AI in an Immigration Practice: Where It Helps and Where It Bites

High-volume immigration work is built on repetition: similar petitions, recurring evidentiary standards, and large records that must be marshaled under deadline. That structure is exactly where general-purpose AI tools can save time, and exactly where sensitive client data and unverified output can do real harm.

Where AI fits a high-volume immigration practice

An immigration practice runs on document assembly and pattern. A firm may file dozens of family-based petitions, employment cases, or humanitarian applications a month, each with overlapping forms, exhibit structures, and legal standards. AI tools, used carefully, can compress the mechanical parts of that work so attorneys spend their hours on judgment rather than formatting.

Three uses are the most concrete in an AI immigration law practice:

• Drafting and revising RFE responses. A Request for Evidence is USCIS asking for more proof before deciding a case. It arrives as a Form I-797 notice that states the specific deficiencies and a response deadline printed on the notice. The reasoning structure of a response is consistent: identify each item USCIS flagged, state the governing standard, and tie specific exhibits to each element. A model can produce a first draft of that skeleton quickly from the officer's stated grounds.
• Assembling petition packets. Cover letters, exhibit indexes, tables of contents, and form-to-evidence cross-references are repetitive and error-prone when done by hand across a high caseload. AI can draft an index, draft a cover letter that lists what is enclosed, and flag where a stated exhibit is missing from the set.
• Summarizing records. Country-conditions reports, medical records, prior filings, and lengthy declarations can run to hundreds of pages. A model can produce a working summary or a chronology that a lawyer then checks against the source, which is faster than reading cold.

None of this is the practice of law on its own. It is drafting and organization that a supervising lawyer must own. The value is in the first draft and the structure, not in the final judgment.

Drafting RFE responses without outsourcing judgment

An AI RFE response workflow is most useful when it is narrow. Give the model the officer's stated grounds and your own outline of the governing standard, and ask for a structured draft that addresses each point in turn. Keep the legal standard in your own hands. The risk is not that the model writes a clumsy paragraph; the risk is that it states the wrong standard, invents a regulatory citation, or asserts a fact about your client that is not in the record.

Two failure modes deserve naming. First, fabricated authority. Generative tools produce fluent, well-formatted citations that do not exist. In Mata v. Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023), Judge P. Kevin Castel imposed a $5,000 sanction under Rule 11 after attorneys submitted a brief containing fake cases generated by ChatGPT, including fabricated quotations and internal citations. The court found the lawyers had acted in bad faith by standing behind the citations after their authenticity was questioned. The same pattern reached a federal court of appeals in Park v. Kim, 91 F.4th 610 (2d Cir. 2024), where the court referred an attorney to its grievance panel after she cited a nonexistent case she admitted she had generated with ChatGPT and could not produce when asked. The lesson carries directly into immigration filings: an RFE response or a brief to an immigration court that cites a regulation, a precedent decision, or a policy provision must be checked against the primary source before it goes out.

Second, invented facts. A model asked to make a response persuasive may assert that a beneficiary meets a criterion, or describe a document that is not in your file. In an immigration matter, an overstatement about eligibility or a misdescribed exhibit is not a stylistic problem; it can expose the client to a misrepresentation finding. Treat every factual sentence the model writes as a claim to verify, not a fact to adopt.

Petition packets and record summaries: useful, with guardrails

For immigration petition AI support, the safe pattern is to let the tool organize known material rather than supply missing material. Drafting an exhibit index from a list of documents you actually have is low risk and high value. Asking a model to tell you what evidence a given petition category requires is higher risk, because the requirements are governed by statute, regulation, and the USCIS Policy Manual, and a general model may state them imprecisely or describe a superseded standard. Use the tool to format and cross-check what you have assembled, and keep the eligibility analysis with the lawyer.

Record summaries carry their own trap. A summary that omits an adverse fact, or smooths over an inconsistency between a declaration and a prior filing, is worse than no summary, because it can lull the reviewing attorney into missing the exact problem an officer will see. When you use a model to summarize a record, treat the summary as an index that points you back to pages to read, not as a substitute for reading the parts that matter. For declarations and country-conditions evidence, the lawyer still has to confirm that the cited support actually says what the summary claims.

