What is shadow AI, and how do you govern it?
Shadow AI is the use of AI tools at work that the company has not approved or does not know about, and shadow AI governance is how a company brings that use into the open safely.
Shadow AI shows up two ways. People use tools their security team never approved, and people pay for tools out of their own pocket, assuming that because nobody is watching, the company has no exposure. Both put customer lists, pricing, and internal notes inside systems the company has no record of.
Banning the tools rarely works. The need that drove someone to the tool does not go away, so the use just moves somewhere leadership cannot see it. The real driver is usually curiosity with nowhere sanctioned to go.
Good governance gives that curiosity a home. It pairs a short list of approved tools with basic training on what data may and may not be pasted into them. It also asks teams what they are already using, without punishment, so the real footprint is known.
Shadow AI looks a lot like ghost SaaS: point solutions bought for one problem, data sprawling across tools that do not talk to each other, and no central record of any of it. The fix is the same too: an inventory, an owner, and a sanctioned place to experiment.
What to do about it
- Run a no-blame survey of which AI tools people already use.
- Publish a short approved-tools list with clear data rules.
- Train every user on what never goes into a prompt.
Frequently asked questions
Should companies ban ChatGPT and similar tools?
Bans tend to push use out of sight rather than stop it. A sanctioned alternative plus training lowers risk more reliably than a ban.
What is the difference between shadow AI and shadow IT?
Shadow IT is any unapproved software. Shadow AI is the subset that also ingests company data into models, which raises the stakes because that data can leave the company's control.