On 28 October 2025 the University of Chicago Law School announced two things in one news item: required AI modules for every 1L from early 2026, and a ban on AI in the Fall Quarter of its Bigelow legal writing programme. Mandate and ban, same school, same year. That pairing is what law schools teach about AI in 2026, in miniature: the law school AI curriculum now assumes nobody can keep the tools out, and nobody wants a first-year learning to write by reading what a model wrote.
The profession did the same reversal faster: Mishcon de Reya restricted ChatGPT in March 2023 and rolled Legora out to every fee earner in July 2025. Schools are repeating the move with the extra problem that their students have no judgement yet with which to supervise the output.
The reversal: ban first, then allow, by design
Chicago’s sequence is the point. Fall Quarter: no AI while students learn research and writing basics. Winter: AI permitted under guidelines. Clinic students must disclose AI use so the class can “review and debate the quality of the AI output”. Professor Joan Neal bans AI in her contract-drafting course because students “don’t have the base-level knowledge yet to judge the AI output”. Professor Mark Templeton states the rule underneath: “When you use AI, there is a duty to supervise it like you would a junior attorney or paralegal. And to fulfill that duty, you have to be the expert yourself.”
Harvey tells firms the same: a first-year who once spent 40 hours on a markup “might now spend 5 hours reviewing an agent’s markup”, so build “intentional friction”. Chicago built it into the calendar.
Three teaching models: the sandwich, the three zones and the certificate
Suffolk’s sandwich. From 2025-26 every Suffolk 1L completes a Hotshot generative-AI track inside the mandatory Legal Practice Skills course. Professor Dyane O’Leary wants students to move “from personal users of tools like ChatGPT to professional ones”, and her image is the one to keep: “Think of it like a sandwich. The student must be the bread on both sides. What the student puts in, and how the output is assessed, matters more than the tool in the middle.”
Berkeley’s three zones. Wayne Stacy’s “AI and the Practice of Law” is three credits, more than 100 hours of hands-on training and 11 assignments, taught on Claude but “platform agnostic”. Stacy sorts work into “AI automated” low-complexity tasks that clients will not pay hourly rates for, “the disruption zone” of mid-complexity work where “judgment and oversight are critical”, and “AI augmented” work on novel arguments and strategy.
Case Western’s certificate. On 21 January 2025 Case Western Reserve became the first US law school to require every 1L to earn a legal-AI certification, “Introduction to AI and the Law”, built with Wickard.ai and taught by Oliver Roberts; Legora’s Scholars Program now puts its platform into nine schools.
| School | Requirement | Model | Distinctive rule |
|---|---|---|---|
| University of Chicago | Required 1L modules from early 2026 | Ban, then allow | No AI in Fall Quarter writing; clinic disclosure for class debate |
| Suffolk | Mandatory Hotshot track, from 2025-26 | Sandwich | The student is “the bread on both sides”; negotiation bots and an AI mock judge |
| Berkeley | Elective, 3 credits | Three zones | 100-plus hours hands-on, 11 assignments, platform agnostic |
| Case Western Reserve | Mandatory 1L certification, from January 2025 | Certificate | First in the US; built with Wickard.ai |
The bar-exam headline, corrected
Every one of these programmes exists in the shadow of a March 2023 press release: GPT-4 “passes a simulated bar exam with a score around the top 10% of test takers.” Eric Martínez of MIT re-ran the numbers in Artificial Intelligence and Law (2024). The 90th percentile holds only against the February Illinois sitting, dominated by repeat takers who had failed in July. Against July takers GPT-4 sits below the 69th percentile overall and around the 48th on essays; against those who passed, roughly the 15th on essays.
The controlled studies used law students as subjects. With GPT-4, 60 Minnesota students got “large and consistent increases in speed” but only slight quality gains; in a 2025 follow-up with a reasoning model (o1-preview) and a retrieval tool (Vincent AI), productivity rose 50 to 130% in five of six tasks and quality improved, but the reasoning model produced 11 hallucinations against 4 for students working alone and 3 for the retrieval tool. Faster and better, and nearly three times as likely to make something up.
What students actually use
No reliable survey of student tool use exists, so read the signals. O’Leary’s “personal users of tools like ChatGPT” describes the starting point, and the profession they join looks the same: 63% of AI-using Texas lawyers use ChatGPT. On r/LawSchool the argument is already the professional one, whether Westlaw’s AI or Lexis’s is safer for research, with one practising lawyer correcting the thread: “Westlaw 100% hallucinates case holdings. It just may not hallucinate case names.” That distinction, existence versus holding, is the one a student most needs; how to verify AI legal citations walks through all six layers.
What employers say graduates lack
LexisNexis’s Mentorship Gap report (nearly 900 UK lawyers, February 2026) is blunt: 72% name deep legal reasoning as the biggest skills gap, 69% weak verification and source-checking, only 2% believe AI strengthens learning, and 52% want structured verification exercises. In a case Legal Cheek reported in July 2026, a Pinsent Masons junior was criticised by a High Court judge for citing a non-existent insolvency rule after AI-assisted research.
Firms are rebuilding the training contract around this: Sidley’s London office added a mandatory “AI Knowledge Lab” seat, “a working seat, not a classroom”; Ropes & Gray lets first-years spend 20% of creditable time on AI; Latham runs a two-day AI Academy for its roughly 400 first-years. Frauke Rostalski’s warning stands behind all of it: “Replacing all junior lawyers with AI risks eroding the future pool of (senior-) experts needed for human-in/on-the-loop oversight.”
