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Yes, you can use legal AI with client-related work, but only after a matter-specific confidentiality and competence review. Start with the least sensitive information, verify how the provider stores, trains on, shares, secures and deletes data, and use an approved configuration with access controls. Obtain meaningful informed consent when the risk and governing ethics rules require it, document the decision, train and supervise everyone who uses the tool, and have a lawyer independently verify every consequential output before relying on it or disclosing it.
What professional duties apply when a lawyer uses generative AI?
Confidentiality duties apply to information entered into a generative-AI system just as they apply to information given to any other service provider. ABA Formal Opinion 512, issued July 29, 2024, says Model Rule 1.6 requires a fact-specific risk assessment before client-related information is entered into a GAI tool. The analysis covers both disclosure or access outside the firm and misuse by people or systems inside the firm.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsThe risk is not determined by the word “AI” alone. It depends on the client, the matter, the task, the sensitivity of the information, the provider’s safeguards and contract, and the way the tool is configured. A system that appears to be private may still retain prompts for a period, allow administrator access, send data to subprocessors, or use submissions to improve a model.
Why a self-learning system creates a special concern
Some systems change their behavior based on user submissions. If a model can reuse one client’s information when responding to another user, a prompt could become an unauthorized disclosure. A closed deployment limited to a firm’s employees reduces some exposure but does not automatically eliminate the risk: poor permissions, logs, backups, integrations or model-training settings can still expose information.
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What state and local opinions add
Florida Bar Opinion 24-1 (January 19, 2024) permits lawyers to use generative AI while requiring protection of client confidentiality, accurate and competent services, compliance with billing rules and applicable advertising restrictions. It directs lawyers to investigate retention, data-sharing and self-learning policies and to remain responsible for professional judgment and work product.
North Carolina’s 2024 Formal Ethics Opinion 1 allows a lawyer to provide client documents to a third-party AI program only after satisfying herself that it is “sufficiently secure” and will not permit inadvertent disclosure or unauthorized access. It also treats privilege as a separate question that must be resolved independently. The New York City Bar’s Formal Opinion 2024-5 is another 2024 jurisdiction-specific source; lawyers should read the rules and opinions that govern their own practice rather than assume one jurisdiction’s approach controls another.
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Which client information and tasks are suitable for legal AI?
Classify the task and the information before opening a tool. The safest starting point is public, synthetic or already de-identified text. If a task can be completed without identifying a client, privileged material, work product, personal data or trade secrets, do not add those details merely for convenience.
| Task or input | Typical sensitivity | Safer starting approach |
|---|---|---|
| Public statutes, regulations or published opinions | Low, provided no client facts are added | Ask for a summary, issue list or research outline, then check the cited authority yourself. |
| Synthetic fact patterns or a blank clause | Low | Use invented names, dates and numbers that cannot be mapped to a real matter. |
| Redacted contract or pleading | Moderate | Remove names, addresses, account numbers, metadata and unique identifiers; confirm the tool’s retention and training settings. |
| Client-identifying facts, strategy or work product | High | Use only an approved configuration after documenting the risk assessment and any required consent. |
| Medical, financial, employment or criminal-history data | High and potentially subject to additional laws | Minimize fields, separate identifiers from analysis, apply least-privilege access and obtain specialist advice when another legal regime applies. |
| Trade secrets, settlement positions or privileged communications | Very high | Prefer a non-AI workflow unless the provider’s controls, contract and consent analysis support a specific use. |
Use a data-minimization test
Ask three questions: What is the smallest amount of information needed for this output? Can the task be done with a hypothetical or redacted example? Can the analysis be performed locally or by a human without sending the data to a third party? If the answer to the second or third question is yes, choose that option unless there is a documented reason not to.
How should a firm vet a legal-AI provider and its contract?
Do not rely on a marketing statement such as “private,” “secure” or “enterprise.” Obtain the current product terms, privacy documentation, security materials and order form, and record the answers for the exact plan and configuration the firm will use.
