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Security Doctrine

Protecting Customer PII and IP

Classify sensitive categories, PII, financials, source code, trade secrets, and enforce with data-loss-prevention controls and AI gateways so they never reach an external model. What the AI never sees, it cannot leak; what it cannot memorize cannot resurface elsewhere.

5 min read/Written by Perry Luzier/Reviewed

Classification comes first

You cannot protect what you have not defined as sensitive. Classification names the categories that must never reach an external model, the prerequisite for any technical control.

65%
of shadow-AI breaches expose customer PII
IBM, 2025
40%
expose intellectual property
IBM, 2025
17%
of firms can automatically block sensitive uploads
IBM, 2025

Enforce with controls, not hope

Once classified, sensitive data needs technical enforcement, DLP, AI gateways, output filtering, not a policy document employees are trusted to follow under deadline pressure.

Policies do not stop paste

A written policy telling staff not to paste customer data into public AI is necessary but not sufficient, only 17% of firms can technically block it. Pair the policy with runtime controls that actually prevent the upload.

Questions

Frequently asked questions.

Is it safe to use public AI tools with business data?

Only for data you have classified as non-sensitive. Customer PII, financials, source code, and trade secrets should be kept out of public models entirely, enforced with DLP and AI gateways, not just a policy, or routed to a sanctioned, contractually protected tool.

Want this built into your operation?

We install the systems described here as owned infrastructure. Start with a diagnostic of where your business actually loses time and margin.