When an employee installs an AI writing assistant, connects a coding copilot to their IDE, or starts summarizing meetings with a new browser tool, they are doing exactly what a productive employee should do: finding faster ways to work. Across most organizations today, employees are running three to five AI tools on any given day. Most were never reviewed by IT. A significant portion connects to corporate data through OAuth tokens or browser sessions, giving them access to shared drives, emails, and internal documents the employee never specifically intended to expose. Security teams often have no visibility into any of it. This is the shadow AI gap, and it is widening fast. Most security tools were built to monitor email and network traffic flowing through the corporate network. A browser-based AI tool that connects to company data through a quick login approval bypasses those controls entirely, because it never passes through the corporate network at all. According to Gartner, 69% of organizations suspect or have confirmed that employees are using prohibited AI tools at work, and only 37% have an AI governance policy in place. The result is a growing disconnect between how employees work and what security teams can see. A program that channels AI adoption into a safe, visible, approved path gives security teams the visibility they need and employees the tools they want. The five steps below show exactly how to build one. A security program can only manage what it can see. The first step is discovering which AI tools are in use across the organization, and most security teams will find the answer surprising. Three areas account for the majority of shadow AI activity. A simple employee survey is also worth running. A survey framed around helping employees work more safely tends to get candid responses. Many shadow tools surface through surveys that automated discovery misses entirely. The goal of this step is a current, accurate inventory: every AI tool in us