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| Question to document | Why it matters |
|---|---|
| Are prompts, uploads, outputs or feedback retained? For how long, and in which systems or backups? | Retention determines how long a disclosure remains possible and whether deletion is meaningful. |
| Are customer inputs used to train, fine-tune or improve a model by default, by opt-in or not at all? | Training or self-learning can expose one client’s information in another matter. |
| Who can access data: the firm’s users, provider personnel, administrators, support staff or other customers? | Access must be limited to authorized people and isolated between tenants. |
| Which subprocessors receive data, and where are systems and backups located? | Sharing and cross-border transfers may create additional confidentiality, contractual or regulatory issues. |
| Can the firm export and permanently delete data, including indexes, logs and backups? | Deletion and portability affect matter closing, client requests and incident recovery. |
| What encryption, authentication, role-based permissions, audit logs and administrator controls are available? | Technical controls reduce accidental disclosure and make investigations possible. |
| What are the breach-notice, confidentiality, indemnity, audit and cooperation commitments? | The contract should support prompt response and give the firm usable remedies. |
| How does the provider handle conflicts, outsourced work and vendor personnel who may see content? | Third-party access can affect conflicts analysis, privilege and supervision duties. |
| Can the firm disable training, connectors, public sharing and other high-risk features? | Configuration choices often matter as much as the product’s headline security claims. |
Keep a record of the person who reviewed the terms, the date, the product edition, the enabled settings and any unresolved assumptions. Revisit that record when the provider changes terms, adds a model, changes subprocessors or materially changes retention behavior.
Do I need the client’s consent before entering information into an AI tool?
Sometimes. ABA Formal Opinion 512 requires lawyers to evaluate the risk first; when the risk is material, the lawyer should explain the proposed tool and information, the reasonably foreseeable risks and benefits, alternatives, and the possibility of later access or reuse, then obtain informed consent when the governing rules require it. Consent is not a substitute for selecting a secure configuration or minimizing the data.
What meaningful informed consent includes
- The specific tool or category of tool and the task it will perform.
- The types of client information that will be submitted and whether identifying details can be removed.
- Retention, training, sharing, administrator access, security and deletion practices that are relevant to the decision.
- Material risks, including unauthorized access, reuse in another matter, inaccurate output and possible effects on privilege.
- Alternatives, such as a human-only workflow or a tool that does not receive client information.
- A chance for the client to ask questions and refuse the proposed use without losing representation, unless the engagement genuinely depends on it and the rules permit that arrangement.
A generic sentence in an engagement letter is not automatically meaningful consent. The client needs information sufficient to make an informed decision about the actual use. Follow any stricter instruction in the engagement agreement or from the client, even if a bar opinion would otherwise permit the use.
How privilege differs from confidentiality
Attorney-client privilege is a separate legal analysis from the ethical duty of confidentiality. A provider’s personnel, subprocessors or other users may receive access in ways that affect privilege, and the answer depends on the jurisdiction, the service arrangement and the purpose of the disclosure. North Carolina’s 2024 opinion specifically requires privilege questions to be resolved separately; do not assume that an ethical permission preserves privilege.
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How can lawyers minimize and protect data before submitting a prompt?
Use this sequence for each proposed use. It is designed to stop unnecessary information from entering the system in the first place.
- Define the output. State the exact task, such as producing a list of issues or suggesting neutral headings. Avoid broad prompts that invite the system to process an entire file.
- Remove identifiers. Replace names, addresses, account numbers, dates of birth, matter numbers and unique fact combinations with consistent pseudonyms. Keep the key that maps pseudonyms to real identities outside the AI system.
- Separate facts from analysis. Store identifiers separately from legal analysis, strategy, medical details and financial information. Provide only the fields needed for the defined output.
- Redact hidden content. Strip comments, tracked changes, document properties, embedded spreadsheets, attachments and metadata before upload. Inspect the resulting file rather than assuming a visual redaction is permanent.
- Use an approved configuration. Disable provider training, public sharing, third-party connectors and unnecessary history where the product permits. Use the firm account, not a personal account.
- Limit access. Apply role-based permissions, multifactor authentication and the least privilege needed for the matter. Turn on audit logging and review unusual access.
- Set retention and deletion. Use the shortest practical retention period, follow the firm’s matter-closing procedure and confirm how deletion propagates to indexes, logs and backups.
An “incognito” or private-browser window does not prevent a provider from retaining or accessing information on its servers. Browser privacy settings and provider retention controls solve different problems.
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What security controls should a firm require?
