Use AI legal tools only within a documented confidentiality and supervision process. Before putting any client-related text or file into a system, confirm which professional-conduct rules, court orders, engagement terms, and client instructions apply; understand the tool’s complete data lifecycle; minimize and protect the material; obtain informed consent when required; restrict connected-system access; and have a qualified lawyer verify every consequential output. An “enterprise,” “private,” or “no-training” label is not, by itself, proof that a particular use is permissible.
The governing details depend on your jurisdiction, the matter, the data, and the tool’s live configuration. The ABA Model Rules provide a useful baseline, while the State Bar of California’s 2025 practical guidance adds state-specific direction on material confidentiality risks, integrated systems, and autonomous agents.
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Start with the professional duty, not the product name
AI changes how information is processed, but it does not replace a lawyer’s existing duties. ABA Model Rule 1.6(a) states: “A lawyer shall not reveal information relating to the representation of a client unless the client gives informed consent, the disclosure is impliedly authorized in order to carry out the representation or the disclosure is permitted by paragraph (b).” The rule also requires reasonable efforts to prevent inadvertent or unauthorized disclosure of, or unauthorized access to, information relating to a representation.
That baseline covers more than obvious secrets such as a client’s name or a settlement amount. Prompts, uploaded pleadings, internal notes, transaction terms, metadata, identifying combinations of facts, and the fact that a person sought legal advice may all relate to a representation. A tool can create a confidentiality problem through its collection, retention, sharing, indexing, or compromise even when a lawyer never intentionally publishes the information.
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ABA Formal Opinion 512, issued July 29, 2024, frames generative AI through the duties lawyers already owe: “To ensure clients are protected, lawyers using generative artificial intelligence tools must fully consider their applicable ethical obligations, including their duties to provide competent legal representation, to protect client information, to communicate with clients, to supervise their employees and agents, to advance only meritorious claims and contentions, to ensure candor toward the tribunal, and to charge reasonable fees.”
Check the controlling rule in the jurisdiction governing the representation rather than assuming that the ABA model text has been adopted verbatim. Also check protective orders, discovery restrictions, regulatory requirements, engagement letters, outside-counsel guidelines, and written client instructions. A client may prohibit external AI processing even when a professional-conduct rule would permit a particular disclosure.
Map the tool’s entire data lifecycle
Do not evaluate an AI service from a single marketing statement. Document what happens from the moment a user types or uploads information until every copy, index, log, and backup is deleted or expires. The following questions should be answered for the exact edition, account type, region, and configuration your firm will use.
| Lifecycle area | Questions to answer before use | Why it matters |
|---|---|---|
| Collection | What prompt text, files, images, metadata, user identifiers, telemetry, and error logs are collected? Are optional analytics enabled? | Information outside the intended task can still relate to the representation. |
| Use | Is the material processed only to answer the request, or also for abuse detection, product improvement, evaluation, personalization, or other purposes? | A secondary use may be a disclosure or unauthorized use under the applicable rule or client contract. |
| Training or refinement | Are inputs or outputs used to train, fine-tune, evaluate, or refine a model? Is the setting account-wide, workspace-specific, or unavailable? | Training and refinement can extend access and retention beyond the immediate matter. |
| Retention and deletion | How long are prompts, uploads, generated outputs, logs, and backups retained? Can a firm administrator delete them, and when does deletion propagate? | A deletion button may not immediately remove every operational or backup copy. |
| Disclosure | Which employees, contractors, subprocessors, support personnel, or integrated services can access the data? In what countries is it processed? | Third-party access and cross-border processing may require additional authorization or controls. |
| Security | What authentication, encryption, tenant isolation, vulnerability management, audit logging, incident notification, and access-review controls are documented? | Reasonable efforts require a risk assessment, not reliance on an unqualified assurance. |
| Connected systems | Can the tool read email, document repositories, calendars, case-management systems, knowledge bases, or other client files? | Integrations can expose substantially more information than a single prompt. |
| Autonomy | Can the system send messages, edit or delete records, file documents, change permissions, or trigger workflows without a person approving each action? | External actions need bounded authority, monitoring, and human review. |
Read the applicable terms, privacy policy, security documentation, data-processing terms, retention schedule, and administrator settings. Ask the provider specific written questions when documentation is ambiguous. California guidance cautions that generalized marketing assurances alone may not establish that reasonable efforts have been made. A qualified information-technology or cybersecurity professional can help interpret architecture, access paths, and contractual controls.
