Thales Expands Collaboration with Google Cloud to Help Secure Agentic AI Workflows

Integration enables new protections for communications between AI agents, models, enterprise data, and tools to help control what agents can access, share, and do Thales AI Security Fabric mitigates risks, brings enhanced visibility and policy enforcement to AI-driven workflows on Google Cloud

Thales today announced an expanded collaboration with Google Cloud to help enterprises address emerging security and governance challenges associated with agentic AI, bringing integrated protection, visibility, and policy enforcement to AI-driven workflows on Google Cloud.

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The integration of Thales AI Security Fabric with Google Cloud Gemini Enterprise helps organizations apply security, governance, and visibility across interactions among users, agents, models, and tools in real time.

“Enterprises are moving from AI assistants to AI agents that can autonomously take action, make decisions, and interact with critical business systems. This requires a fundamentally different approach to security,” Eva Rudin, Senior Vice President, Cybersecurity Products, at Thales, said.“By expanding our collaboration with Google Cloud, we are helping organizations build the necessary trust with security and governance as the foundation required for the next generation of enterprise AI.”

As enterprises move beyond AI experimentation and begin deploying autonomous agents at scale, traditional security approaches are struggling to keep pace. Unlike conventional applications that operate within predefined workflows, AI agents can reason, plan, decide and act with other agents dynamically, creating new attack surfaces and governance challenges.

According to industry analysts, securing agentic AI has emerged as one of the most pressing challenges facing enterprise AI adoption, as organizations seek to balance innovation with security, compliance, and trust.

Security Built for the Agentic AI Era
The expanded collaboration between Thales and Google Cloud is designed to help organizations address emerging risks across the agentic AI lifecycle, including prompt injection, sensitive data leakage, unsafe outputs, unauthorized actions, and increasingly complex agent-to-agent interactions.

As enterprises connect AI agents to sensitive business systems and critical data, they create a broader and more dynamic attack surface than traditional security architectures were designed to manage. For example, AI agents tasked with settling insurance claims could exceed their mandate by using personal information from outside approved sources to influence payouts, creating privacy and compliance risks. Thales AI Security Fabric applies controls around agents to keep them within authorized boundaries, limit data access, and block inappropriate actions in real time.

This unified security layer provided by Thales AI Security Fabric works across interactions to help organizations enforce policy, detect AI-specific threats, maintain visibility into agent behavior, and support governance requirements. With this foundation in place, organizations can deploy AI agents to execute legitimate business workflows while mitigating the risks associated with an expanding attack surface.

“Google Cloud helps enterprises move from experimenting with AI agents to deploying them securely across their businesses,” Vineet Bhan, Director of Security and Identity Partnerships, Google Cloud, said. “As agents become more capable and connected to critical data and systems, customers need security and governance built into how they operate. Our work with Thales gives organizations additional capabilities to protect agentic AI workflows and adopt this next generation of AI with greater confidence.”

Core Capabilities of the Thales AI Security Fabric
Thales AI Security Fabric helps organizations securely scale AI by providing visibility and control over how AI systems and agents access data, interact with one another, and take action across the enterprise. It enables businesses to discover and assess AI-related risks, protect sensitive information, help prevent unauthorized or unsafe actions, and ensure AI activity aligns with organizational policies and user intent. Centralized governance and compliance capabilities also give security and business leaders greater confidence to expand the use of AI while maintaining appropriate oversight.

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