Zscaler unveils new AI security tools for enhanced data safety

Zscaler has announced new artificial intelligence (AI) security capabilities and AI-powered innovations aimed at supporting businesses in enhancing data security and preventing cyberattacks.

The newly introduced features are designed to help organisations adopting AI technologies overcome key challenges, such as protecting proprietary information and ensuring ongoing regulatory compliance.

The Zscaler platform connects users, devices, and data across distributed environments and leverages what the company refers to as the largest inline security cloud globally. According to Zscaler, this system processes more than 500 trillion security signals daily, forming the basis for its AI engines to deliver precise threat detection and automated security measures.

Recent AI-focused solutions by Zscaler are intended to tackle the complexities encountered when deploying advanced AI tools within large-scale and geographically dispersed environments. The company states that these new capabilities increase precision, facilitate automated threat neutralisation, and promote collaborative workflows by unifying users, applications, devices, clouds, and branches.

The latest solutions made available for customers include AI-powered data security classification, which now uses AI trained to mirror human intuition in identifying sensitive content. This feature expands to recognising over 200 content categories and moves beyond traditional regular expression matching to identify previously unrecognised sensitive data. According to Zscaler, this granularity allows for more comprehensive data security posture assessments in less time.

The company also announced enhanced generative AI protections with expanded prompt visibility. Zscaler's new capability reportedly gives organisations greater control over generative AI applications, such as Microsoft CoPilot, by allowing advanced prompt classification and inspection. Using these enhancements, organisations can block prompts that conflict with policies and leverage existing data loss prevention features to protect sensitive data while ensuring compliance within AI-driven workflows.

AI-powered segmentation is being introduced, with what Zscaler describes as a user-to-application segmentation AI automation engine. This tool aims to simplify application management, application grouping, and segmentation processes by factoring in user identity, potentially streamlining security segmentation workflows and helping organisations improve their security posture more rapidly.

Another addition is the AI-powered Zscaler Digital Experience (ZDX) Network Intelligence. With this capability, network operations teams can benchmark and visualise internet and regional ISP performance, identify last-mile and intermediate provider outages, and analyse multi-path flow data to optimise connections to Zscaler data centres and applications. Zscaler says this leads to greater reliability and improved performance. Additionally, the tool is designed to detect, isolate, and analyse disruptive ISP issues such as packet loss, supporting faster remediation via routing adjustments and offering the potential for cost savings in ISP negotiations.

Adam Geller, Chief Product Officer at Zscaler, said: "Zscaler is redesigning the boundaries of enterprise security by advancing AI-driven innovations that address the complex challenges of today's digital age. With industry-first capabilities like AI-driven threat detection and automated segmentation, we empower organisations to adopt and scale AI responsibly and securely. These advancements not only neutralise emerging threats but accelerate collaboration and operational efficiency, allowing businesses to capitalise on the transformative power of AI with confidence and precision."