AI for Family Lawyers: Standard Petitions, Financial Discovery and the Client Who Uses ChatGPT

Two Reddit posts from September 2026 sum up AI for family lawyers. A divorce lawyer on r/Lawyertalk: “I do divorce, and AI is great for it, no need for a ton of legal research or cites, and it cranks out standard petition and motions easily.” A family lawyer on r/legaltech: “I can’t get clients to even try to respond to interrogatories asking why they want custody of their own children without using AI. Even Jim Bob is suddenly opining about the best interest of the children and objecting to relevance.”

Both are right. On your side of the desk, a model that drafts a standard petition and turns two years of bank statements into a spreadsheet is a gift. On the client’s side, the same tool is summarising your advice, rehearsing custody arguments and building a discoverable record.

Why AI for family lawyers works: standard forms, few citations

Family practice is fact-heavy and citation-light: standard forms, statutory guidelines, and a fight over money, houses and children rather than over which appellate case controls. That is where language models perform best: work grounded in documents you supply, not finding the law on their own.

Judge Brantley Starr said as much in the first AI standing order in the United States, in May 2023: these platforms “have many uses in the law: form divorces, discovery requests, suggested errors in documents, anticipated questions at oral argument. But legal briefing is not one of them” (Courthouse News). A New York solo told Clio’s 2025 Legal Trends Report that clients now “literally populate their own divorce forms” at intake, work that used to take him two or three hours.

Lawyer-side workflows: petitions, separation agreements, chronologies

Rech Law’s inventory of what a family firm does with AI is a fair one: first drafts of forms and separation agreements; summarising document sets; comparing financial statements, texts, valuations and expert reports; flagging disclosure inconsistencies; intake questionnaires. Its house rule is the one to copy: “Use AI for preparation, not final product.”

Start with the issue list:

You are assisting a [state]-qualified family lawyer acting for the [wife/husband].
List every issue a [state] separation agreement should address for a couple with [minor children / a jointly owned home / a family business / pensions], organised by category.
Under each issue, list the questions I must ask my client before drafting it, and flag any issue where [state] law imposes a mandatory term or court approval, tagged [VERIFY].
Do not cite cases. Do not draft clauses yet. If unsure whether a rule applies in [state], say so.

The second everyday task is the message chronology: custody disputes arrive as thousands of texts, the model sorts them by date and topic and quotes any commitment or refusal verbatim, and you read the ones that matter (method in the case chronology guide). Forbid it from characterising either parent’s conduct.

Financial discovery: bank statements into a spreadsheet

A family lawyer on r/Lawyertalk describes the workflow that has probably saved more divorce hours than any other: feed a couple of years’ worth of bank and credit-card statements to a model, ask for specific payment types or recipients, and export the results to Excel.

From the attached statements (anonymised, OCR'd), extract every transaction matching any of these criteria: payee or reference containing [names / keywords]; amounts over [X]; transfers to accounts not in <known_accounts>; cash withdrawals over [Y]; recurring payments to the same payee.
Output a CSV: Date | Account | Payee/Reference (verbatim) | Amount | Criterion matched | Statement page. Then a summary table by payee with totals and date range.
State how many transactions you processed and how many pages you could not read. Do not estimate any amount you cannot read.

Then the part the model cannot do: Thomson Reuters’ prompting guidance says these systems are weak at “math, counting, and sorting”, so totals are recomputed in Excel, the processed count is compared to the real line count, and every row you will rely on is opened at the statement page.

What clients do with ChatGPT (and why it hurts them)

Ward and Smith’s family team catalogued what divorcing clients actually do with a chatbot: summarising attorney communications, brainstorming custody arguments, reorganising financial documents, analysing the spouse’s discovery responses, drafting agreements and preparing for depositions.

A Texas family lawyer describes clients who now draft “pleadings” with “little bearing on Texas law and procedure”. Three harms follow. The chatbot is wrong about your state’s procedure. It expands the dispute, so every interrogatory answer becomes a brief and the bill grows. And it creates a record.

Privilege: forwarding your advice to a chatbot

Ward and Smith’s warning is blunt: “sharing information with them can waive privilege just as easily as forwarding a confidential email to a stranger.” A paid subscription changes nothing if the terms reserve rights over the data.

The case law caught up in 2026. In United States v. Heppner (S.D.N.Y., bench ruling 10 February 2026, memorandum 17 February 2026) Judge Rakoff held that roughly 31 documents of a defendant’s own consumer-Claude exchanges were protected by no privilege and no work-product doctrine.

