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Litigation Associate

Draft motions and briefs

Enhances✓ Available Now

What You Do Today

Write motions to dismiss, summary judgment briefs, discovery motions — building the written advocacy that wins cases before trial

AI That Applies

AI generates first drafts of legal briefs from research and case facts, following court-specific formatting and citation requirements

Technologies

How It Works

The system ingests research and case facts as its primary data source. A language model generates initial drafts by synthesizing the input context with learned patterns, producing text that follows the specified tone, format, and domain conventions. The output — first drafts of legal briefs from research and case facts — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

First drafts are AI-generated in hours; you edit, strengthen arguments, and add the strategic framing that makes briefs persuasive

What Stays

The art of persuasive writing — the opening paragraph that grabs the judge, the argument structure that builds inevitably to your conclusion

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for draft motions and briefs, understand your current state.

Map your current process: Document how draft motions and briefs works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The art of persuasive writing — the opening paragraph that grabs the judge, the argument structure that builds inevitably to your conclusion. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Harvey AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long draft motions and briefs takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your general counsel or managing partner

What's our current capability gap in draft motions and briefs — and is it a people problem, a tools problem, or a process problem?

They set the firm's AI adoption posture

your legal technology manager

How would we know if AI actually improved draft motions and briefs — what would we measure before and after?

They manage the tools and can show you capabilities you don't know exist

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.