Artificial Intelligence (AI) is rapidly transforming modern businesses, offering unparalleled opportunities for innovation and efficiency. However, this growth also brings about new security challenges, as identified by McKinsey, which reported that 78% of organisations are now leveraging AI in at least one business function.
This is a significant increase from 55% two years ago. In response, the 2025 Thales Data Threat Report notes that 73% of these organisations are allocating funds towards AI-specific security tools. Thales has launched foundational features of its AI Security Fabric aimed at securing both the core and edge of corporate AI ecosystems.
Thales AI Security Fabric: Safety across AI-powered functions
The Thales AI Security Fabric is designed to safeguard Large Language Model (LLM)-powered applications, data, and identities.
By implementing these tools, organisations can:
- Unlock AI-driven growth securely by balancing innovation and risk. This includes threats, such as prompt injection, data leakage, model manipulation, and exposure of sensitive or regulated data.
- Ensure comprehensive protection of data, applications, and identities by providing controlled dataset access for Agentic AI and GenAI, deploying runtime security in cloud and on-premises settings, and securing all AI interactions with minimal integration complexities.
- Use enterprise-grade, standards-aligned security that directly addresses crucial OWASP Top 10 risks, averting costly or reputation-damaging incidents before they occur.
Initial capabilities unveiled by Thales
Among the first abilities now released is AI Application Security, designed to safeguard proprietary
Among the first capabilities now released is AI Application Security, designed to safeguard proprietary applications that employ LLMs. This solution offers real-time protection against AI-specific threats, such as prompt injection, jailbreaking, system prompt leaks, and model denial-of-service attacks. It provides adaptable deployment options, suitable for cloud-native, on-premises, or hybrid environments.
Additionally, AI Retrieval-Augmented Generation (RAG) Security offers the ability to identify and secure sensitive enterprise data prior to integration into retrieval-augmented applications. Comprehensive data protection solutions, including encryption and key management, help secure communication between the LLM and external data sources.
Securing the future of AI applications
“As AI reshapes business operations, organisations require security solutions tailored to the specific risks posed by Agentic AI and Gen AI applications,” said Sebastien Cano, Senior Vice President of Thales’ Cyber Security Products Business.
“Thales AI Security Fabric offers enterprises specialised tools to secure AI applications while minimising operational complexity. Supported by decades of security expertise, Thales enables businesses to confidently scale their AI adoption, safeguarding sensitive data, applications, and user interactions.”
Future enhancements in AI security fabric
Looking forward to 2026, Thales intends to enhance its AI Security Fabric with new runtime security features, such as data leakage prevention, a Model Context Protocol (MCP) security gateway, and comprehensive runtime access control.
These advancements aim to bolster data flow protection, secure agentic AI data access, and ensure consistent, regulatory-compliant management of interactions across users, models, and data sources. Further details or trials of these tools can be accessed through the Thales AI Security Fabric Website.
