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AI Reliability Checklist for Law Firms

Eight practical checks for data control, model portability, record citations, human review, tested fallbacks, and continuity.

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The record, the reviewer, and a workable fallback stay in the same system.

AI Reliability Checklist for Law Firms

Checklist · Andrew Mayes

Before adoption

Know what becomes load-bearing.

  1. 1. Data location

    Document where prompts, testimony, files, and outputs go.

  2. 2. Model portability

    Confirm the workflow can survive a model or vendor change.

  3. 3. Method portability

    Keep prompts and procedures usable outside one product.

  4. 4. Record citations

    Require page-and-line support or a clear not-in-the-record result.

In production

Keep accountability and continuity visible.

  1. 5. Human review

    A qualified professional reviews consequential output before release.

  2. 6. Tested fallback

    A second workable path has been exercised, not merely named.

  3. 7. Manual path

    The critical task can still be completed without the AI system.

  4. 8. Written continuity plan

    Owners, steps, and escalation paths are documented.

The standard: A backup, a documented process, and accountable human review stay attached to every critical AI workflow.

andrewmayes.com/guides/ai-reliability-checklist-law-firms/ Updated

What this guide protects against

An AI tool can look reliable while one vendor, one model, or one undocumented workflow remains load-bearing. This guide turns reliability into eight questions a firm can answer before adoption and revisit during routine review.

How to use it

  1. Assign an owner for every item.
  2. Record the answer, not merely a checkmark.
  3. Test the fallback and manual path under realistic conditions.
  4. Revisit the guide when a vendor, model, retention policy, or critical workflow changes.

The visual is designed to print cleanly. Use Print / save PDF to create a one-page office copy, then keep the documented answers with the firm's technology and continuity procedures.

The operating standard

AI should support accountable legal work without becoming an unexplained single point of failure. Critical claims stay traceable to the record, consequential output receives professional review, and the firm retains a way to keep working when the primary tool is unavailable.

Basis and limits. ABA Formal Opinion 512 (opens in a new tab) addresses competence, confidentiality, and review under the ABA Model Rules. NIST AI 600-1 (opens in a new tab), GOVERN 6.2, recommends documented fallbacks and rehearsed incident response. These eight checks are my continuity framework, not a complete ethics checklist or a certification of any tool. Apply the rules of your jurisdiction.

For additional context, the worked review example shows how a real citation can still fail to support a proposed summary, using a short synthetic record.

Related tool: CasePrompts

Prompt like you're assigning the work — not Googling it.

The builder runs in your browser with no signup and does not accept case files. Every output still needs professional review.

Read the CasePrompts case study Build a free prompt (opens in a new tab)

Questions about your workflow? Start a conversation