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Legal Project Manager

Scope and plan a new litigation matter

Enhances◐ 1–3 years

What You Do Today

Meet with the lead partner, break the case into phases and tasks, estimate hours by timekeeper level, create the project timeline, set milestones, and establish the communication cadence with the client.

AI That Applies

Matter planning AI generates project plans from case parameters, referencing historical data from similar matters to estimate hours, timelines, and resource needs by phase.

Technologies

How It Works

The system ingests case parameters as its primary data source. Predictive models fit to historical outcome data identify which variables are the strongest leading indicators, then apply those weights to current inputs to generate forward-looking scores. The output — project plans from case parameters — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Scoping becomes data-driven. AI estimates are based on actual historical performance across similar matters, not just partner intuition about how long things take.

What Stays

You still negotiate the plan with the lead partner, adapt for case-specific complexity, manage client expectations, and adjust when the case takes unexpected turns.

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 scope and plan a new litigation matter, understand your current state.

Map your current process: Document how scope and plan a new litigation matter works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: You still negotiate the plan with the lead partner, adapt for case-specific complexity, manage client expectations, and adjust when the case takes unexpected turns. 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 Legal Project Management 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 scope and plan a new litigation matter 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 the current accuracy of our forecasting, and how would we know if an AI model is actually better?

They set the firm's AI adoption posture

your legal technology manager

Which historical data do we have that's clean enough to train a prediction model on?

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.