Zscaler governs AI usage through its cloud proxy, recently packaged as AI Guard, Secure AI Access, and Zscaler AI Security. The most direct alternatives to their overall solutions are the other large SSE and SASE platforms, which take the same approach. They route traffic through a vendor cloud and run AI security as one module of a broad platform. A different option is purpose-built AI security that runs in your own environment and works at the level of the individual interaction. This guide covers both and is honest about where each fits.
Which Zscaler alternative is right for you?
Best for AI governance and policy enforcement? Verax is the standout if AI security is the focus. With hundreds of dedicated integrations, Verax is able to go far deeper in terms of access controls and DLP functionality. Instead of purely app-level traffic control and basic prompt inspection, Verax goes beyond inspecting each interaction to also detect the plan, model, connectors, and file access in play. And unlike the larger SSE and SASE solutions, your data never leaves your environment, both adding further protection and allowing them to offer predictable per-seat pricing that doesn’t scale with your AI usage. That said, it is not an SSE platform, so for SWG, CASB, and ZTNA you'd keep or choose one of the platforms below.
Best broad SASE platform with AI coverage? Palo Alto pairs Prisma SASE with the broadest AI portfolio here, offering AI Access Security across 6,000+ apps, Enterprise DLP, the Prisma Browser, and Prisma AIRS for agents. If your main goal is consolidation with some AI governance inside it, it's the most complete platform. When it comes to Access Security, however, it either requires an endpoint solution or
Best SSE peer with mature inline DLP and user coaching? Netskope's SkopeAI runs real-time DLP on prompts and responses, coaches users toward approved tools, and scores a large catalog of AI apps, all on the same inline proxy and DLP engine you'd deploy for web and SaaS.
Best for Microsoft 365-only shops? Microsoft governs AI natively through Purview (DSPM for AI, DLP, sensitivity labels), Defender for Cloud Apps (shadow AI discovery), and Entra. It's the deepest option for Copilot and M365. The main disclaimer here is that as a standalone option, Microsoft won’t be the right fit to solve your AI security needs beyond their product suite. If you want to address the other thousands of AI tools out there, even just to block them, you’ll want a more focused AI solution on top of Microsoft’s.
For reference, Zscaler itself is strongest at inline DLP at global scale, browser isolation for AI sites, and the reach of an already-deployed proxy.
How we evaluated
- Purpose-built for AI vs an AI module of a platform.
- Where inspection runs and how deep it sees each interaction (app-level and DLP-match, or per-interaction signals like plan, model, connectors, files).
- Reach into native desktop apps and agents that don't route through a web proxy.
- Deployment footprint and whether it complements or replaces what you run.
Comparison at a glance
Reflects publicly available vendor information as of June 2026, verified against each vendor's documentation.
The main considerations: depth of AI coverage & architecture
For the most part, "Zscaler alternatives" are other SSE and SASE platforms, Palo Alto, Netskope, and Microsoft, and they share Zscaler's model.
If you’re looking to go beyond their main offerings and secure your company’s AI usage, you should know that their offerings are quite limited. Their AI detection is largely app-level and DLP largely prompt-level only. Essentially, they can tell you which AI app is being used, offer basic access controls, and inspect prompt text for sensitive data. That's valuable, especially if you already run the platform.
True AI-usage security requires deeper AI integrations and focus. Going beyond the prompt to recognize any interaction, the account and plan, the model invoked, the connectors accessed, the files involved, and where agents can go. And doing this for 100s of tools, a list which is growing faster every day, That's where Verax is a better fit, and because it can chain off your existing SWG via ICAP, it adds that depth without replacing your platform. Many teams run an SSE platform and Verax together.
How to choose
If you're looking for a new SSE or SASE, this is a far more complex question. But if you’re looking to extend those capabilities to AI usage, you should evaluate Verax and consider running it alongside the platform you already have.
Frequently asked questions
How comprehensive is Zscaler’s AI solution? Their AI detection is largely app-level with prompt-level DLP monitoring and blocking, which is important. But they lack deep access controls or comprehensive DLP monitoring beyond the prompt: file access, agentic usage, connectors, and tier + model monitoring.
What is the best Zscaler alternative for AI security? Among SSE/SASE platforms, Palo Alto and Netskope are Zscaler's closest rivals, with Microsoft as the native option for M365/Copilot shops. For AI security, Verax is the standout, and it can complement an SSE platform rather than replace it.
How is Verax different from Zscaler? Zscaler delivers AI security as a module of its cloud SSE platform, with app-level and DLP-match detection. Verax is purpose-built for AI usage and works more as an AI focused add-on to Zscaler’s existing capabilities by letting you control just about any aspect around your employee’s AI usage.
Can Verax run alongside Zscaler? Yes and this is the most common scenario. Verax can chain off your existing SWG via ICAP or proxy chaining to add deeper AI usage security without replacing your SSE platform.
