Securing Cloud AI: Real-World Scenarios in AWS, Azure, and GCP
Join our cloud security team as they dig into real-world exposures tied to popular AI-based services. Learn how to find the gaps to make AI more secure for your organization's cloud infrastructure.
Deploying AI into production infrastructure is no longer optional. It's happening across organizations, often faster than security teams can keep up. But with that speed comes risk: misconfigured permissions, exposed endpoints, and unmonitored data flows that can turn a promising AI initiative into a liability.
In this webinar, our experts will walk through common AI deployment scenarios across AWS, Azure, and GCP, examining what typically goes wrong and how to fix it. Rather than discuss abstract theory, we'll dig into real-world exposures tied to popular AI-based services so your team can find the gaps.
Key takeaways:
- Understand the most common security gaps in AI deployments across AWS, Azure, and GCP
- See real-world examples of how AI services can be exposed or misconfigured
- Learn practical steps to lock down permissions, data access, and endpoints for AI workloads
- Gain a framework for evaluating the security posture of AI services before adopting them
- Walk away with actionable recommendations you can apply to your own environment
Join Paul Burkeland, Force Cloud Security Practice Lead; Edwin David, Senior Security Consultant; Mike Felch, Principal Security Consultant; and Fatima Ghani, Security Consultant to learn how to make AI work for your organization’s cloud infrastructure while prioritizing security. If you’re an IT manager, sysadmin, or developer, don’t miss your chance to gain insights from our experts and learn where the risks really reside. You’ll leave with the insight needed to make informed, confident decisions about how your organization builds and secures AI systems. Register today!