Shadow AI refers to artificial intelligence tools and systems adopted and used within an organization without the knowledge, approval, or governance of central IT or data leadership. Often driven by well-meaning business units eager to move quickly, shadow AI can include anything from teams using ChatGPT to generate reports, to departments deploying off-the-shelf machine learning tools, to customer service groups integrating AI chatbots independently.
While shadow AI can spark innovation and accelerate experimentation, it also poses major risks—such as regulatory noncompliance, security vulnerabilities, biased or unvalidated models, and fragmented data practices. As generative AI tools become more accessible, organizations are seeing a surge in shadow AI, prompting the need for governance frameworks that balance agility with control. Identifying and addressing shadow AI is now a critical component of enterprise AI strategy and risk management.