The output reads well immediately. That is the benefit and the hazard, and they arrive together.
Start a conversation with the AI Adoption Concierge, already scoped to drafting. Pick a starting point, or describe your situation directly.
Drafting is where most firms feel the gain first, because the change is immediate and visible: a first draft of a routine document appears in a fraction of the time it took to produce. The saving is real and it is concentrated at a specific point — the blank page, which is where a surprising share of drafting time actually goes. The hazard is specific too. Generated prose is fluent by construction, and fluency is what reviewers use as a proxy for correctness. A draft that reads like a competent lawyer wrote it receives lighter scrutiny than a rough one, exactly when the errors are subtle: a defined term used inconsistently, a standard clause that does not fit this deal, a provision that reads sensibly and allocates risk the wrong way.
Strongest at the top, weakest at the bottom — and the bottom is where the money is.
Getting a conventional document shaped correctly. Reliable and a genuine time saver.
Standard agreements, letters, routine filings. Large saving where the form is well-established.
Turning something dense into something a client can read. Consistently good.
Defined terms and cross-references drift. Needs a deliberate pass, and reviewers rarely make one.
It will produce something conventional. Conventional is often wrong for this deal.
The commercial substance. This is the lawyer's judgement and it does not transfer.
How firms make drafting assistance work.
Whether the saved time turns into capacity or into a correction later.
Reviewers use polish as a proxy for care. Generated text is polished before it is correct, which inverts the signal — and the errors that survive are the quiet ones about substance.
Adapt a precedent, in almost every case. Supplying your own form and asking for it to be adapted to these facts keeps the firm's positions, its risk allocations and its accumulated judgement in the document, and it narrows the task to something the tool is genuinely good at. Generating from nothing produces a document reflecting whatever was conventional in the training data, which is a different firm's risk appetite at best. The gap in output quality between these two approaches is larger than the gap between most tools.
The same review as a junior's draft, plus a specific mechanical pass. The mechanical pass — defined terms used consistently, cross-references pointing at real provisions, party names and dates correct throughout — matters because these are exactly the errors fluent text conceals and human drafters make less often. Then substantive review on the clauses that carry the commercial risk, done as though a stranger drafted it. The failure pattern is a reviewer who reads for quality of prose, finds it good, and stops.
Practice varies and the safe reading is that it depends on the engagement, the jurisdiction and what the client has been told previously. The relevant obligations are around communication and fees rather than any specific AI rule: a client is generally entitled to know material facts about how their matter is being handled, and if AI use materially affects the work or the bill, that starts to look material. Some firms address it once in the engagement letter, which is cleaner than deciding matter by matter. Check what your own jurisdiction has said.
Treat prompts as firm knowledge rather than personal technique, because otherwise you get as many drafting standards as you have lawyers. When someone finds an approach that produces good drafts of a document type the firm produces often, that belongs in a shared library with the firm precedent it works against. This is unglamorous and it is where the durable gain lives — individual experimentation produces individual gains that leave when the person does.
Describe what your firm drafts most often. The Institute will help you build the workflow.