Overcoming AI Risk: Strategies for Understanding and Managing AI Challenges

As artificial intelligence becomes deeply embedded in business operations, it is also emerging as both a target and a tool in the cybersecurity landscape. From deepfakes to data poisoning, and from Shadow AI to unauthorized model training, organizations must proactively address the growing risks that AI introduces to their digital environments.

Join CBIZ Managing Director of Cybersecurity, John Verry, as he breaks down the evolving intersection of AI and cybersecurity risk, helping attendees identify vulnerabilities, implement governance strategies, and prepare for upcoming regulatory obligations. In this session, we’ll examine three key areas of AI risk:

Use Risk – including bias, misinformation, shadow AI, and AI Acceptable Use Policy Development.
Development Risk –  such as bias, data quality, data leakage, and compliance with evolving laws.
Security Risk –  covering adversarial attacks, prompt injection, deepfakes, AI-assisted cyberattacks, and changes to Third-Party Risk Management to limit AI use risk.

Attendees will also gain practical guidance on navigating new compliance expectations, including the EU AI Act, NIST AI RMF, ISO 42001, and state-level legislation—plus best practices for governance, third-party oversight, and AI system monitoring.

Whether you’re in IT, risk, compliance, or security leadership, this webinar will give you the tools to build a cyber-aware AI strategy grounded in accountability and resilience.

Speaker

John Verry, Managing Director, CBIZ

Key Learning Objectives

• Understand the unique cybersecurity risks introduced by AI tools and models across the enterprise.
• Understand Shadow AI risk and how to manage it via your Third-Party Risk Management Program.
• Gain familiarity with global and U.S. regulatory frameworks related to AI risk and governance.
• Discover how to implement practical cybersecurity controls and internal governance processes aligned with AI standards.
• Explore vulnerabilities in AI system design, including prompt injection, data leakage, and adversarial manipulation.
• Leave with a strategic roadmap to strengthen your AI security posture while enabling responsible innovation.