Imagine if every time you shared a document, an AI double-checked whether it contained your company’s most valuable secrets—not just obvious identifiers like Social Security numbers, but the subtle stuff, like whether a financial report is the public version or the one with unreleased numbers. In this AI Explainer episode, Ben Kus, Box CTO and Meena Ganesh, Senior Product Marketing Manager for AI, break down the enterprise classification problem, why traditional approaches (and older DLP-style detection) miss what matters most, and how AI-powered classification adds a critical “second layer” beyond permissions—continuously re-checking files as they change. We'll cover: -Why PII isn’t always the most sensitive data -Permissions vs. classification (and why you need both) -How AI detects context and even compound sensitivity (information that’s only sensitive when combined) -Real-world examples, including jet engine information and an evolving smartphone-style document that gets more sensitive over time -How continuous classification can enable safer, freer collaboration—without relying on humans to label everything perfectly

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