Use a repeatable approval workflow
1. Classify the proposed task and information
Describe the task in plain language: for example, extracting dates from a public statute, summarizing an internal chronology, drafting a client email, or searching a matter repository. Classify every input as public, firm-confidential, client-confidential, privileged, subject to a protective order, personal data, regulated data, or another category defined by your policy. Include information that could identify a client when combined with otherwise harmless facts.
Record the matter, responsible lawyer, intended users, destination of the output, and whether the request involves a court filing, advice, negotiation, discovery response, or another high-consequence activity. A clear task description prevents a broad “AI is approved” decision from being reused for a materially different purpose.
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2. Identify the governing requirements
Check the lawyer’s jurisdiction and any jurisdiction-specific ethics opinions, court rules, orders, and statutes. Review the engagement agreement, outside-counsel guidelines, confidentiality provisions, data-location requirements, and client instructions. If several lawyers or offices are involved, identify which rules and contractual controls apply to each transfer.
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3. Verify the exact configuration
Capture the product edition, workspace, region, enabled integrations, user roles, retention settings, training or refinement controls, and administrator policies. A feature can behave differently in a consumer account, a firm-managed workspace, an application programming interface, or an embedded legal application. Save the relevant version and settings with the approval record so a later change can trigger reassessment.
4. Decide whether the task can be completed without confidential material
Try a public, synthetic, or hypothetical example first. A lawyer may be able to ask for a general explanation of a procedural concept, a neutral outline, or a formatting transformation without revealing a client’s facts. If the task still requires matter information, define the minimum fields needed and remove everything else.
5. Review prompts, files, and metadata
Inspect the prompt and every attachment before submission. Remove names, direct identifiers, account numbers, contact details, unique dates, document properties, comments, tracked changes, hidden sheets, embedded images, and unrelated matter content when they are not necessary. Check generated summaries and intermediate files as well as the final document.
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6. Make and record the authorization decision
Document why the tool, configuration, data minimization, and access controls are reasonable for this task. State whether the use is permitted under the governing rule and client terms, whether informed consent is needed, who approved it, and what restrictions apply. Define an expiration or review date for higher-risk uses instead of treating approval as permanent.
7. Run the task in a controlled workspace
Use individual accounts with strong authentication, least-privilege permissions, and the firm-approved workspace. Do not paste client material into an unapproved personal account, public demonstration, browser extension, or plug-in. Keep matter separation intact and label outputs so they are not mistaken for verified legal work.
8. Review, store, and dispose
Compare the output with the source documents and controlling law. Correct errors before anyone relies on it, and preserve the final work product in the authorized matter system rather than in an uncontrolled chat history. Delete temporary prompts, uploads, and exports according to the firm’s retention schedule, subject to litigation holds and other preservation duties.
Decide when informed consent or client communication is required
Consent is fact- and jurisdiction-dependent. California’s 2025 practical guidance states: “As a general matter, a lawyer must not input any confidential information of the client into a generative AI solution that may present material risks to confidentiality or security, absent informed client consent (see rule 1.0.1(e)) as to the underlying risks.” This is California guidance, not a universal rule that every AI use requires consent.
For a proposed use with a material confidentiality or security risk, informed consent should explain what information will be submitted, the purpose, the tool or service category, who may receive or access it, retention and training practices, known limitations, the safeguards in place, and meaningful alternatives. Give the client enough context to make an informed choice; a vague statement that the firm “uses technology” is not equivalent to consent to a specific risk.
