Using AI for SOX Testing Self-Study Webinar
Overview
Artificial intelligence is creating new opportunities to enhance the efficiency, effectiveness, and scalability of SOX compliance and internal control testing. This self-study webinar provides a practical framework for understanding AI technologies, establishing governance and risk management practices, and evaluating how AI can be applied within SOX programs and financial reporting environments. Participants will explore emerging regulatory perspectives, responsible AI principles, and real-world use cases that demonstrate how AI can support testing, documentation, risk assessment, and internal control monitoring. You’ll gain insight into:
- Foundational AI concepts, governance principles, and considerations for responsible adoption within compliance and assurance functions
- Regulatory and professional guidance related to AI, including perspectives from the IIA, PCAOB, and Center for Audit Quality
- Practical AI applications for SOX testing, risk assessment, internal controls, and audit readiness
Objective
To provide CPAs and other finance professionals with a practical understanding of how AI can be applied to SOX testing and internal control activities, enabling them to evaluate governance considerations, identify appropriate use cases, strengthen risk management practices, and support effective compliance and assurance processes.
DETAILED LEARNING OBJECTIVES
• Define artificial intelligence (AI) and distinguish among machine learning, deep learning, generative AI, and large language models
• Identify the key elements necessary to build trustworthy and responsible AI
• Explain the importance of governance in AI adoption and deployment
• Recognize common AI applications within finance, accounting, and SOX environments
• Describe current regulatory, legal, and standards-based developments affecting AI
• Identify risks associated with AI-enabled controls and understand key auditor considerations related to AI usage
Emphasis
- Definition and evolution of AI
- How organizations approach AI:
– Necessary conditions to build trustworthy AI
– Why adoption should start with governance
– Responsible use and identifying the right use cases - Risk and governance considerations:
– Defining enterprise IQ around the Responsible AI framework - Applications in finance and accounting
- Regulatory insights:
– Institute of Internal Auditors (IIA) AI Auditing Framework
– Perspectives from the Center for Audit Quality and PCAOB - Illustrative AI use cases in SOX:
– Testing enabler
– Query response generator
– Intelligent process walk-through bot
– 10-K analysis of financial reports for financial risk - Risk-based assurance framework and relying on AI-enabled internal controls:
– What to expect from your auditors
– Responding to identified risk
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