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Protecting confidentiality with legal AI requires a matter-by-matter risk decision, not a brand or product label. Before entering anything related to a representation, identify the information and task, inspect the specific service’s retention, access, sharing, training, storage, and deletion practices, and use the least revealing input that can complete the work. Then apply the professional-conduct rules in your jurisdiction, decide whether client communication or informed consent is required, and keep human supervision and verification in place.
ABA Formal Opinion 512 (2024) states: “Before lawyers input information relating to the representation of a client into a GAI tool, they must evaluate the risks that the information will be disclosed to or accessed by others outside the firm.” A secure configuration reduces risk, but it does not automatically preserve privilege, satisfy every ethics rule, or make generated work reliable.
What does the duty of confidentiality require when I use legal AI?
The duty covers information relating to a client representation, not only information that would be embarrassing or obviously secret. A prompt, uploaded pleading, contract, chronology, billing record, or internal strategy note can fall within that scope even when it does not contain a client’s name.
ABA Formal Opinion 512 directs lawyers to evaluate the risk of disclosure or unauthorized access before entering such information into generative AI. The analysis turns on the particular matter, client, task, tool, sensitivity of the data, available safeguards, and likely effect on the representation. A service marketed for legal work is not automatically confidential, and a private account is not proof that data cannot be accessed or reused.
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Confidentiality is only one part of the professional analysis. Competence, supervision, independent judgment, communication with the client, and verification of work remain relevant after a tool has been approved. Florida Ethics Opinion 24-1 and North Carolina 2024 Formal Ethics Opinion 1 likewise place responsibility on the lawyer rather than on the software vendor.
How should I classify the information and task before using AI?
Start with the proposed input and the result you need. The same service may be acceptable for a public statute but inappropriate for a client’s unfiled medical record, depending on its controls and the governing rules.
Identify whether the material relates to a representation
Mark information that came from a client, a prospective client, an opposing party under a duty of confidentiality, or your work on a matter. Include indirect details that could reveal the client or strategy when combined with public information. Internal notes and draft work product may also expose the representation.
Rate sensitivity and consequences
Consider whether the material includes personal identifiers, health or financial information, trade secrets, credentials, settlement positions, litigation strategy, facts covered by a protective order, or information subject to a contractual or statutory restriction. Ask what harm could result from disclosure, alteration, retention, or use to improve a model.
Define the minimum useful task
Describe the output precisely: for example, “extract all dates from this public regulation” is narrower than “analyze this client’s entire file and recommend a litigation strategy.” Determine whether a smaller excerpt, a redacted version, a synthetic example, or a local non-cloud process would achieve the same objective.
- Use public or synthetic material when the task does not require client facts.
- Separate general legal research from matter-specific analysis.
- Remove details that do not affect the requested output.
- Record why the remaining information is necessary for the task.
What data practices must I check in the specific AI service?
Read the current contract, privacy terms, security documentation, and administrator settings for the exact service and account type. Marketing language such as “enterprise,” “secure,” or “for legal professionals” does not answer the questions below.
Retention and deletion
Find out whether prompts, uploaded files, outputs, logs, and support records are retained; the default period; and whether the firm can set a shorter period. Confirm how deletion works, whether backups persist, and whether the provider can produce a deletion confirmation. A “delete” button may remove a workspace view without immediately removing copies from backups or abuse-monitoring systems.
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Training, self-learning, and product improvement
Determine whether submitted content is used to train, fine-tune, evaluate, or otherwise improve a model. Check whether the setting applies to all data types, whether it is enabled by default, and whether human reviewers or contractors can see samples. A promise not to train one model does not necessarily cover support tickets, telemetry, or a different feature in the same account.
Access and sharing
Identify provider employees, subprocessors, affiliates, and other third parties that may access data. Review role-based permissions, single sign-on, multifactor authentication, audit logs, and administrator ability to disable sharing. Check whether a user can publish a link, invite an external collaborator, or move a conversation into a personal account.
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Storage location and security controls
Ask where content and backups are stored and whether data crosses national borders. Review encryption in transit and at rest, key-management options, vulnerability response, incident notification, and independent security assessments. For highly sensitive matters, obtain qualified information-security advice instead of relying solely on a vendor questionnaire.
Export, portability, and termination
Confirm whether the firm can export prompts, outputs, audit records, and configuration data in a usable format. Check what happens when a user leaves, a subscription ends, or the provider changes its terms. A workflow that cannot be audited or recovered may create additional professional and records-management risk.
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Look for confidentiality obligations, limits on secondary use, subprocessor terms, breach-notification deadlines, data-location commitments, and the provider’s right to change policies. Have procurement or outside counsel review terms that conflict with engagement letters, protective orders, court rules, or client instructions.
