What it means
AI data retention is the policy and system behavior that determine how long AI-related inputs, outputs, logs, prompts, source records, embeddings, summaries, and reviewer actions are stored. In HR software, retention questions can involve candidate data, interview records, employee comments, performance notes, compensation context, workflow logs, and generated communications.
Why buyers should care
AI features can create new data artifacts that teams may not notice during implementation. A generated summary, prompt log, or model interaction may contain sensitive people information even when the original workflow looked routine. Buyers should understand what is stored, where it is stored, who can access it, and how deletion or retention settings interact with HR, legal, privacy, and compliance requirements.
Evaluation checks
Review retention defaults, admin controls, deletion workflows, export options, audit logs, subprocessor behavior, and whether AI data is used for product improvement or model training. Ask vendors to distinguish source records from generated outputs and logs. Retention should be configurable enough to support policy, privacy, and operational review without keeping unnecessary sensitive data indefinitely.
This glossary entry is buyer-oriented guidance, not legal, compliance, or financial advice.