How Long to Keep AI Audit Logs (and When to Delete)

Keep AI audit logs long enough to cover the disputes and audits that actually happen, then delete them on a schedule you can prove. For most products that is somewhere between one and seven years depending on the industry, with sensitive fields redacted or dropped much sooner. An indefinite "keep everything forever" log is not caution. It is a growing liability that a breach, a subpoena, or a privacy regulator turns against you.

Retention is the question teams skip after they finally build audit trails into their AI systems. They log everything, keep it forever, and never think about it again. That is a mistake in both directions: too short and you cannot defend a decision, too long and you are hoarding risk.

What determines how long you keep AI logs

Three forces pull against each other.

• Defensibility. When a customer disputes a decision or a regulator asks, you need the record. This pushes retention up. How far up depends on how long disputes take to surface in your domain.
• Legal and regulatory minimums. Some industries mandate retention periods. Financial records, healthcare, legal matters each carry their own clocks. These set a floor you cannot go below.
• Privacy and breach risk. Every record you hold is a record that can leak, be subpoenaed, or fall under a deletion request. This pushes retention down. The safest data is the data you no longer have.

Your policy lives where those three balance. Name the period per data category. Do not use one blanket number for everything.

Sensible defaults by data type

Split the log into tiers and retain each on its own clock.

• Operational traces (request IDs, model versions, prompt versions, outcomes): keep for the length of your dispute window plus a margin. Often one to three years. These are low-sensitivity and high-value for making decisions defensible after the fact.
• Full input and output content: more sensitive, since it can contain customer data. Keep only as long as you genuinely need to reconstruct decisions, then drop or aggregate. Consider redacting personal fields at write time so the long-lived record is already clean.
• Regulated records: follow the mandated period exactly. In domains like legal case management, retention is not your choice, which is why CaseSolo treats it as a configured policy, not a default.
• Security and injection-attempt logs: keep long enough to spot patterns across time, but these rarely need the full sensitive payload.

The point is that a log is not one thing. Treating it as one forces you to keep your most sensitive content as long as your least sensitive metadata, which is exactly backwards.

Deletion has to be provable, not aspirational

A retention policy nobody enforces is worse than none, because you claimed a control you do not have. That is the gap between real governance and compliance theater.

Automate deletion. Make it a scheduled job, not a quarterly reminder someone ignores. Log the deletions themselves so you can show a reviewer that records from before your window are gone. When a buyer's security questionnaire asks about retention, you want a real answer with evidence, which is the whole point of being ready to answer an enterprise security questionnaire for AI.

Write it down before you need it

The worst time to decide your retention period is when a lawyer, a regulator, or a breached customer is asking. Decide now. Document the period per data type, the reason, and the deletion mechanism.

This is not glamorous, and it is not optional if you sell to anyone serious. A clear, enforced, defensible retention policy signals that you understand logs are both an asset and a liability. Keeping the right things for the right time, and provably destroying the rest, is what separates a governed product from one that just accumulates risk until something breaks.