How Zscaler secures AI adoption and accelerates AI initiatives

As AI becomes more embedded across the enterprise, from public GenAI tools to private models, pipelines, agents, and supporting infrastructure, security teams need controls that extend beyond traditional app security. They need visibility into how AI behaves across the system.

Zscaler helps organizations secure AI usage with protections that span the AI security lifecycle:

AI asset management
Gain full visibility into AI usage, exposure, and dependencies across applications, models, pipelines, and supporting infrastructure (ex: MCP pipelines), including AI bills of material (AI-BOM) to discover your full footprint and identify risks.

Secure access to AI
Enforce granular access controls for AI applications and users. Inspect prompts and responses inline to ensure safe and responsible use of AI apps by preventing sensitive data from being sent to external models or returned in unsafe outputs.

Secure AI applications and infrastructure
Protect the AI systems enterprises are building and deploying, not just the tools employees use. This includes hardening systems and enforcing runtime protections with vulnerability detection across models and pipelines, adversarial red team testing, and securing against common and evolving threats like prompt injection, data poisoning, and unsafe use of sensitive information.