Episode 23 — Classify AI assets by sensitivity, criticality, and compliance scope (Task 13)
This episode explains how to classify AI assets so controls can be applied proportionally, which is a common AAISM decision point when scenarios ask what to protect first and how to justify the level of protection. You will learn to classify by sensitivity of data and outputs, business criticality of the AI service, operational impact of downtime, and compliance scope such as regulated data types and contractual obligations. We use examples like customer-facing models, internal copilots, training datasets with personal data, and inference logs that may contain sensitive prompts to show how classification drives access control, monitoring intensity, retention limits, and review frequency. Troubleshooting focuses on misclassification risks, such as treating prompts and logs as low sensitivity, ignoring downstream usage, or failing to update classification when a use case expands. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
