Most companies do not have a complete overview of the AI applications and services being used within their organization. This includes GenAI tools, AI development environments, embedded AI in SaaS, models, agents, and underlying infrastructure. This lack of visibility limits their ability to gain insight into AI exposure, data access, and risks. At the same time, organizations struggle with controlling access to applications and workloads and enforcing policies. This is because AI traffic shifts to new protocols and non-human patterns that traditional security tools cannot manage. Furthermore, new threats such as prompt injection and model manipulation are not addressed by traditional Red Teaming and posture management.

The new innovations from Zscaler provide companies with a comprehensive inventory and dependency map of their AI footprint, including GenAI services, embedded AI in SaaS, AI development environments, MCP servers, agents, models, and AI infrastructure. These solutions correlate asset discovery, access relationships, data lineage, runtime behavior, and security posture. This allows organizations to implement AI faster while maintaining security, governance, and control.

'AI is changing the way companies operate,' says Jay Chaudhry, CEO, chairman, and founder of Zscaler. 'Traditional security approaches are not designed to secure AI. Therefore, business leaders are looking for a total solution - not more disparate products. At Zscaler, we provide the security needed to help leaders move forward with confidence and embrace the full spectrum of AI. We are not only securing the AI era, we are accelerating it.'

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A revolution in AI security for three use cases

The new Zscaler AI Security Suite addresses the security challenges of AI within companies in three crucial ways:

• AI Asset Management provides CISOs, IT, and governance teams with a comprehensive inventory of AI apps, models, infrastructure, agents, and usage. This helps them detect hidden AI, understand what data is being processed by AI, and prioritize risks by providing insight into AI usage.
• Secure Access to AI helps security architects and IT administrators enable approved AI services securely with zero trust controls, inline inspection, and rapid classification to reduce data loss and misuse while maintaining productivity.
• Secure AI Infrastructure and Apps enables application teams to protect AI development throughout the entire lifecycle with automated AI red teaming, rapid security measures, runtime security mechanisms, and continuous risk assessment; from build to runtime.

'The industry is currently facing a huge lack of insight, as AI traffic does not behave like traditional web traffic,' says Zeus Kerravala, Principal Analyst at ZK Research. 'It is faster, non-human, and uses protocols that most security systems simply cannot detect. This is not just about a new security tool, but about the shift to a zero trust framework that truly understands the context of an AI conversation. Without this level of deep inspection and automated security mechanisms, companies are effectively going blind into the most significant technological transition of our time.'

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Governance, partnerships, and additional controls

To simplify the global adoption of AI, Zscaler is now also supporting customers in aligning their security programs with frameworks such as the NIST AI Risk Management Framework and the EU AI legislation. This governance is accompanied by CXO-level reporting on the use of GenAI and deep ecosystem integrations with OpenAI, Anthropic, AWS, Microsoft, and Google. Additionally, Zscaler is expanding its defense capabilities with a new MCP gateway for secure automation with AI Deception, to divert and neutralize cybercriminals seeking to compromise AI models.

Read the blog 'Accelerating AI Initiatives with Zero Trust' for more information on the latest developments in the Zscaler AI Security Suite.

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