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General Counsel

Intellectual Property Protection

Enhances✓ Available Now

What You Do Today

Protect the company's IP — patents, trademarks, trade secrets, copyrights. Monitor for infringement, manage the IP portfolio, and enforce rights when needed.

AI That Applies

AI-powered trademark and patent monitoring that scans filings, publications, and web content for potential infringement or conflicting applications.

Technologies

How It Works

For intellectual property protection, the system draws on the relevant operational data and applies the appropriate analytical models. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Infringement detection becomes continuous rather than periodic. AI catches trademark squatters and copycat products across global markets in real time.

What Stays

IP strategy — which innovations to patent, which to protect as trade secrets, and when infringement is worth pursuing versus ignoring.

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 intellectual property protection, understand your current state.

Map your current process: Document how intellectual property protection works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: IP strategy — which innovations to patent, which to protect as trade secrets, and when infringement is worth pursuing versus ignoring. 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 Natural Language Processing 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 intellectual property protection 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 intellectual property protection?

They set the firm's AI adoption posture

your legal technology manager

Who on our team has the deepest experience with intellectual property protection, 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 intellectual property protection, 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.