Project managers have always been responsible for managing risk. That responsibility has not changed, but the nature of risk has.

AI is now embedded across how work gets done: in the tools PMs use, in how teams deliver, and increasingly in the products being built.

Each introduces new and often poorly understood risks that can impact quality, security, compliance, and outcomes.

This session provides a practical, PM-focused view of AI governance, not as a technical discipline, but as an extension of project risk management.

The session focuses on three critical areas every project manager must understand:

- AI used by the PM: where productivity tools can introduce accuracy, confidentiality, and decision risks

- AI used by the team: where AI-assisted delivery (e.g., development, automation) introduces quality, security, and IP risks

- AI embedded in the product: where traditional approaches to testing, validation, and accountability no longer apply

Participants will leave with a clear mental model for identifying where AI is influencing their projects, what risks it introduces, and how to manage those risks within existing project governance practices.

Target audience: Project managers, program managers, PMO leaders, and delivery leaders working in environments where AI is emerging or already in use

Session format: Interactive lecture with facilitated discussion

Preferred duration: 60 minutes (including Q&A)

Level: Intermediate (no technical AI background required)

Technical requirements: Standard presentation setup (screen/projector)