Law Firm AI Policy Quick Start

Law firms do not need a long AI policy before they can set safer working rules.

They do need clear answers to everyday questions: which AI tools are allowed, what client information must not be entered, when human review is required, and who decides on exceptions.

This quick start is designed for firms using or considering ChatGPT, Claude, Microsoft Copilot, Gemini, legal research tools, document automation, and AI-enabled practice software.

For a downloadable boardroom-style worksheet, use the Law Firm AI Governance Diagnostic.

1. Start With The Tool List

Create a plain-English register of AI tools and AI-enabled features.

For each tool, record:
- Tool name and vendor
- Whether it is approved, restricted, under review, or not approved
- Account type: personal, team, firm-managed, or embedded in another platform
- Data-use position based on vendor materials and settings
- Business owner and technical owner
- Approved use cases
- Review date

The first governance gap in many firms is not a missing policy. It is that no one has a complete view of what staff already use.

2. Set Client Data Boundaries

The policy should be direct about what must not be entered into open or unapproved AI tools.

Cover:
- Client names and matter details where confidentiality restrictions apply
- Privileged or confidential correspondence
- Draft advice, strategy, pleadings, witness material, settlement positions, and negotiation notes
- Personal information, financial information, and sensitive business information
- Documents subject to client-specific restrictions
- Internal pricing, partner papers, HR matters, and firm strategy

Where AI use is allowed, state whether information must be anonymised, summarised, de-identified, or replaced with synthetic examples.

3. Define Approved And Restricted Use Cases

Useful approved use cases often include low-risk tasks such as:
- Turning internal notes into a first draft agenda
- Summarising non-sensitive training material
- Drafting internal communications for review
- Creating checklists from firm-approved templates
- Improving readability of non-client text

Restricted use cases need extra review before use:
- Summarising matter documents
- Drafting client correspondence
- Analysing contracts or evidence
- Preparing research notes
- Using meeting transcripts
- Working with client-provided data

The policy should explain who can approve restricted use and what evidence should be kept.

4. Make Human Review Non-Negotiable

AI output should not move straight into client work without accountable review.

Reviewers should check:
- Accuracy and completeness
- Missing context
- Incorrect assumptions
- Confidentiality and client restrictions
- Citations, sources, or references where relevant
- Tone and professional judgement
- Whether AI use should be recorded internally

The point is not to slow every task. It is to make higher-risk use visible and reviewable.

5. Address Copilot Separately

Microsoft Copilot needs a specific section because it can work across Microsoft 365 content that users can already access.

Before rollout, confirm:
- Which users, teams, and practice groups are in scope
- Which SharePoint sites, Teams, OneDrive locations, and mailboxes contain sensitive information
- Whether broad groups or inherited permissions expose more than intended
- How external sharing and guest access are reviewed
- Whether staff understand that Copilot follows existing permissions

If the firm cannot explain what Copilot-enabled users can access, policy wording alone will not solve the risk.

6. Create A Simple Exception Path

Staff will encounter grey areas.

A practical exception path should answer:
- Who reviews unusual AI use requests?
- What information must the requester provide?
- How are client restrictions checked?
- What risk rating is used?
- Where are decisions recorded?
- When does leadership need to be involved?

A short exception log is often more useful than a long policy that no one follows.

7. Keep Evidence Leadership Can Inspect

A policy is stronger when the firm can show how it works.

Useful evidence includes:
- AI tool register
- Approved and restricted use-case list
- Staff guidance or briefing material
- Vendor setting notes
- Human review examples for important outputs
- Exception and incident log
- Copilot permission review notes
- Action tracker for unresolved gaps

Suggested 30-Day Policy Sprint

Week 1: identify tools, owners, and existing use.
Week 2: define client-data boundaries and approved use cases.
Week 3: set review, exception, and incident handling steps.
Week 4: brief staff, record leadership decisions, and plan the next review.

Summit Guard helps law firms turn AI use into clear policies, practical workflows, and leadership-ready evidence.

Contact Summit Guard to discuss a focused AI governance review.