Description

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.

Instructor: Cory Ng

Target Audience

CPAs, cybersecurity professionals, internal auditors, IT risk managers, finance leaders implementing AI technologies, CITP/CISA credential holders or aspirants, and professionals interested in the impact of agentic systems for cybersecurity and risk manag

Course 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

Subjects

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