hands-on-workshops.
- AI operational best practices for Auditors' role in improving performance.
- AI best practices for the Auditor's role in improving security.
- How to effectively collaborate Auditor & IT administrator governance.
Module 9: Auditing NEW AI and Gen AI with Purview Advanced AI Governance Capabilities
This lesson will teach you how to perform an internal audit of AI applications. Hands-on-workshops.
- Reviewing AI activities as an advanced auditor.
- Advising on AI application design, and development
- Advising on AI applications deployment, pre and post-monitoring, and efficacy as an advanced auditor.
Learning Path 4: Auditing Data and AI with AI Hub & Audit
- These module lessons will teach you how to manage AI applications and audit data and the LLM life cycle. Hands-on-workshops
Module 10: Classifying data and auditing AI applications
- Managing generative AI applications, Copilot
- Evaluating AI application with AI Hub Purview
- Governing data classification and AI applications with Audit in Purview
Capstone Final Event:
- In this last lesson, you will apply learned processes to audit AI services by completing a business case study.
Business Case Study: Operation or Financial
The case study includes the following assets:
- Business processes.
- Present Regulatory Framework.
- Present Approach to Management.
- Requirements for Internal Audit.
- Auditor Presentation.
- Facilitator preferred solution.
Addendum: Practitioners Guide and Glossary
- Detailed guide on AI auditing concepts
- Glossary of AI applications concepts