How can I minimize the information sent to an AI system?
Use the least revealing workable input. Minimization reduces the impact of a mistake but does not eliminate the need to assess the service and jurisdiction.
Prefer synthetic or generic examples
For prompt design, testing, formatting, or workflow experiments, create fictional parties, dates, amounts, and facts. Test the process with public filings or a sample contract before introducing matter data.
Redact unnecessary identifiers
Remove names, addresses, account numbers, medical details, credentials, unique transaction references, and other fields that do not change the requested answer. Replace them consistently with neutral labels such as “Client A” and “Vendor B” so the output remains usable.
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Anonymization is not a guarantee. A rare fact pattern, a distinctive job title, a small community, or a combination of dates can permit re-identification. Keep the key that maps labels to real people outside the AI service, restrict access to it, and assess whether the remaining context could identify the matter.
Arizona State Bar best practices recommend anonymization for public platforms. North Carolina guidance advises generally avoiding client-specific information in public AI resources unless adequate safeguards and applicable obligations have been assessed. Treat both as risk guidance tied to their jurisdictions, not as a universal safe harbor.
Can I put client information into a public AI tool?
Do not assume that a publicly available tool is suitable for client information. Public access often means the default account, retention, sharing, and training settings are designed for a broad consumer audience rather than a law firm’s confidentiality obligations.
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Before using such a service, determine whether the task can be completed without client-specific information. If it cannot, evaluate the service’s actual controls, the sensitivity of the data, and the rules that govern the representation. North Carolina’s 2024 Formal Ethics Opinion 1 cautions against entering client-specific information into public AI resources without adequate safeguards. Arizona guidance similarly emphasizes anonymization, vendor terms, and security advice.
Turning off a training setting or deleting a conversation does not by itself address every risk. You still need to consider access by the provider or subprocessors, retention in logs or backups, cross-border storage, accidental sharing, and whether the client’s expectations or instructions restrict the use.
When do I need to communicate with the client or obtain informed consent?
There is no single nationwide answer. Apply the professional-conduct rules adopted in the jurisdiction governing the representation, together with the engagement agreement, client instructions, protective orders, and the facts of the task.
Evaluate the nature of the use
Using AI to organize public authorities is different from asking it to assess a client’s options, draft advice from confidential facts, or make a recommendation that you may adopt. The more substantive the delegation and the more sensitive the input, the stronger the case for disclosure and informed consent.
Explain what the client needs to decide
If communication is required or prudent, describe the purpose of the AI use, the categories of information involved, the service’s material retention and access practices, the safeguards in place, and the alternatives. Explain that you remain responsible for professional judgment and verification. Generic boilerplate may not provide meaningful consent if it does not identify the proposed use and material risks.
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Check matter-specific restrictions
A client may prohibit external processing, require a particular vendor, or impose data-location and deletion conditions. Government clients, regulated businesses, and matters governed by protective orders may have additional requirements. Document the decision and any limits the client accepts.
ABA Formal Opinion 512 and North Carolina’s opinion emphasize that the need for communication or consent depends on the circumstances. Florida’s advisory opinion is not binding, and state ethics opinions should not be presented as a nationwide rule.
How should a firm create controls for legal AI?
A written policy turns individual caution into a repeatable process. It should be specific enough that a lawyer or staff member can decide what to do before opening a prompt window.
Approve tools and account types
Maintain an inventory of approved services, permitted features, account owners, data classifications, and prohibited uses. Distinguish an administrator-managed business account from a personal account, browser plug-in, mobile app, or feature that sends data to a different provider.
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Control access
Use firm-managed identities, multifactor authentication, least-privilege roles, and timely offboarding. Disable public sharing where possible. Keep audit logs and review them for unusual downloads, external invitations, or use of unapproved workspaces.
Train and supervise users
Training should cover confidentiality, prompt minimization, hallucinated authorities, copyright and data ownership, secure handling of exports, and incident reporting. Supervising lawyers must know when a task requires direct review rather than unsupervised delegation.
Set review and reapproval dates
Vendor terms, model behavior, subprocessors, and settings can change. Assign an owner to recheck contracts and privacy controls periodically and whenever the provider introduces a new feature, changes a policy, reports an incident, or changes storage locations.
Keep an auditable decision record
For higher-risk uses, record the matter classification, task, service and account, data minimization steps, consent analysis, safeguards, reviewer, and date of approval. Store the record where the firm can retrieve it without copying confidential prompts into an uncontrolled system.
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AI output is an aid, not a substitute for legal judgment. The responsible lawyer must verify authorities, quotations, citations, calculations, dates, procedural requirements, and factual assumptions before relying on the result.
Check primary sources
Open the cited case, statute, rule, or regulation and confirm that it exists, is current, and supports the proposition stated. Treat uncited assertions and confident summaries as unverified until checked.
