Risk Management: Internal Controls & Fraud Prevention - Part 3 Self-Study Webinar
Overview
As artificial intelligence becomes more embedded in business operations, it is transforming how organizations identify, assess, and manage risk. This self-study webinar explores the intersection of risk management and AI, including the implications of foundation models, generative AI, and emerging agentic systems. Participants will also examine how third-party dependencies and evolving cybersecurity threats are converging with AI adoption, creating new challenges for governance, oversight, and control. You’ll gain insight into:
- How different types of AI technologies introduce new risk considerations
- The growing importance of third-party risk management and SOC reporting in AI-driven environments
- How cyber risks and AI capabilities are converging to reshape the risk landscape
Objective
To provide CPAs and other finance professionals with a practical understanding of AI-related risks and third-party considerations, enabling them to strengthen risk oversight, evaluate emerging threats, and support effective governance in technology-driven environments.
DETAILED LEARNING OBJECTIVES
• Understand the role and structure of AI foundation models
• Evaluate key considerations when selecting AI models
• Identify risks associated with third-party AI vendors
• Differentiate levels of AI risk tolerance and implementation approaches
• Understand characteristics of agentic AI systems
• Recognize challenges in monitoring complex AI systems
• Identify benefits of AI in risk management and fraud detection
• Understand AI applications in predictive modeling and anomaly detection
• Recognize limitations of AI including data silos and integration challenges
• Evaluate ethical and transparency concerns in AI systems
• Understand components of third-party risk management programs
• Identify tools used to assess third-party controls including SOC reports
• Differentiate between SOC 1 and SOC 2 reports
• Understand enhancements introduced under SSAE 18
• Recognize trust services criteria used in SOC 2 reporting
• Identify key categories such as security, availability, and confidentiality
• Understand emerging AI-related cyber threats such as prompt injection
• Recognize risks associated with data poisoning in AI systems
• Evaluate risks posed by adversarial AI technologies
• Understand vendor dependency and lock-in risks
• Assess the intersection of AI and cybersecurity risk management
• Recognize the importance of governance across the AI lifecycle
• Understand monitoring and control requirements for AI-driven systems
• Evaluate enterprise risks arising from AI adoption
Emphasis
- The intersection of risk management and AI, including:
– Foundation models
– Generative AI
– Agentic AI - Third party risks and SOC reports
- The convergence of cyber risks and AI in 2026
Speakers
Rosemary Ferrero, CPA
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