AI-Ready Infrastructure: How to Assess Enterprise AI Readiness and Resilience

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Nearly 90% of organizations now use AI in at least one business function. Meanwhile, security breaches involving AI tools have risen 61% year over year, according to IBM’s 2026 Cost of a Data Breach Report. Beyond targeting the vulnerabilities created by enterprise AI adoption, attackers are also using AI to execute attacks faster and more effectively. This double-edged sword of AI risk forces security teams to ask two connected questions: how can we protect the AI in our environment from exploitation, and how can we prevent AI-powered attacks from spreading? The solution is building an AI-ready network, designed to enforce granular controls for internal AI tools and stop AI-speed attacks in real time. We’ll share a framework for benchmarking AI readiness and best practices for strengthening AI resilience at the architectural level. - What is AI resilience? AI resilience is an organization’s ability to withstand and continue operating through an AI-related compromise, whether that’s an AI-accelerated attack or exploitation of internal AI tools and agents. Resilience against AI threats depends on a network architecture designed to contain compromises at the point of entry, making the speed of an attack irrelevant.

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