Technical settings cannot replace a legal analysis, but they make an approved use safer. At minimum, an implementation should address:
- Identity: individual accounts, multifactor authentication and single sign-on where available; never shared credentials.
- Authorization: role-based access, matter-level separation and prompt removal of departing personnel.
- Isolation: tenant separation and controls that prevent one customer or matter from seeing another.
- Encryption: encryption in transit and at rest, with documented key-management responsibilities.
- Monitoring: audit logs for logins, uploads, downloads, sharing and administrative actions, retained long enough to investigate.
- Administration: a restricted group that can change training, connectors, retention and sharing settings.
- Recovery: documented backup, deletion and incident-response procedures that cover the AI service and its subprocessors.
Record which controls are actually enabled. A feature listed in a product brochure does not protect the firm if it is unavailable on the chosen plan or disabled in the tenant.
How should a firm govern employees and review AI outputs?
Publish a written permissible-use policy before deployment. The policy should identify approved tools and configurations, prohibited inputs, required redaction, consent triggers, retention rules, incident reporting, records to keep and the person responsible for supervision.
Train and supervise every user
Training should cover confidentiality, security settings, privilege, hallucinated authorities, biased or incomplete analysis, billing accuracy and the difference between a draft and professional judgment. Lawyers remain responsible for work delegated to staff and vendors. Supervisors should review whether users follow the approved workflow, not merely whether the final document looks polished.
Verify every consequential output
Before relying on or disclosing an AI-generated result, a lawyer should independently check:
- case citations, quotations, statutory text and procedural rules against authoritative sources;
- calculations, dates, names, defined terms and factual assertions against the file;
- privilege, confidentiality and conflicts treatment;
- the completeness and balance of the analysis, including contrary authority;
- filing requirements, signatures, exhibits and any statement that a court or client could treat as the lawyer’s own representation.
Save the reviewed version and the material prompts or source notes needed to explain how the work was produced, subject to the firm’s retention policy. Do not bill a client for time the lawyer did not actually spend or for automated work in a way that violates applicable billing rules; Florida Opinion 24-1 expressly flags improper billing as a compliance concern.
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What should an AI-use policy and approval record contain?
A short policy can be operational if it answers the questions users face at the moment of upload.
- Scope: approved tools, plans, models, integrations and user groups.
- Data classes: public, internal, confidential, privileged, personal and highly restricted information, with examples.
- Permitted tasks: drafting, summarization, classification, translation or research, each with its allowed data class.
- Prohibited actions: uploading unredacted client files to unapproved services, enabling public sharing, relying on uncited output or allowing unsupervised external access.
- Consent: when a lawyer must consult the client, what must be explained and where the decision is recorded.
- Human review: who verifies authorities, facts, calculations, privilege and final disclosures.
- Security: authentication, permissions, encryption, logging, retention, deletion and device requirements.
- Incident response: whom to notify, how to preserve evidence and how to assess contractual, ethical and legal notice duties.
- Change management: who reviews new models, features, subprocessors and contract amendments before activation.
For each use case, keep an approval record containing the matter and task, data classification, tool and edition, relevant contract terms, configured safeguards, consent decision, reviewer and review date. This creates an auditable explanation of why the use was reasonable at the time.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should a firm do if data is exposed or the provider changes its terms?
Stop the affected workflow, preserve relevant logs and prompts, and notify the firm’s designated security and ethics contacts. Determine what information was accessible, to whom, for how long, and whether the provider or a subprocessor retained or reused it. Then follow the engagement terms, applicable law, bar obligations and the provider’s breach-notice procedure; do not promise a client that no disclosure occurred until the facts are established.
If a provider changes training, retention, subprocessors, data location or access terms, pause new uploads until the change is reviewed. Reconfigure the tenant, obtain updated consent where the risk has materially changed, or move the task to a different workflow. Update the tool inventory and approval record so users do not continue relying on an outdated assumption.
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How should firms compare two legal-AI options?
