Open Innovation AI is heading to GISEC Global 2026, 16–18 September, joining the cybersecurity community to explore one of the defining challenges of the next era of AI: how do we make increasingly autonomous AI systems secure?
As AI moves beyond assistants toward agents that can access enterprise knowledge, connect to systems, call tools, and take action, the security landscape is changing with it.
At GISEC, our focus will be on what organizations need to build and operate AI securely while maintaining sovereignty, governance, and control.
AI Changes the Security Perimeter
Traditional cybersecurity protects infrastructure, networks, identities, applications, and data.
AI introduces new risks across another layer.
Models can contain vulnerabilities. AI applications can expose sensitive information. Retrieval systems can surface data to the wrong users. Agents can interact with APIs, enterprise systems, and other agents, potentially taking actions rather than simply generating answers.
As AI systems become more autonomous, securing the infrastructure underneath them is no longer enough.
Organizations also need to understand:
- Which models and AI components they can trust
- What data AI systems are allowed to access
- What actions agents are permitted to take
- How systems respond to adversarial inputs
- How AI behavior is governed and monitored in production
Security can no longer be added at the end. It needs to be designed across the AI lifecycle.
Securing AI Across the Lifecycle
Open Innovation AI addresses this challenge through two complementary parts of its AI Fabric.
Agent Fabric is our enterprise platform for building and orchestrating multi-agent workflows. It enables organizations to connect agents to enterprise knowledge, models, tools, and systems while maintaining control over how those agents operate.
As these systems become more capable, they also need security that extends beyond the application layer.
Security Fabric is designed to secure AI across the entire lifecycle, from the models and components entering the environment to the applications and agents running in production.
It brings together model scanning, AI red teaming and evaluations, runtime guardrails, and live monitoring to help organizations identify vulnerabilities, test AI behavior, enforce protections, and continuously monitor AI systems once deployed.
Security Fabric can work alongside Agent Fabric or independently, helping organizations protect models, RAG applications, AI agents, and other AI workloads while maintaining the governance and control required for enterprise and sovereign environments.
