As accounting firms and financial institutions deploy agentic AI, they face significant governance challenges. This course focuses on cybersecurity, data governance, and risk management practices essential for the safe and effective use of autonomous systems. Participants will examine frameworks such as NIST AI RMF and the CSA's red-teaming guidelines, as well as case studies on AI-powered cyber incidents. The course equips professionals to assess agentic system vulnerabilities, implement controls, and integrate risk insights into enterprise compliance strategies. This course equips CPAs to fulfill their oversight responsibilities in safeguarding financial data and ensuring the reliability of autonomous systems within the enterprise's control environment.
Learning Objectives
- Evaluate key cybersecurity and data risks associated with agentic AI
- Understand global regulatory frameworks relevant to agent deployment
- Apply AI risk management frameworks (e.g., NIST, CSA) to financial settings
- Design oversight and monitoring strategies for autonomous AI systems, integrating them within existing internal control frameworks relevant to CPAs
- Align agent governance with internal controls and assurance reporting
Major Topics
- Cyber risks: prompt injection, drift, model manipulation, data leakage
- Red-teaming and simulation exercises (CSA, IBM frameworks)
- Controls mapping: COSO, SOX, and NIST AI RMF
- Regulatory context: GDPR, CCPA, EU AI Act, SEC guidance
- Platform security discussion and comparisons
