AI is already being used across organisations, whether it is officially approved or not.
Employees want to work faster, write better, analyse more quickly, and remove friction from daily tasks. So when there is no approved enterprise AI solution in place, they often turn to whatever is easiest to access: free versions of ChatGPT, Gemini, Perplexity, and other public tools.
That is where the real challenge begins.
What looks like harmless experimentation can quickly create serious business risk. Employees may paste sensitive company information into public AI tools without fully understanding the consequences. That could include customer data, financial information, contracts, internal strategy, source code, or confidential operational details.
The problem is not only data exposure. It is also the loss of control. In many cases, public AI platforms may retain or process submitted information under terms that are not acceptable for enterprise use. For security, legal, and compliance teams, that creates a clear and immediate concern.
At the same time, most organisations have very limited visibility into what is actually happening. They often do not know which AI tools are being used, by whom, how often, or whether sensitive data is being shared. Without that visibility, there is no real governance.
This leaves organisations stuck between two poor choices: either block AI and frustrate employees, or buy expensive enterprise licences for everyone and struggle to justify the cost.
Shadow AI grows in exactly that gap between demand and enablement.
Mitigate Shadow AI