Your data policy has a gap in it. A big one. And your IT team probably doesn’t know it exists.
Employees are copying contracts, financial models, customer data, and internal strategy docs into free AI tools. Not because they’re careless. Because the tools are genuinely useful and nobody told them not to. By the time your security team finds out, that data has already been processed by a model you don’t control, on servers you’ve never audited, under terms of service your legal team has never read.
This is shadow AI. And it’s happening in your company right now.
Shadow IT used to mean employees using Dropbox or Slack before IT approved them. The risk was manageable, a file sitting in the wrong cloud. Shadow AI is a different category of problem. When an employee pastes a sensitive document into a free LLM, they’re not just storing data somewhere unapproved. They’re feeding it into a training pipeline. Potentially. Permanently.
Most free AI tools default to using your inputs to improve their models. Some let you opt out. Some make the opt-out hard to find. Some are run by companies with no enterprise data agreements whatsoever. Your employee doesn’t know which is which. They just know the tool summarized a 40-page contract in 30 seconds and saved them two hours.
You can’t blame them for using it.
The companies most exposed aren’t the ones with the least security awareness. They’re the ones where the gap between “what people need to do their jobs” and “what IT has approved” is widest. When approved tools are slow, clunky, or don’t exist yet, employees fill the gap themselves. They always have.
The difference now is that the gap-filling tool is a generative AI product that may retain everything it is given.
A few things worth knowing:
- ChatGPT’s free tier trains future models using conversations, unless users opt out in settings most people never open.
- Google’s Gemini has had similar defaults with varying levels of clarity in its disclosures.
- Dozens of specialized AI tools, coding assistants, writing tools, and meeting summarizers have data retention terms buried in multi-page ToS documents.
None of that is secret. It’s just not what the person copying a client proposal into a chatbox is thinking about at 4pm on a Tuesday.
The answer isn’t to ban AI. That’s already failed at every company that’s tried it. People will use their phones. They’ll use personal accounts. You’ll push the behavior underground and lose even the ability to see it happening.
What actually works:
Provide people with approved tools and ensure real enterprise data agreements are in place. OpenAI’s enterprise tier, Microsoft Copilot with proper licensing, and Google Workspace AI with data processing agreements aren’t perfect, but they’re a different risk category than a free consumer product with no enterprise controls.
Then build a clear policy and actually communicate it. Not a PDF in the employee handbook. A real conversation about what’s allowed, what’s not, and why. Most employees, when they understand the risk, make different choices.
Audit your existing tools. Find out what AI features are already embedded in the software you pay for. Salesforce, Microsoft 365, HubSpot, and Zoom have all added AI capabilities in the last 18 months. Some of those features are on by default. Some of them have their own data handling implications.
The companies that are going to struggle with this aren’t the ones that haven’t heard of shadow AI. It’s the ones that heard about it, filed it under “something to address eventually,” and moved on.
Eventually, it becomes a breach notification.
Where are you on this? Have you audited which AI tools your employees are actually using, or are you still in the “we’ll deal with it soon” category?
The post Shadow AI: Your Employees Are Feeding Your Secrets to Free Chatbots appeared first on Chad M. Barr.
