A Practical AI Governance Model for Law Firms

AI governance should help a law firm use AI responsibly. If governance is only a prohibition memo, experimentation moves into the shadows. If it is only a list of approved tools, important workflow and supervision questions remain unanswered.

A practical model combines policy, technical controls, workflow design, ownership, and ongoing review.

Define approved uses

Describe permitted, restricted, and prohibited activities in language people can apply. Distinguish low-risk internal assistance from client-facing, filed, strategic, or highly sensitive work.

Include examples by role and practice area. State when attorney approval is required and when a workflow may not proceed.

Establish data-handling rules

Specify what information may be entered into each approved service, how it is retained, whether it is used for training, where it is processed, and who can access it.

The rule should follow the data through prompts, connectors, indexes, logs, exports, and support channels—not just the visible chat interface.

Review vendors and integrations

Evaluate security, privacy, contractual terms, model behavior, identity controls, auditability, incident response, data location, subcontractors, and the firm’s ability to retrieve or delete its data.

Review the configuration actually being deployed. A vendor may offer strong controls that are not enabled in the purchased plan.

Build human oversight into workflows

“Human in the loop” must identify the human, the evidence available to them, the standard they apply, and the action that follows.

Use stronger review where consequences are higher. Preserve attorney judgment and clearly separate generated assistance from legal decisions.

Log meaningful activity

Record sensitive reads, generated outputs, approvals, edits, exports, permission changes, and agent actions as appropriate. Logs should support investigation and improvement without creating unnecessary exposure.

Access to logs should itself be controlled.

Assign ownership

Governance needs named owners across legal, operations, technology, security, and firm leadership. Someone must be accountable for approved-use decisions, vendor review, incident handling, workflow quality, and policy updates.

Create a clear path for users to ask questions and report unexpected behavior without fear that doing so will end the program.

Review continuously

Models, vendors, laws, client requirements, and firm workflows change. Reassess approved uses, controls, incidents, adoption, and quality on a regular cadence.

Governance works when it is close enough to the work to guide real decisions. The objective is not zero risk. It is deliberate, documented, reviewable use of AI that protects clients while allowing the firm to improve how it operates.