Shadow AI in the Workplace: Four Steps to Govern It

This post is informational and reflects the state of the law as of April 2026. For a policy tailored to your company, consult a licensed attorney.

Your employees are transcribing meetings with AI tools you did not approve. The harder problem is that you probably do not know which ones. Otter.ai, Fireflies, Fathom, ChatGPT, and a growing list of others are easy to adopt and easy to overlook. Most employees are not trying to create risk; they are trying to be productive. But they are routing customer data, financial details, and confidential business information through platforms your IT and legal teams never vetted.

The exposure is real. A single meeting sent through the wrong app can trigger data-protection violations, trade-secret loss, breach of a customer confidentiality agreement, and regulatory problems. This is usually called “shadow AI,” and a ban is not the fix. Bans push the behavior out of view, and you lose the visibility you need to manage it. Here is what works instead.

1. Audit what is already in use

You cannot govern tools you do not know about. Start with an inventory of what employees are actually using, not what policy says they should use. Most companies are surprised by what a basic audit turns up.

2. Write an AI use policy that names tools

“Use AI responsibly” is not a policy. A useful one names the specific tools employees may use, identifies the ones they may not, and defines what categories of company data can go into an approved tool and what cannot. Specificity is the whole point.

3. Give people a tool they actually want to use

This is where most programs quietly fail. There is a reason employees reach for a consumer AI account instead of the enterprise option IT provisioned: the better product wins. If your approved tool loses that comparison, employees route around it and you are back to shadow AI. Choose the approved option with adoption in mind, not just procurement.

4. Train on both the risk and the tool

Show employees concretely what happens when company data goes into a system you do not control. Then show them how to use the approved tool and what information is safe to put in it. Training that only covers the risk produces avoidance; training that also covers the tool produces the behavior you want.

The goal

The objective is a workforce that reaches for the right tool first, not one that routes around a rule. That is a governance problem before it is a technology problem, and it is one a clear policy and a genuinely usable approved tool can solve. (For how this fits with broader AI governance and employment practices, see the firm’s AI Governance and Employment pages.)

If your team is using AI tools faster than your policies can keep up, talk to MB Legal.

This post is informational and does not constitute legal advice. AI governance depends on your industry, data, and tools. For guidance on a specific policy, consult a licensed attorney.