Generative AI is quickly becoming a daily productivity engine, but it also introduces new security and governance challenges. Shadow AI, inconsistent controls across tools, and fast-evolving AI stacks can create gaps that increase the risk of sensitive data exposure and policy violations.
Join this webinar where we’ll build on Zscaler’s internal Zero Trust journey and show how to apply Zero Trust principles—continuous verification, least-privilege access, and strong data protection—to secure employee use of AI tools with consistent controls across locations, devices, and users. We’ll also cover how to gain visibility into AI usage and reduce risk with policy-driven protections that help prevent data leakage and support governance.
Key takeaways:
How a Zero Trust architecture helps reduce AI-related risk while supporting productivity for hybrid users
Practical ways to secure employee use of generative AI with data protection controls that minimize leakage
How to strengthen protections for sensitive resources (“Crown Jewels”) with verified user and posture-based access
Approaches to improve visibility into AI usage (including shadow AI) and reduce blind spots with consistent policy enforcement
How integrations and automation can speed detection and response when AI-related activity increases security risk
Senior Director, IT Infrastructure
Zscaler
Senior Manager of Product Marketing
Zscaler