Confidentiality: immigration data is unusually sensitive

Immigration files concentrate some of the most sensitive information a firm holds: immigration status and history, Alien Registration Numbers, passport and biometric data, family relationships, medical and psychological records, criminal history, and, in asylum and related matters, detailed accounts of persecution, harm, and the identities of people still abroad. A confidentiality failure here is not merely an embarrassment. It can endanger people.

That raises the central technical question before any tool touches a client file: what does the tool do with what you put into it. The relevant distinction is between a consumer service that may retain inputs and use them to train models, and an enterprise or business offering that contractually commits not to train on your data and provides appropriate security and retention controls. Under ABA Model Rule 1.6 and its requirement that a lawyer make reasonable efforts to prevent unauthorized disclosure of client information, a lawyer should understand a tool's data handling before entrusting client material to it. The Florida Bar made the same point in Ethics Opinion 24-1 (January 19, 2024), framing protection of client confidentiality under Rule 4-1.6 as the lawyer's first responsibility when using generative AI, and noting that a self-learning tool may expose one client's information to others. The California State Bar's Practical Guidance for the Use of Generative Artificial Intelligence in the Practice of Law (November 16, 2023) likewise warns against inputting confidential client information into tools that may lack adequate security.

Practical confidentiality discipline for an immigration practice:

• Use only tools whose terms commit not to train on your inputs and that offer enterprise-grade security and a defined retention policy. Read the terms, do not assume them.
• Prefer to minimize. Strip A-numbers, dates of birth, and names where the drafting task does not require them, and reinsert identifiers in your own system.
• Be especially cautious with asylum and humanitarian files, where disclosure can reach people who are not your client and who may be at risk.
• Confirm whether your obligations require client notice or informed consent before particular client information goes into a given tool, and document that decision.

What the bars expect, and where fees come in

The governing framework is not new ethics, it is settled duties applied to a new tool. ABA Formal Opinion 512 (July 29, 2024), the Standing Committee on Ethics and Professional Responsibility's first formal guidance on generative AI, ties lawyers' use of these tools to existing Model Rules: competence (Rule 1.1, including the comment 8 duty to keep abreast of relevant technology), confidentiality (Rule 1.6), communication and candor, the supervisory duties of Rules 5.1 and 5.3, and reasonable fees under Rule 1.5. The opinion stresses that a lawyer must independently verify or review AI output rather than rely on it uncritically, and must consider whether client consent or disclosure is warranted.

Two points land hard in a high-volume practice. The first is supervision. Paralegals and junior staff often run the document assembly. Rules 5.1 and 5.3 make the lawyer responsible for the work product regardless of who or what produced the draft, which means a firm needs an actual policy: which tools are approved, what may be entered, and what verification is required before a filing leaves the office. The second is fees. The California guidance is direct that a lawyer may bill for time actually spent, such as crafting and refining inputs and reviewing outputs, but must not bill the client for time the tool saved as though the lawyer had spent it. Florida Opinion 24-1 makes a parallel point about reasonable and non-duplicative charges. In a practice that bills flat fees per matter, the cleaner posture is to treat AI as an efficiency that benefits the firm and the client, not as a line item that recreates hours that were never worked.

A working checklist

Before AI touches an immigration matter, a firm can hold itself to a short standard:

• Tool diligence. Confirm the tool does not train on your inputs and provides adequate security and retention controls. Read the terms.
• Data minimization. Remove identifiers the task does not need; reinsert them in your own system.
• Standard stays with the lawyer. Supply the governing standard yourself; do not ask a general model to tell you what the law requires.
• Verify every citation. Check each regulation, precedent decision, and policy provision against the primary source. Assume nothing the model cites exists until you confirm it.
• Verify every fact. Treat each factual sentence about your client or the record as a claim to check against the file.
• Read the parts that matter. Use summaries as a map back to the source, especially for declarations and adverse facts.
• Written policy and supervision. Approve specific tools, define permitted inputs, and assign verification responsibility under Rules 5.1 and 5.3.
• Honest billing. Charge for work done, not for time the tool saved.

Used this way, AI is a competent drafting and organizing assistant for the repetitive spine of immigration work, and nothing more. The judgment, the verification, and the duty to the client stay where they have always been.

This is general information for lawyers and law-firm leaders, not legal advice, and it does not create an attorney-client relationship. The authorities are cited so you can read them yourself.