What are the risks of shadow AI usage among employees?

Unsanctioned AI tool use creates several distinct categories of risk. The most immediate is sensitive data leaving the organization's control, since employees often paste internal documents, customer information, or proprietary code directly into third party models without understanding or checking that model provider's data retention and training policies. Once that data has been submitted, the organization generally has no way to retrieve it or verify it was not retained.

A second risk is inconsistent compliance posture, since regulatory frameworks around data handling and AI usage increasingly require organizations to know what systems are processing sensitive data and how. Shadow AI usage undermines this by definition, since it happens outside any tracked or governed process. A third risk is the complete absence of an audit trail if something does go wrong, whether that means a data leak, a compliance violation, or an AI generated output that turns out to be inaccurate or harmful in some way.

Shadow AI risk is compounded relative to earlier shadow IT problems because the tools involved are often free browser extensions or personal accounts that bypass procurement entirely, meaning there is no vendor contract, no security review, and no data processing agreement in place at any point.

Visibility is the necessary first step toward managing any of this, since an organization cannot assess or mitigate risk from tools it does not know are in use. Akto's Atlas discovers this usage across the enterprise so security teams can assess and govern it deliberately, rather than continuing to operate without any real picture of their actual AI exposure.