AI technology rapidly advancing modern business offers revolutionary potentials alongside growing security concerns. Data from a recent McKinsey report reveals that 78% of organizations integrate AI into at least one area of their operations, a significant increase from 55% two years prior. In response, 73% of these companies are investing in AI-focused security measures.
Thales is contributing to this demand by introducing the initial phase of its AI Security Fabric aimed at bolstering the security of enterprise AI systems.
Key Features: Thales AI Security Fabric
The Thales AI Security Fabric is designed to enhance the security of applications powered by large language models (LLMs), data, and user identities.
This new offering aims to enable organizations to securely leverage AI-driven innovations by addressing threats like data leakage, model manipulation, and exposure of sensitive information. Additionally, it promises comprehensive end-to-end protection for data, applications, and identities.
New Capabilities to Secure AI
The initial capabilities of the Thales AI Security Fabric include:
- AI Application Security: This solution protects custom applications utilizing LLMs, offering real-time defense against AI-specific threats such as prompt injection, jailbreaking, and system prompt leakage. It also supports deployment across various architectural settings, including cloud, on-premises, and hybrid environments.
- AI Retrieval-Augmented Generation (RAG) Security: Designed to discover and protect sensitive data before its integration into retrieval-augmented applications, this tool ensures robust data protection through encryption and key management, enhancing the security of communications between LLMs and external data sources.
Addressing Risks of Agentic and Gen AI
Thales responds to the unique security needs posed by Agentic AI and Gen AI applications
With the evolving AI landscape, Thales responds to the unique security needs posed by Agentic AI and Gen AI applications. Sebastien Cano, Senior Vice President of Thales’ Cyber Security Products Business, emphasized, “As AI reshapes business operations, organizations require security solutions tailored to the specific risks posed by Agentic AI and Gen AI applications.”
He further suggested that Thales AI Security Fabric provides the necessary tools to safeguard AI applications while reducing operational complexities.
Future Expansion of AI Security Fabric
By 2026, Thales aims to fortify its AI Security Fabric further with advanced runtime security features, including data leakage prevention, a Model Context Protocol (MCP) security gateway, and comprehensive runtime access control.
These enhancements are poised to enhance protection across data interactions, enforce secure data access, and bring unified governance over exchanges between users, models, and data. For more information or to explore these solutions, visit the Thales AI Security Fabric website.
AI is one of the fastest-growing technologies in the history of modern business, with the ability to revolutionize industries, optimize operations, and drive innovation, but it is also introducing security gaps, risks, and vulnerabilities.
According to McKinsey, 78% of organizations are using AI in at least one business function, up from 55% two years ago. As a result, 73% of them are investing in AI-specific security tools, either with new or existing budgets, according to the 2025 Thales Data Threat Report. Thales is introducing the first foundational capabilities of its AI Security Fabric to protect the core and edge of enterprises' AI ecosystems.
Thales AI security fabric–safeguarding LLM-powered apps, data, and identities
With Thales AI Security Fabric, organizations will be able to:
- Unlock AI-driven growth securely: Maximize AI’s business value by enabling innovation and expansion while mitigating risks such as prompt injection, data leakage, model manipulation, and exposure of sensitive or regulated data.
- Protect data, applications, and identities end-to-end: Provide Agentic AI and GenAI with controlled dataset access, deploy runtime security across cloud and on-premises environments, and safeguard all AI interactions with minimal integration effort.
- Rely on enterprise-grade, standards-aligned protection: Leverage proven security capabilities that directly address the most critical OWASP Top 10 risks and prevent costly or reputation-damaging incidents before they impact the organization.
The first capabilities available now are:
- AI Application Security: a security solution designed to protect homegrown applications that use LLMs. Providing real-time protection for AI-specific threats, including prompt injection, jailbreaking, system prompt leakage, model denial-of-service attacks, sensitive information leakage, and content moderation. With flexible and seamless deployment options to fit any architecture, whether cloud-native, on-premises, or hybrid environments.
- AI Retrieval-Augmented Generation (RAG) Security: provides the capability to discover and secure sensitive structured and unstructured enterprise data before it is ingested into retrieval-augmented applications with comprehensive data protection solutions, including encryption and key management. Helps secure communication between the LLM and external sources of data.
Agentic AI and Gen AI applications
“As AI reshapes business operations, organizations require security solutions tailored to the specific risks posed by Agentic AI and Gen AI applications,” Sebastien Cano, Senior Vice President of Thales’ Cyber Security Products Business, said.
“Thales AI Security Fabric offers enterprises specialized tools to secure AI applications while minimizing operational complexity. Supported by decades of security expertise, Thales enables businesses to confidently scale their AI adoption, safeguarding sensitive data, applications, and user interactions.”
AI Security Fabric in 2026
Thales plans to expand its AI Security Fabric in 2026 with new runtime security capabilities, including data leakage prevention, a Model Context Protocol (MCP) security gateway, and end-to-end runtime access control.
These features will strengthen protection across data flows, secure agentic AI data access, and ensure unified, compliant management of interactions between users, models, and data sources. See more information or get trials and access to some of these tools at the Thales AI Security Fabric Website.
