What is Shadow AI?

Prepare for the ISACA Advanced in AI Security Management (AAISM) Test. Study with in-depth multiple choice questions, each offering insightful hints and detailed explanations. Equip yourself with expert knowledge and get exam-ready!

Multiple Choice

What is Shadow AI?

Explanation:
Shadow AI refers to AI tools and models that are deployed and used outside the formal IT governance and security controls of an organization. It happens when individuals or business units adopt external or unvetted AI solutions, run them in production, and connect to sensitive data without IT involvement. This bypasses risk management, data protection, and oversight, creating potential issues like data leakage, compliance violations, insecure configurations, unpatched vulnerabilities, and licensing or vendor risks. Because governance and monitoring are absent, the organization can’t ensure proper data handling, access controls, or ongoing risk assessment. The described option fits this exactly: decentralized, external deployment of AI solutions without IT/security involvement. The other choices refer to different concepts—an AI model masquerading as a human is about deception or impersonation, central IT governance describes controlled, reviewed deployment, and a legal framework is about rules rather than how AI is deployed—so they don’t capture the idea of ungoverned, shadowed AI usage.

Shadow AI refers to AI tools and models that are deployed and used outside the formal IT governance and security controls of an organization. It happens when individuals or business units adopt external or unvetted AI solutions, run them in production, and connect to sensitive data without IT involvement. This bypasses risk management, data protection, and oversight, creating potential issues like data leakage, compliance violations, insecure configurations, unpatched vulnerabilities, and licensing or vendor risks. Because governance and monitoring are absent, the organization can’t ensure proper data handling, access controls, or ongoing risk assessment.

The described option fits this exactly: decentralized, external deployment of AI solutions without IT/security involvement. The other choices refer to different concepts—an AI model masquerading as a human is about deception or impersonation, central IT governance describes controlled, reviewed deployment, and a legal framework is about rules rather than how AI is deployed—so they don’t capture the idea of ungoverned, shadowed AI usage.

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