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Before putting client information into a local AI tool, verify where every part of the workflow sends and stores it—not just where the model runs. Prompts, documents, extracted text, indexes, outputs, logs, telemetry, backups, updates, and support connections may follow different paths. A local installation does not remove a lawyer’s duties to protect client information, use technology competently, and review AI-generated work.
1. What does “local” mean in this deployment?
Trace the full workflow from the moment a user selects a document through the creation, storage, and deletion of the response. A model may run on a firm-controlled computer while the surrounding application uses a remote service for another function. Ask the product provider or your IT team to identify each component and its data path rather than relying on the word “local.”
- Inputs: prompts, uploaded files, extracted text, and document metadata.
- Processing artifacts: embeddings, indexes, caches, and temporary files created for retrieval or analysis.
- Outputs and records: generated responses, chat history, audit logs, crash reports, and diagnostic data.
- Supporting services: the user interface, connectors, telemetry, license checks, model downloads, updates, remote administration, and vendor support tools.
- Copies: cloud or network sync, snapshots, archives, and backups.
For each item, establish whether it remains on the device, moves to another firm-controlled system, or leaves the firm’s environment. Record who can access it and how long it is kept. NIST’s National Cybersecurity Center of Excellence described an internally installed chatbot designed to keep interactions within its secure network in the initial public draft of NIST IR 8579, dated July 2025. That is an example architecture, not evidence that other local AI products keep every component or data type inside a firm’s network. The draft also identifies risks including prompt injection, data exposure, and unauthorized access.
2. What happens to prompts and documents after use?
Inspect the application’s settings, documentation, and applicable terms for retention, reuse, training, sharing, and deletion. Look separately at conversation history, uploaded originals, extracted text, indexes, logs, and backups; a “delete chat” control may not delete every copy or derived artifact.
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- Is client information retained, and for how long?
- Can prompts, documents, or outputs be used to train or improve a model, or shared with another party?
- Can a user disable telemetry, history, or cloud synchronization, and does that setting cover all components?
- What happens to stored information if the firm changes vendors, ends a service, or removes the application?
- Can the firm export or securely delete the relevant data, including indexes and backups?
North Carolina State Bar Formal Ethics Opinion 1 advises lawyers to consider whether an AI program retains information and subsequently uses it. It also cautions that an in-house derivative can still send inputs to a central program. Confirm the behavior of the particular deployment rather than inferring it from where its interface or model is installed.
3. Who can access the application and its data?
Apply least privilege to the AI tool and to the files and systems around it. Restrict access to the application, source documents, indexes, logs, and backups to people who need it for their work. Use individual accounts so access can be assigned and removed by person, and review permissions when roles change or someone leaves.
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- Limit administrator privileges to people responsible for administration.
- Remove access promptly when a user no longer needs it.
- Check whether shared folders, service accounts, or support accounts can reach client material.
- Use firm-approved access controls for both the AI interface and the underlying storage.
NIST’s February 2024 SP 1300 small-business guide recommends restricting access to sensitive information to people who need it. It is baseline cybersecurity guidance, not a legal-sector certification or a substitute for reviewing the specific deployment.
4. Are sign-in and device protections enabled?
Require strong authentication
Enable multi-factor authentication (MFA) for accounts that can access sensitive client material or administer the system. NIST’s small-business MFA guidance, updated January 5, 2026, highlights phishing-resistant methods for sensitive information and elevated privileges. Apply the firm’s authentication policy to remote access and administrative accounts as well as ordinary user sign-ins.
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Protect devices and stored data
Enable full-disk encryption on laptops and tablets that hold client information. Keep the operating system, AI runtime, dependencies, and supported security software patched; NIST SP 1300 recommends automatic updates. Use firewall and endpoint protections appropriate to the firm’s environment. These controls matter even when inference happens locally because the device and its stored files remain potential points of exposure.
5. Which network connections does the tool need?
List the connections required for model downloads, licensing, updates, connectors, remote access, and support. Have the firm’s IT or security team compare those needs with actual inbound and outbound traffic, then disable unnecessary connections and follow firm policy for network access. Check whether a setting that appears to disable a cloud feature also disables related telemetry or support traffic.
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Disconnecting a computer from the internet is not, by itself, proof that the workflow is secure. Stored files, removable media, compromised endpoints, and local users still present risks. NIST IR 8579’s draft discussion of data exposure and unauthorized access is a reminder to assess the whole environment, not just internet connectivity.
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Determine which client files, indexes, and configuration must be recoverable, and protect their backups with access controls appropriate to the underlying information. Limit who can restore them, and test restoration so the firm knows the process works. NIST SP 1300 recommends protecting and testing backups.
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Decide whether model files need to be backed up based on how they can be recovered and any applicable licensing terms; do not assume every downloaded artifact needs to be retained. Include backup copies in the retention and deletion review, since removing a working copy does not necessarily remove its backups.
7. Have privilege and professional obligations been considered?
A local installation does not settle whether using a particular tool is consistent with the rules governing a lawyer’s practice, a client’s instructions, or the terms of an engagement. North Carolina State Bar Formal Ethics Opinion 1 is specific to that jurisdiction, and its committee expressly does not decide whether sharing information with an AI tool waives attorney-client privilege. It advises lawyers to resolve privilege questions before engaging a third-party AI program with client-specific information. Rules and individual representations vary, so apply the law and professional obligations relevant to the matter.
The opinion also makes clear that lawyers remain responsible for securing client information regardless of where a program runs. The ABA’s summary of Formal Opinion 512, released July 29, 2024, identifies competence, confidentiality, client communication, and reasonable fees as relevant considerations in generative AI use. A local deployment is not an exemption from those duties.
8. How will you verify AI-generated legal work?
Security settings can reduce exposure; they cannot establish that an answer is legally correct. Before relying on generated material in a client matter, independently verify authorities, citations, facts, and analysis. North Carolina’s opinion states that lawyers remain responsible for evaluating and relying on AI work. Use the tool only for tasks the responsible lawyer can competently supervise and review.
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Ask a qualified IT or cybersecurity professional to review the deployment if the firm stores client information on its own servers, cannot confidently map the data flow, or lacks the expertise to assess the controls. North Carolina State Bar Formal Ethics Opinion 1 specifically recommends consulting an IT/cybersecurity expert when independently storing client information on local servers. A useful review should examine the actual application architecture, access, network connections, retention, updates, incident handling, and recovery arrangements—not just confirm that the model runs on a local machine.
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