Evaluate communication obligations throughout the representation. Consider the technology, the sensitivity and volume of information, the scope of the engagement, the client’s sophistication, the expected benefit, and whether the use changes the service or risk profile. Follow a client’s instruction restricting AI even if you believe the tool is secure. Record the decision and any conditions, and revisit it if the system, task, or client instructions change.
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Apply stronger controls to integrated and agentic systems
An isolated drafting interface is not the same as an agent that can search a document repository, read email, update a case-management record, or send an external message. The more systems an AI can reach, and the more actions it can take, the greater the potential impact of a mistaken instruction, prompt injection, excessive permission, or cross-matter retrieval.
Limit access by task and matter
- Give the system access only to the repository, folder, mailbox, or records required for the approved task.
- Enforce matter-level permissions and prevent broad “all firm” search unless it is specifically justified.
- Use separate service identities and rotate credentials; never share a lawyer’s personal login with an automated process.
- Disable tools and connectors that are not required, including automatic synchronization and unrestricted web retrieval.
Require approval before external action
Configure a human checkpoint before an agent sends an email, transmits a file, files a document, changes a client record, grants access, or takes another consequential action. The reviewer should see the proposed action, the data it will transmit, the destination, and the evidence supporting it. California guidance warns that poorly configured agents may disclose information across matters and calls for appropriate safeguards and human review for autonomous external transmission.
Monitor and test
Log authentication, retrievals, prompt and connector activity where appropriate, attempted policy violations, and external actions. Review logs for unusual access, cross-matter results, bulk downloads, and repeated failed authorization. Test with synthetic matters for leakage, privilege-boundary failures, prompt injection, hallucinated permissions, and unsafe fallback behavior before production use. Monitoring does not eliminate the need for least privilege or lawyer review; it provides evidence that controls are operating.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep human responsibility and legal verification intact
Confidentiality review and substantive accuracy review are separate controls. A response can stay within the permitted data boundary and still be wrong, incomplete, biased, or unsupported. The California guidance says AI use must not diminish or abdicate professional judgment and that a lawyer remains fully responsible for AI-assisted outputs and work product.
For each material output, the responsible lawyer should:
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- Check whether the system omitted adverse facts, confused matters, invented authority, or relied on outdated law.
- Confirm that the output matches the assignment, client objectives, court requirements, and professional duties.
- Review tone, privilege markings, confidentiality labels, and recipients before transmission.
- Document the level of review appropriate to the risk and retain supporting sources in the matter file.
Do not present an AI-generated draft as independently verified legal advice. Do not delegate the decision to sign, file, advise, negotiate, or disclose to a system that lacks the authority and judgment required for that decision.
Build firm-wide policy, supervision, and training
Individual caution is not a substitute for governance. Firm leaders should publish a policy that distinguishes permitted, restricted, and prohibited uses and identifies who may approve exceptions. The policy should cover:
- Approved tools, account types, regions, integrations, and configuration baselines.
- Data classifications and examples of information that may never be entered into an unapproved service.
- Required minimization, de-identification, metadata review, and matter separation.
- Consent and client-communication triggers, documentation, and escalation paths.
- Authentication, least privilege, logging, retention, deletion, and export requirements.
- Human review standards for research, drafting, analysis, filings, communications, and autonomous actions.
- Incident reporting, preservation, client notification, regulator notification, and remediation responsibilities.
- Approval and reassessment when a vendor changes terms, adds a connector, changes model behavior, or expands autonomy.
Train lawyers, paralegals, assistants, contractors, and IT administrators on realistic examples. Training should show how a seemingly harmless prompt can reveal a client through context, how hidden metadata travels with a file, how retrieval permissions can cross matters, and how to stop an agent before it transmits information. Supervisors should review actual use, not merely distribute a policy. California guidance expressly points to policies, training, supervision, and updates as systems become more autonomous or integrated.