The hiring numbers, and Furlong’s warning
Legal Cheek’s June 2026 review: MinterEllison cut its 2025-26 graduate intake from 100 to 72; Latham expanded summer associates from 122 to about 170 for 2027; UK City training-contract numbers “have in fact remained stable for the past half a decade”; Law.com found US first-year headcount at the 100 largest firms “stayed essentially flat between 2024 and 2025”.
Jordan Furlong drew the conclusion in April 2024, when Am Law 100 first-year hiring had fallen about 17% in one cycle: “we will effectively be licensing unemployable lawyers.” His later caution applies to schools too: “be careful not to confuse ‘digitally native’ with ‘technologically savvy’.” In Germany, a Bucerius Law School and Simon-Kucher study (March 2025) found two-thirds expect significant AI disruption but only a fifth expect their own Kanzlei to be directly affected. Will AI replace junior lawyers? goes through the hiring evidence in full.
A self-taught curriculum for the student who is not getting one
If your school offers nothing, build the course yourself in six steps: how LLMs work and why they invent cases; which ChatGPT, Claude and Gemini tiers train on inputs; three sanctions opinions read and five citations checked by hand; O’Leary’s on-ramp, “a low-stakes, casual environment with topics familiar to them — cooking, travel, home repair”, then 30 minutes a day on legal tasks; drills; and Chicago’s friction, drafting by hand before comparing.
Drill me on [the enforceability of restrictive covenants in [jurisdiction]]. Ask one question at a time, from fundamentals to difficult, and wait for my answer. After each answer: what was right, what was missing, the correct answer and the authority I should read, tagged [VERIFY]. Be strict; I would rather be wrong here than in practice. Stop after ten questions and list my weak spots.Build me a six-week plan of 30 minutes a day to become competent with [Claude / ChatGPT] for [litigation / transactional] work as a law student, using only public or invented materials, never client data. Each day: one task, the prompt pattern it teaches, a success criterion and what could go wrong. Week 1: low-stakes personal tasks. Week 2: summarising cases. Week 3: a memo section, every citation checked in a database. Week 4: a contract against a checklist. Week 5: a reusable Project. Week 6: one full workflow. End with a self-assessment.Advice for faculty, and for the partner supervising a trainee
Sequence, not prohibition: a no-AI term followed by supervised use builds the base knowledge Neal says students lack. Assess the bread, not the filling: grade what went in and how the output was judged. Run verification exercises with planted fakes; 52% of surveyed lawyers asked for them. And keep the friction: hand-drafting before comparison is how craft survives.
Set up a two-hour exercise for [1L students / first-year associates] on [reviewing five clauses of a services agreement]. Step 1: each participant marks up the clauses by hand in 45 minutes, no AI. Step 2: run [our review prompt] on the same clauses. Step 3: a table of issues found by the person only, the AI only, both, neither (instructor adds). Step 4: five questions on why the AI missed what it missed. Step 5: a final markup. Produce the instructions and the table template.Where to go next: the learning paths hub collects the training guides; AI for law students is the practical companion to this page; the best AI courses for lawyers compares what is on offer after graduation. Sidley made an AI seat mandatory; AI Lab for Lawyers gives you the same eight hours of supervised, hands-on practice without waiting for a firm.
Frequently asked questions
Do law schools allow ChatGPT?
The direction is towards allowing generative AI under rules, and several schools now require training in it. The University of Chicago bans AI in the Fall Quarter of its 1L writing programme, permits it in winter under guidelines and requires clinic students to disclose use so the class can debate the output. Suffolk and Case Western Reserve make an AI course mandatory for every 1L. Individual professors still ban it where students lack the base knowledge to judge the output.
Which law schools teach AI?
Case Western Reserve was first to require a legal-AI certification for all 1Ls in January 2025; Suffolk made a Hotshot generative-AI track mandatory from 2025-26; the University of Chicago is rolling out required 1L modules in early 2026; Berkeley runs Wayne Stacy's 100-plus-hour 'AI and the Practice of Law'; Washington University embeds AI in 1L legal research; Drake offers an AI Law Certificate; and Legora's Scholars Program supplies nine schools with its platform.
Did AI pass the bar exam?
GPT-4 passed a simulated Uniform Bar Exam in March 2023, but OpenAI's 'top 10%' claim was overstated. Eric Martínez showed the 90th percentile holds only against the February Illinois sitting, dominated by repeat takers. Against July takers GPT-4 scored below the 69th percentile overall and around the 48th on essays; against those who passed, around the 48th overall and roughly the 15th on essays. Passing an exam also says nothing about inventing citations in a brief.
What AI skills do law graduates lack?
Verification and judgement. LexisNexis's Mentorship Gap report of nearly 900 UK lawyers found 72% name deep legal reasoning as the biggest skills gap, 69% weak verification and source-checking, and only 2% believe AI strengthens learning. The Ninth Circuit's standard in Lnu v. Blanche, a case involving briefs by unlicensed law graduates, is that a competent lawyer must do more than check citations exist: 'A competent and diligent attorney must also read and reason.'
Should law students learn prompt engineering?
Yes, but as the smaller half of the skill. Berkeley's Wayne Stacy says 'the workflows are really the secret sauce', and Suffolk's Dyane O'Leary says what the student puts in and how the output is assessed matter more than the tool. Learn how models fail, which tier of ChatGPT or Claude trains on your inputs, how to verify a citation in a real database, and practise in low-stakes settings first. The prompt is the easy part.