QA for AI Texts in Law Firms: Criteria, Stop Rules, Example Checklist

Problem: "Sounds Good" Is Not a Quality Definition

AI texts can be fluent and still be dangerous:

• unclear claims,
• too much generalizing,
• missing process logic,
• formulations that are vulnerable to attack.

Goal: a verifiable QA standard.

QA Criteria (Short Version)

1. Does it help a real decision-maker? (concrete, actionable)
2. Claims are clean (no unprovable promises)
3. Process before tool (no tool litany)
4. Compliance sensitivity (no legal advice, no no-go claims)
5. Internal links are meaningful (Pillar + 2 Cluster)

Artifact: QA Checklist (Copy/Paste)

A) Content & Value

• 1 clear angle (checklist/decision aid/anti-pattern)
• At least 1 artifact (template, table, text block)
• No repetition of paragraph "filler text"

B) Claims & Risk

• No "guaranteed", "always", "legally secure" etc.
• No implicit legal advice
• If sensitive: alternatives/formulations offered

C) Structure

• Lead (1-2 sentences)
• 3-5 sections (##)
• Conclusion + CTA (scope/KPI)

D) Consistency

• Terms consistent (status, owner, SLA)
• Examples fit the law firm context

E) Links

• Link to Pillar: - [ ] 2 links to related articles

Stop Rules (No Publish)

• More than 2 risky claims without safeguards → Stop
• No artifacts/no concrete steps → Stop
• Interlinking missing → Stop

KPI Block

• Correction rate after QA: Target < 30% (otherwise briefing/prompt is bad)

• Internal Link Coverage: Target 100% (Pillar + 2 Cluster)

• Guide: Content Automation for Law Firms

• Deep dive: Content Approval in 10 Minutes (Review Flow)

• Deep dive: No-Go Claims: Safe Alternatives

Next Step

If you have 1 example article + your internal "no-gos", I can adapt the QA checklist so it's applicable by your team in 10 minutes.

→ Schedule initial consultation