---
id: data-classification-review-for-ai-workloads
version: 0.1.0
title: Data Classification Review for AI Workloads
authors:
- drafts@cybergurkhas.com
reviewed_by:
- drafts@cybergurkhas.com
last_reviewed: '2026-05-09'
tags:
  lifecycle: operational
  type: operational
  compliance:
  - nist-ai-rmf
  - iso-42001
  complexity: medium
summary: 'Align data classes with AI processing: labeling rules, residency, retention,
  and permitted model types per class.'
estimated_duration_minutes: 120
---

## Purpose

Execute a consistent, evidenced process for: Data Classification Review for AI Workloads. This runbook
is a template; tailor owners and tools to your environment. Sections marked
for IR review must be validated by a practitioner before you treat the text
as authoritative.

## When to use

- The scenario matches the title and your governance tier requires a run record.
- You need a shared checklist across security, platform, and product teams.
- An audit or customer asks for proof of operational discipline.

## Prerequisites

- Incident or change channel identified (ticket system, war room, or comms tree).
- Access to model cards, monitoring dashboards, and access logs as applicable.
- Legal/comms on standby if external notification may be required.

## Steps

### 1. Initiate and assign roles

**Type:** manual
**Owner:** Incident commander or release owner
**SLA:** 1 hour

Open the tracking record, set severity, assign owners for technical, comms,
and legal streams. Confirm single accountable decision maker.

> **[IR / editorial review]** Confirm escalation titles match your org.

### 2. Stabilize and preserve evidence

**Type:** manual
**Owner:** Security engineering
**SLA:** same day

Capture timestamps, configuration snapshots, and log excerpts. Avoid destructive
changes until evidence is secured. Document scope of affected systems.

### 3. Upload primary evidence bundle

**Type:** file_upload
**Owner:** Security engineering
**SLA:** same day

Attach the initial evidence package: dashboards, queries, redacted samples,
and chain-of-custody notes suitable for later audit export.

### 4. Structured impact assessment

**Type:** form
**Owner:** Product or risk owner
**SLA:** 1 business day

Record data classes touched, user impact, regulatory triggers, and whether
third parties are implicated. Use your internal risk rubric.

### 5. Approver sign-off for next phase

**Type:** approval
**Owner:** Security operations leader
**SLA:** 1 business day

Named approver authorizes remediation actions that may affect production
(for example, model rollback, block rules, or vendor engagement).

### 6. Integrations and follow-up

**Type:** webhook
**Owner:** Platform engineering
**SLA:** same day

Trigger ticketing or paging webhooks per your standard. Ensure post-incident
review is scheduled and linked from the record.