Compare tools by controls, not labels
When evaluating two legal AI products or configurations, use the same questions for each. A feature checklist is more useful than a generic security badge or a broad “enterprise” description.
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| Comparison axis | Evidence to request | Decision question |
|---|---|---|
| Prompt and file handling | Data-flow diagram, input categories, telemetry description, and administrator settings. | Can the firm restrict collection to what the approved task needs? |
| Model training or refinement | Contract language and technical controls showing whether customer content is excluded, and under what exceptions. | Will client material be used beyond the requested service? |
| Retention and deletion | Retention periods, deletion workflow, backup treatment, and legal-hold behavior. | Can the firm meet its confidentiality, preservation, and disposal requirements? |
| Third-party access | Subprocessor list, support-access rules, processing locations, and incident-notification terms. | Who can access the information and how quickly will the firm learn of a breach? |
| Security controls | Authentication, encryption, tenant isolation, audit logs, vulnerability management, and independent assurance details. | Are the safeguards proportionate to the matter’s sensitivity? |
| Firm-system access | Connector permissions, scope filters, role mapping, and revocation process. | Can access be limited to the right matter and removed promptly? |
| Autonomy and external action | Action permissions, approval gates, sandboxing, rate limits, and kill-switch procedures. | Can a person inspect and stop a consequential action before transmission? |
| Monitoring and review | Event logs, alerting, export capability, and reviewer controls. | Can the firm detect misuse and demonstrate oversight? |
The cited professional guidance does not establish a universal certification threshold, rank vendors, or declare a particular product compliant. The decision remains tied to the actual tool, configuration, task, jurisdiction, and client requirements.
Prepare for mistakes and suspected exposure
Include AI-related events in the firm’s incident-response plan. A suspected exposure may involve a misdirected prompt, an overbroad connector, a compromised account, an agent’s unauthorized transmission, or a provider notification. Preserve relevant logs and messages, stop further processing, revoke tokens or connectors, and identify every matter and recipient potentially affected.
Notify the supervising lawyer, security and privacy leads, and the client or regulator when required by the applicable rule, contract, law, or court order. Assess privilege, work-product implications, preservation obligations, and whether an external disclosure can be contained or recalled. Record the timeline, decisions, and remediation. After containment, correct permissions, rotate credentials, update the policy, retrain users, and reassess whether the tool remains appropriate.
A practical pre-use checklist
- Have I identified the governing jurisdiction, court orders, engagement terms, and client instructions?
- Do I know exactly what the tool collects, stores, uses, discloses, and deletes?
- Are training, refinement, subprocessors, processing locations, and support access documented?
- Is the chosen account and configuration approved for this data classification?
- Have I minimized prompts, files, identifiers, metadata, and unrelated matter content?
- Could the remaining details identify the client or matter?
- Is informed consent or a client communication required for this risk and jurisdiction?
- Are integrations limited to the matter and task, with least-privilege permissions?
- Will a human approve every external transmission or consequential action?
- Who will verify the output against source documents and current law?
- Where will the final work product and temporary material be stored or deleted?
- When will the use be reassessed if the tool, task, or client requirements change?
Reassess as the system and matter change
AI services evolve through model updates, new connectors, revised retention terms, and expanded autonomous features. A use that was acceptable for a public-law summary may not be acceptable for privileged discovery material or a cross-border transaction. Reassess when the provider changes its terms or architecture, when the firm enables a new integration, when the matter enters litigation, when the client changes instructions, or when the system is used for a new legal task.
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The safest operating principle is straightforward: treat every AI interaction involving client information as an information-governance decision. Apply the controlling professional rules, verify the tool’s real behavior, disclose or obtain consent when the circumstances require it, constrain access and autonomy, and keep a lawyer accountable for both confidentiality and the quality of the work.
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