An artificial intelligence data retention policy governs the lifecycle of information handled by an AI service. It can cover prompts, uploaded files, generated outputs, account identifiers, diagnostic logs, safety records, and derived data, with different retention periods and access rules for each category.
Retention requirements influence model and provider selection because some workloads cannot send sensitive information to services that store it beyond an approved period. A complete policy should also define deletion, legal holds, backups, auditing, regional storage, and whether retained data may be used for training.
Acronyms and aliases
AI data retention policy acronymartificial intelligence data retention policy variantmodel data-retention policy variant
Related terms
Frequently asked questions
Why do data retention policies affect artificial intelligence model selection?
A capable model may still be unsuitable if its service stores sensitive prompts, outputs, or logs beyond the organization's approved limits.
What information should an artificial intelligence retention policy cover?
It should address prompts, files, outputs, logs, identifiers, derived data, backups, deletion timing, access, location, and training use.
