AI Security Readiness

AI is moving from language to action.
How ready is your organization?

AI systems now retrieve data, invoke tools, and act across enterprise workflows. But most security programs still treat AI like a content problem instead of an execution problem.

Get the enterprise playbook for securing AI across employees, applications, and agents.

Playbook Highlights
  • Traditional model shortfalls
  • New AI exposure surfaces
  • Execution layer defense
  • Unified Defense Plane
Inside the Playbook

What you'll learn

The Enterprise Playbook explains how AI has moved from use to action, where organizations are exposed, and what it takes to secure AI across employees, applications, and agents.

  • Why traditional security models fall short
  • The three new AI exposure surfaces
  • How to secure the execution layer
  • What a unified AI Defense Plane looks like in practice
Learn More↓
Why Readiness Matters

Most organizations are adopting AI faster than they can secure it.

As AI moves from generating output to taking action, risk no longer lives in one place. It shows up across employees, applications, and agents.

+67%
AI security incidents increased as organizations moved from pilots to production agents.
4%
Only a small fraction of organizations report high confidence in their AI security readiness.
99.8%
Threat prevention improves when signals are unified across workforce, applications, and agents.
Readiness is no longer about model safety alone. It is about securing the full AI system.
Where AI Breaks

AI risk concentrates where visibility breaks down.

Most organizations are operating across multiple stages of AI adoption at once. The challenge is not simply using AI safely — it is being ready to discover, govern, and protect how AI behaves across the business.

Employees using AI tools

Employees are already using ChatGPT, Claude, Gemini, copilots, coding assistants, and browser-based AI tools in daily work.

Where it breaks

Sensitive data is shared through conversational interfaces, often without visibility or policy enforcement.

What readiness requires

Visibility into AI use, real-time policy enforcement, and governance at the interaction level.

AI embedded in applications

AI applications dynamically assemble prompts from system instructions, retrieved context, and user input.

Where it breaks

Prompt injection, indirect manipulation, and unintended disclosure emerge inside the application flow, where traditional controls were never designed to operate.

What readiness requires

Inline inspection of prompts, context, and outputs with policy enforcement inside the application itself.

Agents that plan and act

Autonomous and semi-autonomous agents can retrieve data, invoke tools, and execute multi-step actions across systems.

Where it breaks

A single unsafe instruction or manipulated context path can cascade into real operational impact.

What readiness requires

Runtime guardrails that constrain agent behavior based on context, permissions, and expected action.

Start Here

Start with the Enterprise Playbook