Data Freshness

Data freshness refers to how current and up-to-date the information used by AI systems is, measured from the time data is collected to when it's deployed in production models. For enterprise AI governance, maintaining appropriate data freshness standards is critical because stale or outdated data can cause model performance degradation, compliance violations, and poor business decisions. Organizations must establish policies that define acceptable staleness thresholds by use case, implement monitoring systems to track data age, and create processes for regular retraining when freshness standards are violated.

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