Use the same questions for every candidate rather than comparing brand names or model features in isolation.
| Comparison axis | Evidence to collect | Decision question |
|---|---|---|
| Training use | Contract language and a tenant setting showing whether customer data trains or improves models | Can the firm disable reuse, and is that choice enforceable? |
| Retention and deletion | Default and configurable periods, backup handling, export and deletion confirmation | Can the firm meet its matter-closing and client obligations? |
| Isolation and logging | Tenant architecture, matter separation and downloadable audit logs | Can the firm detect and investigate unauthorized access? |
| Identity and administration | Multifactor authentication, single sign-on, role controls and administrative segregation | Can access be limited to the people who need it? |
| Contract protections | Confidentiality, breach notice, subprocessors, location, audit rights and remedies | Does the agreement support supervision and incident response? |
| Privilege and conflicts | Who may access content and how outsourced work is handled | Could use affect privilege or create a conflict that requires client action? |
| Workflow and review | Source linking, export controls, approval gates and human-review checkpoints | Can a lawyer verify the result before it reaches a client or court? |
| Total burden | License, administration, training, security work and consent requirements | Is the efficiency worth the continuing compliance effort? |
A tool that is less capable but offers clear retention, isolation and review controls may be the safer choice for sensitive matters. Conversely, a highly secure service still requires a task-specific decision; no contract makes every use appropriate.
What are the most common mistakes, and how can they be fixed?
| Mistake | Why it fails | Fix |
|---|---|---|
| Copying an entire client email thread into a public chatbot | It sends unnecessary identifiers and strategy to a service whose retention and access are unknown. | Use a hypothetical or redacted excerpt in an approved account, or perform the task without AI. |
| Assuming “enterprise” means no training or no human access | Product tiers differ, and defaults can change. | Verify the exact contract and tenant settings in writing. |
| Relying on a generic engagement-letter sentence | The client may not understand the tool, data, risks or alternatives. | Have a matter-specific informed-consent conversation when required. |
| Treating a closed firm deployment as risk-free | Insiders, administrators, integrations, logs and self-learning can still expose data. | Apply least privilege, isolation, logging and a documented risk assessment. |
| Sending an AI draft directly to a client or court | AI can invent authorities, omit facts or mishandle privilege. | Require lawyer verification of every consequential assertion and filing. |
| Leaving an old account active after a matter or employee ends | Historical prompts and files remain accessible. | Use offboarding checklists, revoke access and execute the retention/deletion procedure. |
What is a practical approval workflow for a new use case?
Use the following sequence whenever a lawyer proposes a new tool, model or category of client information:
- Describe the task and the desired output in one sentence.
- Classify every proposed input and identify whether client consent, privilege analysis or another legal review is triggered.
- Test whether public, synthetic, redacted or local data can produce an adequate result.
- Collect and review the provider’s current retention, training, sharing, security, deletion, breach and subprocessor terms.
- Configure identity, permissions, isolation, logging, encryption, retention and deletion controls; disable unnecessary features.
- Document the risk assessment, decision-maker, safeguards and consent result in the matter or firm inventory.
- Run a limited pilot with non-sensitive data, evaluate accuracy and workflow, and train users before expanding.
- Require lawyer review of each output and periodically recheck the provider, configuration and governing ethics guidance.
This process keeps the decision tied to the specific client, matter and tool instead of treating “AI” as a single risk category. It also gives the firm a defensible record if the client, a regulator or a court later asks how the decision was made.
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Can I use a free consumer AI account for a client memo?
Only if the firm has approved that exact service and verified its current terms and settings; free access often provides little control over retention, training, administration or support. If those facts cannot be established, use a firm-approved service with non-sensitive or synthetic text instead.
Does attorney-client privilege automatically cover prompts sent to an AI provider?
No. Privilege depends on the purpose of the disclosure, who can access the information and the law of the relevant jurisdiction. Analyze privilege separately and obtain specialist advice when the provider or its subprocessors may access substantive client material.
What if my client’s engagement terms prohibit generative AI?
Follow the client’s instruction and do not use the tool for that matter unless the client gives a clear, informed change in direction. Record the restriction so staff do not accidentally apply a general firm permission to the prohibited matter.
How often should a firm recheck an AI provider?
Set a recurring review schedule, such as at least annually, and trigger an immediate review when the provider changes its model, training policy, subprocessors, data location, retention or security controls. A stale approval is not evidence that the current configuration remains safe.
Can AI-generated text be filed without disclosing that AI was used?
The lawyer remains responsible for the filing regardless of disclosure, and court-specific rules may impose additional requirements. Verify every authority, quotation, factual statement, calculation and procedural requirement, and check the applicable court’s current rules before filing.
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