AI training for lawyers: from documents to useful briefing notes

At Syntalith, we propose team training built around the documents and writing your team handles regularly. Preparation includes choosing recurring tasks and agreeing on tools and exercise materials. During the sessions, authors revise their work with feedback from the instructor and the people who read it. The scope can cover matter chronologies, comparisons of contract drafts, and explanations for business colleagues.

From organizing a matter to writing for its reader

A chronology starts with correspondence and documents from which the author needs to select events relevant to the matter. AI helps organize a first draft. The author adds source references and resolves discrepancies before handing it over. A colleague can then open the relevant message rather than search the entire collection for the basis of each sentence.

In contract work, a list of differences is the beginning. The lawyer still needs to identify a change that warrants discussion, describe it using the correct versions, and prepare a question for someone who understands delivery of the service. The program connects those tasks with drafting short correspondence. A reviewing lawyer needs a different level of detail from an operations manager asked to explain what their team can provide.

Suppose an earlier contract draft called for a monthly service report and the revised draft calls for a weekly one. An AI summary described the changes as editorial. After comparing the documents, the author prepares a short note: “The reporting frequency has changed from monthly to weekly. Please confirm whether the service delivery team can prepare a report each week.” They include references to both provisions.

During the discussion, the instructor helps the author preserve the precise basis for that statement and make the business question easy to find. The lawyer responsible for the matter contributes the substantive review; the session addresses working with the tool and the text. In a later independent exercise, only a section heading changes, so the author writes a different summary that reflects the new material.

Workload cost: a scenario to test in 2026

According to Noy and Zhang (2023), average completion time for the studied writing tasks fell by 40%.

In the same study, rated output quality increased by 18%.

The experiment involved 453 college-educated professionals doing professional writing tasks. This workflow needs its own measurement.

Calculation scope: legal briefing-note preparations. These are hypothetical pilot assumptions. Assume a monthly volume of 60 cases. Manual completion takes 45 minutes per case. Assume assisted completion takes 34 minutes per case. During that time, a lawyer checks the chronology and source passages before senior review. Corrections and manual completion of exceptions are included.

In this scenario, monthly manual workload is 45 hours.

Monthly workload after the change is 34 hours.

The team recovers 11 hours per month in this scenario.

Formula: 60 × 45 / 60 = 45.

Formula: 60 × 34 / 60 = 34.

Formula: 60 × (45 − 34) / 60 = 11.

Setup, software and maintenance remain in the budget. Recovered time provides capacity for other work. Source material for assessing the scope supplies context; the timings and volumes are assumptions for this scenario. Source and calculations checked: 21 October 2026.

Feedback on writing the team actually produces

Useful feedback identifies a particular passage to improve. In a chronology, that might be a sentence without a document reference. In a business email, it might be a question buried beneath a long account of the changes. The instructor helps the author revise the passage, while the reader checks whether it now gives them what they need to continue their work.

The division of work shapes the exercises. Junior lawyers preparing material need time to draft and revise it. A partner or in-house reviewer brings the questions they regularly send back to authors. Legal operations helps establish how documents and versions should be referenced so colleagues can find them. We agree with the team on where these roles should join the sessions.

Professional experience does not determine familiarity with AI. Someone new to the tool needs time to prepare and edit a draft. A more confident user can work with longer correspondence or several document versions. A workshop can focus on one type of material, or a series can include independent work between meetings and discussion at the next session. If the need concerns one person, our comparison of individual and group training can help with the format decision.

What the existing tool already provides

Microsoft describes document comparison in Word, which displays differences between two versions in a new document. If the team's main need is to find textual changes, start by checking that feature. Our proposed AI training addresses the work that follows: synthesizing the material, framing questions, and explaining it to the reader.

The firm or legal department identifies the tools and documents permitted for the sessions. Exercises can use fictional material without client files. If the main difficulty is finding earlier work, the team may need to organize its collection or consider the separate option covered in our article on an AI knowledge base for law firms.

Starting with Syntalith

The first conversation concerns a piece of writing that regularly goes back to its author: what the reviewer has to reconstruct and what the business reader is missing. That helps us select the tasks and identify who should join the discussion of the drafts.

The proposal sets out the practice included, materials participants can retain, and feedback arrangements, including any review of work between sessions. The team supplies knowledge of its matters and legal judgment. See Syntalith's pricing for service options.