“Because Claude is not an attorney, that alone disposes of Heppner’s claim of privilege.” — Judge Jed Rakoff, United States v. Heppner (S.D.N.Y. 2026), via Orrick

England reached the same place by another route: the Upper Tribunal held in [2026] UKUT 81 (IAC) that putting client letters into “an open source AI tool, such as ChatGPT, is to place this information on the internet in the public domain, and thus to breach client confidentiality and waive legal privilege”. More in does using ChatGPT waive attorney-client privilege.

The subpoena for “all communications with AI-based tools”

Ward and Smith now tells clients to expect deposition questions about AI use and subpoenas for “all communications with AI-based tools, including prompts, inputs, and outputs”. “Deleted” is a promise, not a guarantee: under the preservation order in the New York Times litigation OpenAI kept every deleted Free, Plus, Pro and Team chat from 13 May to 26 September 2025, and in January 2026 Judge Stein affirmed production of 20 million de-identified logs. And courts already order litigants to say which tool they used: Morgan v. V2X (D. Colo., 30 March 2026) required exactly that.

“Use AI for preparation, not final product”

Rech Law’s rule draws the line where the courts draw it. The model prepares: issue lists, chronologies, tracing spreadsheets, first drafts of standard motions. The lawyer produces the petition, the parenting plan and the settlement advice. The client produces the affidavit, in their own words. The American Academy of Matrimonial Lawyers expects attorneys to “carefully review” any AI-generated parenting plan or financial calculation, and the Supreme Court of New South Wales bans generative AI from generating the content of affidavits outright.

Sanctions in family cases: Massachusetts, Nebraska, Victoria, Berlin

The Nebraska court’s sentence belongs above the desk: “Citing nonexistent case law or misrepresenting the holdings of a case is making a false statement to a court. It does not matter if [generative AI] told you so.” The Berlin case shows why “the citation resolves” is not verification: per the BRAK, the fake combined a real FamRZ page range with a wrong file number. More are in AI hallucination cases in the UK, Germany and Europe.

Custody prediction tools and other controversies

“Will AI decide my custody case?” is a real client question. The honest answer, from Steele Family Law’s survey of the field: a 2021 PLOS study reported predicting joint-custody outcomes with “over 85% accuracy” on Spanish court data, but no official judicial AI system exists; the tools in daily use are parenting apps (CoParenter, OurFamilyWizard) that propose schedules and calculators (SupportPay) that compute support.

The commercial change is elsewhere. Divorce.law runs a consumer chatbot that routes leads to participating firms at $155 a month. The divorce client’s first conversation is increasingly with a chatbot, and the firm it names gets the call; see getting your firm recommended by ChatGPT.

The client handout: “Before you paste that into ChatGPT”

ABA Formal Opinion 512 says boilerplate engagement-letter language about AI “is not sufficient” for informed consent; the same goes for a warning in the other direction. Give clients one page, six rules: nothing I send you goes into any AI tool (Ward and Smith’s directive: “Do not input, paste, upload, or otherwise transmit any legal advice, attorney communications, case documents, financial information, or strategy discussions into any public AI tool”); chatbot conversations can be subpoenaed, deleted or not; a chatbot does not know [state] family law or our judge; declarations are written in your own words; if a chatbot contradicts my advice, call me first; and a yes-or-no question gets a yes or a no. Lawyers on r/LawFirm now answer AI-drafted client memos with “Need a yes or no on X. No memo”, and at least one provides that “replying to unduly burdensome AI slop gets me on hourly full rate regardless of the agreed fee structure”.

Draft a one-page handout for family-law clients of a [state] firm titled "Before you paste that into ChatGPT".
Audience: a divorcing client with no legal training, reading on a phone. Plain English, short sentences, no lecturing.
Cover: never enter our advice, emails, case documents, finances or strategy into any public AI tool; chatbot conversations can be subpoenaed and are not privileged; chatbots do not know [state] family law; declarations must be in your own words; call us before acting on anything a chatbot says; short direct answers help your case and your bill.
Then a three-sentence engagement-letter clause saying the same formally. Under 350 words. Cite no cases.

More client-facing prompts are in the prompt library and in AI for client communication. The client warning and the standard-motion workflow are the kind of exercise built live, in browser tools and on anonymised material, in AI Lab for Lawyers.

Where to go next: the practice-area hub covers the neighbouring fields, and AI for estate planning lawyers deals with the same client-side problem when the document is a will.