AI Risk Map for Accountants 

Date: 5/26/2026
Time: 12:00 PM - 2:00 PM EST
CPE Credit: 2 hours

This course provides a concise overview of the key risks, controls, and governance frameworks that accountants must master as AI reshapes audit, tax, and advisory services in 2025. Drawing on the latest global research, you will explore data-privacy breaches, algorithmic bias, model drift, cybersecurity threats, and audit-trail gaps, then map them to emerging standards such as the EU AI Act, NIST’s AI RMF, and ISO/IEC 42001. Through case-based discussion, you will learn how to embed human-in-the-loop oversight, design robust internal controls, and prepare assurance engagements that keep innovation aligned with professional ethics and public trust.
 
Topics Covered:
1. The 2025 AI risk landscape for accounting professionals
2. Regulatory frameworks: EU AI Act, NIST AI RMF, ISO 42001
3. Data governance, confidentiality, and privacy impact assessments
4. Detecting & mitigating algorithmic bias and fairness issues
5. Model lifecycle management: drift monitoring & explainability techniques
6. Cybersecurity, adversarial attacks, and third-party vendor due diligence
7. Human-in-the-loop oversight, internal controls, and AI assurance engagements
 
Learning Objectives:
By the end of this course, participants will be able to:
1. Identify principal AI risk domains affecting accounting practice.
2. Compare global regulatory and assurance frameworks governing AI use.
3. Assess data-governance controls that protect confidentiality and integrity.
4. Detect and mitigate algorithmic biases in AI-driven accounting tools.
5. Monitor model performance and explain AI outputs to preserve auditability.
6. Design cybersecurity and vendor-risk controls for AI implementations.
7. Recommend governance structures that embed human oversight and accountability.
 
 
Prerequisite Knowledge:
Familiarity with core accounting principles and basic IT control concepts is recommended.
 
Field of Study: Information Technology