AI Integration in Internal Audit Bundle: Build Confidence in Using and Auditing AI Tools

Essentials for AI Auditing - Course Objectives:

1. Understand the fundamentals of AI, including most commonly used artificial intelligence (AI) model types, tools and applications.
2. Identify risks associated with building AI systems responsibly, including safety, data integrity, privacy, security, and the ‘black box’ nature of AI algorithms.
3. Define internal audit's role in the organization's AI strategy.
4. Consider regulatory compliance and standards associated with the use of AI.
5. Utilize a framework based on IIA and industry best-practices for auditing AI models.
6. Identify controls to mitigate AI risks, including Generative AI (Gen AI).

Essentials for AI Auditing - Course Topics:

1. Introduction to AI:
   • AI Overview - Understanding the fundamentals of AI and its evolution.
   • Establish a solid foundation in AI technology, including:
     • Machine learning models.
     • AI and Gen AI models.
     • Data sources.
     • Types of AI being used and explored in organizations.
2. Risk Management in AI:
   • Risk Identification and Management - Identifying and managing AI model risks and model use risks, such as safety, integrity, privacy, security.
   • Understanding the unique risks posed by the ‘black box’ nature of AI systems.
3. Internal Audit's Role in AI Strategy:
   • AI Strategic Management - Exploring how organizations plan and execute AI strategies, and oversight required.
   • Governance in AI - Understanding structures and processes for AI governance.
   • Role of internal audit - Discussing the role of internal audit in AI governance and the Three Lines Model, while leveraging internal controls in managing AI risks.
   • Integrating AI risk assessment with existing annual/quarterly risk assessments.
4. Regulatory Compliance and Standards:
   • Overview of AI-related regulatory landscape - Exploring AI-related global regulations and industry frameworks.
   • Understanding organization’s policies, processes, and structures for complying with existing and upcoming regulations.
   • International standards for AI auditing.
5. AI Auditing Framework:
   • Overview of the AI Auditing Framework - Understanding the framework and associated domains and risk categories.
   • Applying the AI Auditing Framework through real-world scenarios:
     • Identify potential AI-related risks, assess their significance, and develop audit plans that address these risks effectively.
6. Controls for Mitigating AI Risks:
   • Exploring controls to manage AI model and model usage risks, such as bias, safety, data, privacy, and security.
   • Understanding controls for managing unique risks from the Gen AI models.

Leveraging Artificial Intelligence in Internal Audit - Course Objectives:

1. Identify artificial intelligence tools (AI) to streamline the internal audit process.
2. Establish what types of audit processes can be enhanced by using AI.
3. Consider common pitfalls of using AI in the internal audit process.
4. Discuss advantages and disadvantages of using AI in the internal audit process.
5. Establish what using AI tools in the internal audit process looks like operationally.
6. Create change management for AI transformation.

Leveraging Artificial Intelligence in Internal Audit - Course Topics:

1. Identifying AI Tools for Streamlining the Internal Audit Process
   • Explore the landscape of AI technologies and tools available for internal auditors.
   • Evaluate the suitability of AI tools for specific audit scenarios.
   • Understand how AI can automate routine tasks and augment human expertise in auditing.
2. Types of Audit Processes Benefiting from AI
   • Examine various audit processes, such as financial, operational, compliance, and fraud detection.
   • Identify key areas within each audit process where AI can be integrated for improved results.
   • Develop criteria for choosing the right AI solutions based on audit objectives.
3. Common Pitfalls of Using AI in the Internal Audit Process
   • Recognize potential challenges and risks associated with implementing AI in internal auditing.
   • Explore best practices for data quality, security, and privacy to mitigate risks.
   • Learn how to address ethical and regulatory considerations when using AI.
4. Advantages and Disadvantages of Using AI in the Internal Audit Process
   • Discover the benefits of AI adoption, such as enhanced audit scope, reporting, and insights.
   • Assess the limitations and drawbacks of AI, including the potential for bias and overreliance on technology.
   • Gain strategies for maximizing AI advantages while minimizing disadvantages.
5. Operational Implementation of AI Tools in the Internal Audit Process
   • Delve into the practical aspects of integrating AI tools into your audit workflow.
   • Understand the steps involved in developing a proof of concept - data preparation, model selection, and validation.
   • Managing stakeholder engagement.
   • Examine case studies and real-world examples of successful AI-driven internal audits.
   • Assessing AI tool effectiveness and ROI.
6. Change Management Framework
   • Assess the impact of the change on People, Process, and Technology.
   • Establish a process to make sure the AI technology and associated processes are in compliance with regulatory requirements.