How to Address Shadow AI in Healthcare

As artificial intelligence tools become more common in healthcare, organizations are now facing a new challenge known as “shadow AI.” This concept is similar to shadow IT, where employees use software or digital tools without approval from the IT department. In the case of shadow AI, staff members may start using AI tools on their own — often through personal accounts — without considering security, compliance or data privacy risks.

In modern workplaces, employees often look for tools that make their work faster and easier. If the process for getting IT approval is slow or complicated, they may start using AI tools on their own. While this may improve productivity in the short term, it can create serious risks, especially in healthcare, where patient data must be protected and strict privacy regulations must be followed.

To reduce the risks of shadow AI, healthcare organizations must first build a strong AI governance structure. This means creating clear policies about which AI tools are allowed, how they should be used and who is responsible for monitoring their use. Organizations should create a governance team that includes IT staff, clinical teams, legal departments and management. This ensures that decisions about AI are made from an organizational perspective rather than by individual departments.

However, organizations should not completely block employees from trying new AI tools. Instead, they should create a structured process where employees can test new AI solutions safely. For example, organizations can provide a controlled testing environment or sandbox where staff can experiment with AI tools without risking sensitive data or system security. This approach encourages innovation while still maintaining security and compliance.

Another important step is to implement technical controls to monitor the use of AI tools. IT departments should use monitoring tools to detect unauthorized applications and limit access to risky platforms. By monitoring network activity and application usage, organizations can identify shadow AI tools before they become a major security risk.

Communication also plays a major role in reducing shadow AI. Healthcare organizations should clearly explain why certain AI tools are approved and how they benefit the organization. When employees understand the purpose of AI policies and how approved tools improve their work, they are less likely to use unauthorized tools.

Organizations should also measure the return on investment (ROI) of AI tools and define clear use cases. When employees see that approved AI tools are useful and supported by the organization, they are more likely to adopt them instead of using unapproved solutions.