TD SYNNEX Inspire Japan 2026

Securing AI Across Hybrid & Multi-Cloud

AI workloads are increasingly spread across on-premises, private cloud, and multi-cloud environments. This creates new security gaps around visibility, access, data movement, and AI-to-system interactions.
Join us for a practical discussion on securing distributed AI environments beyond traditional perimeter controls.

Agenda

Hybrid AI Blind Spots
Visibility across AI workloads, identities, data, and models.
Why Perimeters Fail for AI
Understanding new access and data-flow risks across distributed environments.
Zero Trust for AI
Protecting workloads, identities, and AI-to-tool interactions with LSS, eBPF, and KubeArmor.
AI Supply Chain Visibility
Using SBOM and xBOM to track components and dependencies.
AI-Specific Risk Surfaces
Securing model access, prompts, data flows, and agent-to-system communication.

Walk away with a practical reference model for evaluating and securing AI environments across hybrid and multi-cloud infrastructure.