What is GenAI Risk Categories?
GenAI risk categories are the main classes of risk used to organize generative AI controls, such as safety, security, privacy, IP, accuracy, bias, and misuse. They matter because compliance teams need a structured taxonomy to map testing, monitoring, and governance obligations to the actual risks posed by a generative AI system.
In Depth
In practice, a GenAI risk taxonomy helps teams decide what to test, what to document, what approvals to require, and what monitoring to continue after deployment. It is especially useful when a single system can produce synthetic text, images, code, or decisions that trigger different legal and operational concerns, including hallucinations, copyrighted content, confidential data leakage, and harmful or discriminatory outputs.
Frameworks do not all use the same labels, but the concept is embedded in risk-based governance approaches across the EU AI Act, NIST AI RMF, ISO/IEC 42001, and SOC 2 + AI control environments. It is also closely connected to transparency, data governance, cybersecurity, and content-marking obligations that arise in specific jurisdictions or use cases.
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