The Conventional Wisdom
Many compliance teams believe AI logs should either be kept "as long as possible for evidence" or "as briefly as possible to minimize risk." One group opts for multi-year retention, while the other deletes everything at 90 days. Both think consistency is the safe bet: one retention period, applied uniformly, shows you have a policy.
Uniform retention is easier to document, simpler to audit, and harder to mess up. You don't need to make judgment calls about which AI function matters more. You don't risk accidentally deleting something important because someone miscategorized it. And when an auditor asks, "How long do you keep AI logs?" you have a clean answer.
Why This Approach Is Incomplete
A single retention period for all AI logs doesn't satisfy your regulatory obligations or operational needs. It creates the very problems it's supposed to prevent.
Keeping everything too long violates GDPR Article 5(1)(e) storage limitation. AI logs often contain personal data, pseudonymous identifiers, IP addresses, and document references. Each extra month you hold that data increases your breach surface and your discovery obligations in litigation. "We might need it someday" isn't a lawful purpose under Article 5(2). You can't claim data minimization when your default is indefinite retention.
Keeping everything too short means losing the ability to reconstruct what your AI system did. Imagine a customer finds a missed redaction eight months after a confidential transaction closes. If your logs expired at 90 days, you can't prove what the model flagged, which version ran, or whether a human approved the output. For high-risk AI systems under the EU AI Act Article 19 and Article 26(6), six months is the regulatory floor, not a suggestion. Many vendor defaults are below it.
The real issue isn't the number you pick. It's assuming one number can serve both a customer-facing chatbot retrieving confidential documents and an internal autocomplete feature suggesting folder names.
What the Frameworks Actually Require
Look at what the frameworks require, not what they permit.
The EU AI Act Article 12 mandates automatic logging for high-risk systems so their operation can be traced. Articles 19 and 26(6) set retention at a minimum of six months, or longer if other law requires. That's a floor, not a target. Article 18 requires technical documentation for high-risk systems to be kept ten years.
GDPR pushes from the opposite direction. Article 5(1)(c) and (e) impose both data minimization and storage limitation as core principles. Article 17(3)(e) allows retention necessary to establish, exercise, or defend legal claims, but you need to document that necessity. Article 30 requires you to specify retention periods in your records of processing activities.
ISO/IEC 42001:2023 Annex A control A.6.2.8 addresses recording of event logs. Clause 7.5 covers control of documented information. An assessor will ask you to produce both your defined retention schedule and evidence that deletion actually happens on schedule.
Together, these frameworks don't give you a single answer. They give you boundaries: keep logs long enough to reconstruct and defend what the AI did, but no longer than necessary. A redaction engine processing personal data in a regulated transaction needs seven-year retention to survive claim limitation periods and GDPR Article 82 liability windows. An autocomplete tool that suggests tags needs six months to meet the EU AI Act baseline and nothing more.
What to Do Instead
Tier your AI functions by risk, then assign retention to the tier. You need four or five tiers at most.
Start by asking four questions about each AI function:
- Harm if wrong. If the output is incorrect, who gets hurt and how badly? A mis-tagged folder is an annoyance. A missed redaction or wrong credit decision is a breach or rights violation.
- Reliance without review. Is the output used as-is, or does a human check it first?
- Exposure. Can the function disclose personal data, change permissions, or affect systems or money?
- Evidentiary value. Would you need this log to answer a regulator, defend a legal claim, or pass customer due diligence?
Two or more "high" answers put a function in your top tier. Mostly "low" answers put it in your bottom tier.
Then map tiers to retention periods anchored in specific obligations. AI making decisions about people, redacting personal data, or taking automated actions through agents sits at seven years (GDPR Article 82 limitation periods, EU AI Act Article 12). Customer-facing chatbots and retrieval-augmented generation over confidential content sit at three years (EU AI Act Article 15, GDPR Article 32). Internal productivity suggestions with no permission changes sit at six months (EU AI Act baseline).
Log metadata only: what happened, when, for whom, under which model. Don't store document text, full prompts, or OCR output in logs. Long retention is defensible only when the log is lean.
Configure automated deletion per tier in your SIEM and at each model provider, then audit it quarterly. "We have a retention policy" fails an ISO/IEC 42001 audit. "Here's last quarter's deletion evidence" passes.
When Uniform Retention Works
Uniform retention does have one legitimate use case: when you genuinely run only one category of AI risk.
If every AI function you operate is customer-facing, processes personal data, and produces outputs people rely on without review, then yes, a single three-year or seven-year retention period across the board makes sense. You don't need tiers when there's only one tier.
The conventional wisdom also correctly identifies the danger of under-retention. Deleting logs before you've closed an incident investigation, answered a data subject access request, or survived the claim limitation period is worse than keeping them too long. A legal hold process that freezes logs tied to any incident, breach, or inquiry is mandatory regardless of your tier structure.
Consistency in how you apply the tiers, document the rationale, and prove deletion matters more than the specific numbers you choose. An auditor can work with "we keep redaction logs seven years because Article 82 liability" even if they'd prefer five. They can't work with "we keep some things longer but we're not sure which ones or why."
The mistake isn't wanting a clear policy. It's assuming clarity requires uniformity when your AI functions carry materially different risks.
