Core Insights - Zscaler has introduced new AI security innovations aimed at enabling enterprises to securely build, deploy, and govern AI applications while maintaining visibility and control [1][4] Group 1: AI Security Challenges - Many enterprises lack a comprehensive view of their AI applications and services, which limits their understanding of AI exposure and associated risks [2] - Traditional security models are inadequate for the unique behaviors of AI traffic, which can lead to vulnerabilities; Zscaler's ThreatLabz report indicates that most enterprise AI systems could be compromised in just 16 minutes [2] Group 2: New Innovations and Solutions - Zscaler's AI Security Suite provides a detailed inventory and dependency map of AI assets, enabling organizations to adopt AI technologies more securely [3] - The suite addresses enterprise AI security challenges through three core use cases, focusing on visibility, governance, and secure access [4][5] Group 3: Governance and Compliance - Zscaler supports alignment with frameworks like the NIST AI Risk Management Framework and the EU AI Act, enhancing governance for global AI adoption [6] - The company is expanding its defense capabilities with new features such as a secure automation gateway and AI Deception to counter model-based attacks [6] Group 4: AI Asset Management and Security - AI Asset Management provides comprehensive visibility for CISOs and IT teams to detect shadow AI and prioritize risks [7] - Secure Access to AI enables safe use of sanctioned AI services with Zero Trust controls, while Secure AI Infrastructure protects AI development throughout its lifecycle [7]