Your employee is pasting something into ChatGPT right now

Let's not pretend otherwise.

Right now, while you're reading this, someone on your team is opening a browser tab. They're not going to your enterprise IT portal — they're going to ChatGPT, or Claude, or Gemini, and they're pasting something in.

Maybe it's a client name. A contract paragraph they need summarised. An internal report they're turning into a presentation. A performance review they're struggling to write.

It isn't malicious. It's practical. AI makes them faster, and they know it.

The problem is not that your employees use AI. The problem is where the data goes when they do.

Every piece of text pasted into a consumer AI product is, at minimum, processed by a third party your legal team never reviewed and your data-governance policy almost certainly doesn't cover. At maximum, it's training data. At worst, it's a breach you'll find out about the hard way.

Three responses — and why two of them don't work

A — Block access to consumer AI tools

This is the instinct, and it doesn't work. Employees use their phones, home WiFi, private browsing. The data leaves on a different path — and now you've signaled that you're not helping them do their jobs, so they're less likely to tell you when something goes wrong.

B — Give them an enterprise AI account and log everything

Better — until you read the logs. You'll see what people type when they think it's just them and the machine: performance anxieties, doubts about colleagues, half-formed ideas. Now you have a surveillance problem and a culture problem. Logging everything means you own everything you see.

C — Give them a tool that protects them before the mistake happens

The only option that works with human behavior instead of against it. Your employees want to use AI. Give them an interface that lets them — and removes the sensitive data automatically, before it goes anywhere.

What that actually looks like

Without protection, an employee sends the model the client name, the deal value, a named executive, the legal contact and the full contract text — now sitting on a server your legal team has no agreement with.

With Shield in front, the employee types the same thing, but what reaches the model has the sensitive data stripped inline: the company becomes COMPANY, the executive becomes PERSON, the value becomes VALUE, the email becomes EMAIL. The employee gets the same answer. Nothing sensitive left your environment.

They didn't have to think about it. They didn't have to learn a new behavior. The tool handled it for them.

How Shield handles this

• Inline anonymization, before the prompt leaves — people, companies, emails, financial values and identifiers are detected and replaced before the prompt reaches the model. The employee sees the full text; the model never does.
• Works in front of existing AI — Shield sits in front of the AI chat your team already uses. You add a protection layer, you don't rebuild anything.
• Logs what was stripped, not what was typed — auditability without surveillance. You can show a regulator the protections without creating a liability around what employees wrote.
• You define what counts as sensitive — client names, contract values, project codes, HR identifiers. Shield enforces them consistently, every time.

The decision is already made

Your employees will use AI today — that's decided, by them and by competitive pressure. The only decision left is whether it happens with protection in place or without it. A widget that removes sensitive data before it leaves your environment isn't a restriction; it's the thing that makes AI use safe enough to be official policy.

Shield is preparing for launch. Pre-register for early access.

Want your team to understand *why* this works, hands-on? We run live 90-minute sessions on AI data leakage and inline anonymization with our expert partner Avenue78.