Rethinking AI Data Security: A Practical Buyer's Guide
🛡️ Generative AI is now central to enterprise work, but rapid adoption has exposed gaps in legacy security models that were not designed for last‑mile behaviors. The piece argues buyers must reframe evaluations around real-world AI use — inside browsers and across sanctioned and shadow tools — and prioritize solutions offering real-time monitoring, contextual enforcement, and low‑friction deployment. It warns against blunt blocking and promotes nuanced controls such as redaction, just‑in‑time warnings, and conditional approvals to protect data while preserving productivity.