Compare against the matter record
Confirm names, dates, defined terms, jurisdiction, deadlines, and client instructions against authoritative files. Do not allow an AI-generated summary to become the sole record of what a client said or what a document provides.
Review for leakage in the output
Before sending a draft, inspect it for confidential information from another matter, invented facts, hidden metadata, prompt fragments, or content that the intended recipient should not receive. Remove unnecessary client details from comments and tracked changes.
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North Carolina’s 2024 Formal Ethics Opinion 1 permits AI use when the lawyer uses it competently and securely, protects confidentiality, and provides proper supervision when relying on or implementing its work product. That condition means the lawyer—not the system—owns the final professional decision.
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What should I do if the tool changes terms or a disclosure occurs?
Treat a material policy change or suspected exposure as a matter requiring prompt assessment, not as a routine software update.
- Stop the affected workflow and prevent further uploads or sharing.
- Preserve relevant logs, account settings, contracts, prompts, and notifications without spreading the confidential content.
- Notify the firm’s designated security, privacy, and supervising personnel.
- Determine what information was involved, who could access it, the retention period, and whether deletion or access revocation is possible.
- Review duties to the client, court, insurer, regulator, or opposing counsel under the governing rules and agreements.
- Document the analysis, remedial steps, and decision to resume, restrict, or discontinue the service.
Do not assume that a vendor’s statement resolves whether a disclosure waived attorney-client privilege. None of the cited ethics materials decides that issue; privilege consequences must be assessed under governing law and the specific facts.
How do the cited ethics materials differ by jurisdiction?
These materials illustrate the common risk themes while preserving their different legal scope.
| Material | Date and scope | Practical emphasis |
|---|---|---|
| ABA Formal Opinion 512 | 2024; interprets ABA Model Rules as professional guidance | Evaluate disclosure and unauthorized-access risk before entering representation-related information; consider competence, supervision, communication, and verification. |
| Arizona State Bar best practices | Arizona guidance | Use safeguards, consider anonymization for public platforms, obtain information-technology or security advice when warranted, and examine vendor terms. |
| Florida Ethics Opinion 24-1 | Florida advisory ethics opinion | Examine retention, sharing, self-learning, and lawyer responsibility; verify AI work. Advisory opinions are not binding. |
| North Carolina 2024 Formal Ethics Opinion 1 | North Carolina jurisdiction-specific opinion | AI use must be competent, secure, confidential, and supervised; exercise caution with public tools and continue reviewing practices as technology changes. |
Use the rule and opinion that actually governs the representation. ABA Model Rules guidance does not replace rules adopted by a state, and one state’s opinion should not be described as a universal legal requirement.
What is a practical pre-use checklist?
- Have I identified the client, matter, data classification, and precise task?
- Can I complete the task with public, synthetic, redacted, or less detailed information?
- What does the current contract say about retention, backups, training, sharing, subprocessors, storage location, deletion, and export?
- Are access controls, multifactor authentication, audit logs, and administrator settings enabled?
- Could the remaining details permit re-identification?
- Do the jurisdiction, engagement letter, protective order, client instructions, or law require communication or consent?
- Who will supervise the use and verify the output?
- How will the firm detect a policy or vendor change and respond to an incident?
If any answer is unclear, pause the upload and obtain guidance from the firm’s supervising lawyer, privacy or security adviser, or counsel familiar with the applicable professional rules.
Frequently Asked Questions
Does using a paid or enterprise AI account automatically protect privilege?
No. Account pricing and labels do not establish confidentiality, prevent provider access, or determine whether a disclosure waives privilege. Privilege consequences depend on governing law, the facts, and the service’s actual practices.
Can I use an AI plug-in that reads documents inside my case-management system?
Treat the plug-in as a separate service unless your contract and technical documentation establish otherwise. Check what data leaves the system, which subprocessors receive it, whether the plug-in stores or trains on content, and whether permissions follow your firm’s access controls.
Should I keep a record of every prompt used on a matter?
The appropriate record depends on the matter, firm policy, and applicable records duties. For higher-risk uses, preserve enough information to show the tool, data classification, safeguards, reviewer, and decision without creating an uncontrolled duplicate of the confidential content.
What if a client asks me not to use AI after I have already used it?
Follow the client’s instruction prospectively and assess whether prior use created retention, disclosure, or consent issues. Review the service’s deletion and export controls, document the steps taken, and consider whether the client or another authority must be informed.
Is a local or offline model always safe for confidential work?
Offline processing can reduce transmission and provider-access risks, but it does not remove risks from endpoint compromise, backups, user access, inaccurate output, or unauthorized internal use. Apply the same classification, minimization, supervision, and verification process.
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