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Litigation Associate

Prepare trial exhibits and presentation

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What You Do Today

Select and organize trial exhibits, create demonstratives, build the visual story that helps the jury understand complex facts

AI That Applies

AI helps organize exhibits, generate timelines from evidence, and create visual presentations that simplify complex facts

Technologies

TrialDirectorSanctionPresentation tools

How It Works

For prepare trial exhibits and presentation, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — timelines from evidence — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Trial preparation is more efficient; AI creates timelines and exhibit indexes from case data automatically

What Stays

Trial strategy — what story to tell, which exhibits support it, and how to present complex facts simply — is the art of trial advocacy

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 prepare trial exhibits and presentation, understand your current state.

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Map your current process: Document how prepare trial exhibits and presentation works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
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Identify the judgment points: Trial strategy — what story to tell, which exhibits support it, and how to present complex facts simply — is the art of trial advocacy. These are the boundaries AI won't cross.
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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 TrialDirector 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 prepare trial exhibits and presentation 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 data do we already have that could improve how we handle prepare trial exhibits and presentation?”

They set the firm's AI adoption posture

your legal technology manager

“Who on our team has the deepest experience with prepare trial exhibits and presentation, and what tools are they already using?”

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

a client who's adopted AI in their legal department

“If we brought in AI tools for prepare trial exhibits and presentation, what would we measure before and after to know it actually helped?”

Their expectations for outside counsel are shifting

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.

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