Start with a narrow use case
The best first AI workflow is specific. Choose one document type, intake step, or internal communication that repeats and has a clear definition of done. Write down what the tool may receive, what it must return, and what the reviewer must check. A narrow workflow creates evidence before the firm expands the program.
Keep source material visible
AI-generated text is not a source of truth. Give the workflow approved source material and require the output to identify uncertainty or missing information. Compare names, dates, citations, calculations, and client-specific facts. The ABA explains that generative AI can produce fluent text that is unreliable, incomplete, or unsupported, so a review step is essential.
Design for confidentiality
Classify information before it enters a tool. Review the provider’s terms, retention settings, access model, and training policy. Keep privileged and confidential information out of a tool unless the firm has made an informed decision that the use is permitted and appropriately protected. ABA Model Rule 1.6 requires reasonable efforts to prevent unauthorized disclosure.
Define the human approval step
State who reviews the output, what they check, and what they do when the output is wrong. The review must be proportionate to the task. A draft internal outline may need a light check. A client communication, legal analysis, or filing needs a more deliberate review by a qualified person. The lawyer remains responsible for the work.
Create an AI operating rule
An AI policy should name approved tools, prohibited data, review requirements, client communication expectations, and the owner who updates the policy. NIST describes its AI Risk Management Framework as voluntary guidance for incorporating trustworthiness into AI design, use, and evaluation. A small firm can adapt that idea into a short, readable policy.
Implement and improve
Start with a test set of real examples that have already been reviewed. Measure time saved, errors caught, and places where staff hesitate. Update the prompt, source set, or review checklist when the workflow changes. Woven Legal’s published model pairs AI workflow implementation with practical process guidance and fractional execution when a firm needs help putting the system to work.
What makes an AI workflow useful in a law firm?
A useful workflow has one defined job, approved inputs, a reliable output format, and a reviewer who knows what to check. It does not ask a tool to decide a legal question without supervision. Start with a task such as extracting fields, preparing a first draft, organizing notes, or writing a routine internal message. Connect the task to a document automation or intake path only after the first use case is understood.
How should a firm review AI output?
Review depends on the consequence of the output. Check names, dates, source documents, citations, calculations, and missing facts. For a client communication or filing, a qualified lawyer should approve the final result. ABA Formal Opinion 512 explains that generative AI can produce fluent but unreliable content and that a lawyer remains responsible for independent verification. Put the review step inside the approval workflow, with a record of who approved the work.
What should an AI policy cover?
Keep the policy short enough to use. Name approved tools, prohibited data, access rules, review requirements, client communication expectations, and the person who owns updates. Review provider terms and retention settings before confidential information enters a tool. ABA Model Rule 1.6 requires reasonable efforts to prevent unauthorized disclosure, so confidentiality must be part of the workflow design. NIST describes its AI Risk Management Framework as voluntary guidance for incorporating trustworthiness into AI design, use, and evaluation.
AI use-case decision table
Swipe or scroll to see all columns →
| Use case | Good starting condition | Required review |
|---|---|---|
| Internal outline | No client facts or legal conclusion | Source and accuracy check |
| Structured extraction | Known fields and a test set | Sample comparison and exception review |
| Draft client communication | Approved template and source facts | Attorney review before release |
| Legal analysis | Controlled source library | Independent authority and reasoning check |
AI workflow launch checklist
- Write the task and its definition of done.
- Classify the data before it enters the tool.
- Record the approved source material and prompt.
- Test the workflow on reviewed examples.
- Name the reviewer and escalation path.
- Measure errors, rework, and time saved before expanding.
When the system needs process mapping or staffing to make it usable, connect the AI project to a workflow audit, AI governance, and technology competence plan. Woven Legal’s published model combines AI workflow implementation with practical systems and fractional execution.
How Woven Legal can help
Woven Legal starts with the firm’s current work, then helps shape a practical workflow, implement the right systems, and provide fractional execution when the team needs more capacity. The next step is a conversation about the work that is slowing your firm down.
Questions, answered.
Can AI make legal decisions for a firm?
AI can support repeatable work, but professional judgment and final responsibility remain with the lawyer. The workflow must define review and approval.
What information can we put into an AI tool?
That depends on the tool, the firm’s policy, the client relationship, and the information involved. Review terms, safeguards, and confidentiality obligations before use.
Where should a firm start with AI?
Start with one repetitive, well-defined task that has reliable source material and a clear reviewer.