What Is Shadow AI?
Risks Every Enterprise Must Know
Shadow AI refers to generative AI services employees use for work without IT approval. It's already happening in most enterprises, and existing security frameworks can't even detect it.
4 Risks Created by Shadow AI
These are not just IT policy violations — they represent real security and legal risks.
Customer info, source code, and internal documents are transmitted to unauthorized AI service servers.
Many smaller AI services lack enterprise-grade security infrastructure.
Personal data is transferred to AI services without the consent required by GDPR and privacy laws.
No record of what data was sent to which AI service, making root cause analysis impossible when incidents occur.
4 Steps to Control Shadow AI
The key is visibility and providing safe alternatives, not just blocking.
Audit All AI Services in Use
Use endpoint agents to identify all AI services actually being used across the enterprise. You'll find far more Shadow AI services than expected.
Classify AI Services by Risk Level
Classify discovered AI services into three tiers: approved (allowed), conditionally allowed (monitored), and blocked. Security teams and business units should review together.
Apply Policies and Educate Employees
When unauthorized AI is used, show a warning with approved alternatives. Blocking alone leads employees to find workarounds.
Continuous Monitoring and List Updates
Hundreds of new AI services launch every month. Quarterly list updates and continuous monitoring are essential.