From backlog to breakthrough: Using AI in privacy work and governing it across the enterprise

IAPP Women's Leadership Network Web Conference

Broadcast date: 17 September 2026

Time: 08:00–09:00 PDT, 11:00–12:00 EDT, 17:00–18:00 CEST

Privacy and compliance workloads are growing faster than the teams behind them — and AI now sits on both sides of that equation: a tool that can help clear the backlog, and a technology your program is increasingly being asked to govern. This session takes on both, blending hands-on enablement with a broader conversation about where the role is heading.

On the practical side, you'll see how general-purpose AI tools (like Claude and ChatGPT) can act as a force multiplier for routine, high-volume work — third-party vendor research, data map reviews, DSAR triage and response drafting, and contract clause analysis — through live demonstrations and ready-to-use prompt templates you can take with you. Throughout, we keep sight of the guardrails: what AI gets wrong in a privacy context, and the human-in-the-loop checkpoints that keep your work defensible.

The session also features a candid discussion about how AI is reshaping the compliance function itself — what it takes to update a program for AI, why governance increasingly demands technical fluency and surfaces the gap between what contracts promise and what's actually feasible, how to onboard a flood of new AI vendors fast enough to capture their value, and what "AI ethics" really means once you move past the buzzword.

No technical background required — just bring your curiosity, your biggest backlog, and your hardest questions about where this is all heading. 

Key takeaways:

• A repeatable when-to-use-AI framework for your privacy workflow — so you can save hours a week on routine tasks while keeping compliance rigor intact.
• Hands-on prompt templates purpose-built for high-volume privacy work: vendor due diligence, data map reviews, policy and DSAR templates, and contract clause analysis — yours to take and use.
• The guardrails that keep outputs defensible — what AI gets wrong in a privacy context and the human-in-the-loop checkpoints that protect you.
• A practical view of how to evolve your compliance program for AI — from building an AI use inventory (including shadow AI) to the policies, controls, and faster vendor-onboarding lanes the moment demands.
• A clearer grip on the new dimensions of the role — the technical literacy AI governance now requires, the gap between what contracts promise and what's feasible, and a working definition of AI ethics that goes beyond compliance.