AI Governance Framework for Law Firms

AI Governance Framework Brief

A one-page overview of the four risk domains AI creates in a law firm — confidentiality, professional negligence, client trust, and culture — and the four-pillar governance framework to address them: centralized procurement and approved tools, human-in-the-loop mandate, client disclosures, and training and internal equity. Use this as a starting framework for your firm’s AI policy conversation.

AI Use-Case Register Reference

A one-page reference covering ten common legal AI use cases — from legal research and fact-pattern analysis to contract redlining and content marketing — each classified by risk level (Critical, High, Moderate, Low) with the corresponding human oversight standard required. Use this as a reference when building your firm’s internal use-case register.

Centralized Procurement & Approved Tools

AI tools must go through a defined evaluation and approval process before lawyers use them on client matters. The framework establishes how to assess tools — including zero-data retention requirements — and maintain a firm-wide approved tool list.

Human-in-the-Loop Mandate

Every AI output used in client-facing work requires a qualified lawyer’s review before it goes out. This pillar addresses the competence and supervision obligations under the Model Code of Professional Conduct and defines what meaningful oversight looks like in practice.

Client Disclosures

Clients have a right to know when AI tools are used in their matters — particularly when those tools process their confidential information. The framework outlines when and how disclosure obligations arise and what language satisfies those obligations.

Training & Internal Equity

Access to AI tools creates skills gaps and equity issues within firms if not managed deliberately. This pillar addresses how to roll out AI tools equitably, ensure staff are trained on appropriate use, and prevent governance failures driven by shadow AI adoption.

Managing Partners

You’re fielding questions from clients about how the firm uses AI and from associates about which tools are permitted. These briefs give you a governance baseline to stand behind — and a framework to structure your internal conversation about what your firm’s AI policy needs to cover.

Firm Administrators & COOs

You’re responsible for technology adoption and risk management. The use-case register reference gives you the operational vocabulary to catalogue AI tools across practice groups and apply proportionate oversight standards without relying on ad hoc judgment.

Privacy and Risk Leads

You’re trying to satisfy Law Society expectations and data protection obligations at the same time. These briefs are designed to bridge professional responsibility requirements with privacy program best practices — giving you a shared framework for both conversations.

2024–2026

Law Society AI Guidance Wave

The Law Society of Ontario, BC, and others have issued AI guidance requiring lawyers to maintain competence in the tools they use and govern them appropriately.

Client Due Diligence

Increasingly Standard

Enterprise clients are asking law firms how they use AI, what data flows into those tools, and what governance frameworks are in place. Documented policies are becoming table stakes for institutional work.

Privilege at Risk

Without Clear Policies

Without clear policies on what client data can enter AI systems, firms face real risk that confidential information is processed in ways that compromise privilege or trigger disclosure obligations.

Is this framework specific to Canadian law firms?

Yes. The framework brief reflects guidance from the Law Society of Ontario, Law Society of British Columbia, and other provincial law societies that have issued AI practice directions. It addresses Canadian professional responsibility obligations, including duties of confidentiality, competence, and supervision under the Model Code of Professional Conduct. Firms in other common law jurisdictions can adapt the framework with minimal modifications.

How should we use these reference briefs?

These are starting-point frameworks, not finished policies. The governance brief outlines the four pillars your firm’s AI policy should address — use it to structure your internal conversation about what your policy needs to cover. The use-case register reference gives you ten common legal AI applications with risk classifications and oversight standards — use it as a blueprint when building your firm’s own use-case register. If you need help turning this framework into a firm-specific, ready-to-adopt AI policy, that’s what our fixed-fee policy engagement is designed to deliver.

What AI tools does the framework cover?

The framework is tool-agnostic — it establishes governance principles and evaluation criteria rather than prescribing specific products. The centralized procurement pillar addresses how to evaluate tools like Harvey, Spellbook, CoCounsel, Microsoft Copilot, ChatGPT Enterprise, and internal builds, with a focus on zero-data retention requirements. The use-case register reference covers common applications including legal research, drafting, document review, contract analysis, and client communications — the governance standards apply regardless of which tool you use for each.

Do we need lawyer involvement to build on this framework, or can our IT team handle it?

Both. Building a defensible AI policy requires legal judgment on professional responsibility obligations, client disclosure requirements, and the appropriate level of human oversight for different use cases — these are not decisions an IT team can make alone. However, the technical implementation (approved tool list, vendor data retention requirements, access controls) requires IT involvement. The framework is structured so that the legal governance decisions and the technical implementation decisions are clearly separated.

Can we adapt this framework for our firm’s specific practice areas?

Yes — the framework is intentionally principle-based so it applies across practice areas. The four pillars are modular: your firm can prioritize the pillars most relevant to your practice and build specific guidelines for your most common AI use cases. The use-case register reference is a starting point — most firms add practice-specific entries (e.g., litigation e-discovery, real estate conveyancing, IP portfolio management) as they adopt new tools. If you want a firm-specific, ready-to-adopt policy built on this framework, that work is what our fixed-fee engagement delivers.

Laith Sarhan

Founder, Sarhan Data Law

Laith Sarhan is a data and technology lawyer who advises law firms, AI companies, and regulated organizations on the legal infrastructure of responsible AI adoption. His practice sits at the intersection of privacy law, AI governance, and professional responsibility — giving him a clear view of the governance gaps Canadian law firms need to close before AI creates liability.